[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"_public_publisher_byId_cb0af3f9-cebc-4e74-800b-18bd53eeec34":3,"_public_publication_all{\"sortAscending\":false,\"sortField\":\"updateTime\",\"page\":0,\"size\":10,\"facet\":true,\"searchKey\":\"publisherId:cb0af3f9-cebc-4e74-800b-18bd53eeec34,\"}":255},{"code":4,"data":5,"meta":20},"SUCCESS",{"id":6,"createTime":7,"updateTime":8,"relativeEntities":9,"slug":10,"properties":11,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":22,"manageAffiliations":29,"indexDatabases":45,"url":20,"thumbnailPath":20,"statistic":80,"gsStatistic":20,"type":20,"analyzePriority":20},"cb0af3f9-cebc-4e74-800b-18bd53eeec34","2024-04-15T01:05:47.685+00:00","2025-11-21T10:01:53.033+00:00",[],"Springer-Science-and-Business-Media-LLC",{"issn":12,"title":14,"eissn":16},{"VOID":13},"0177-798X",{"EN":15},"Springer Science and Business Media LLC",{"VOID":17},"1434-4483","PUBLISHER","PENDING",null,0,[23],{"id":24,"createTime":20,"updateTime":20,"relativeEntities":25,"label":26,"description":28,"parentId":20,"standard":20,"scholarHubFieldId":20},"7265df54-3387-44e5-811f-17ef2fe075cc",[],{"EN":27},"Atmospheric Science",{},[30,38],{"id":31,"createTime":20,"updateTime":20,"relativeEntities":32,"slug":20,"properties":33,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":36,"statistic":20},"40bcdc2a-a6a2-4279-97a2-b906d6bbf8d5",[],{"title":34},{"EN":35},"Springer-Verlag Wien",[37],"9a7c7208-b28a-42c2-a634-5a7f90eee3ab",{"id":39,"createTime":20,"updateTime":20,"relativeEntities":40,"slug":20,"properties":41,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":44,"statistic":20},"2d97ae22-94a3-42b2-9a54-cadfd8dc26ab",[],{"title":42},{"EN":43},"SPRINGER WIEN",[37],[46,63],{"id":47,"indexDatabase":48,"url":58,"indexYears":59,"academicFieldIds":60,"indexDatabaseRanking":62},"b295d57e-5156-4a53-9477-2a4382a2cfc3",{"id":49,"createTime":20,"updateTime":20,"relativeEntities":50,"label":51,"description":53,"key":55,"publicationTags":56,"standard":20},"3c7051d4-eb7d-4c57-a56b-36fc74c5d1e9",[],{"EN":52,"VI":52},"Scopus - Elsevier",{"EN":52,"VI":54},"Cơ sở dữ liệu Scopus thuộc Elsevier","scopus",[57],"SCOPUS","https:\u002F\u002Fwww.scopus.com\u002Fsourceid\u002F14171","1986-2025",[61],"6fa1c73d-6535-4f6f-b522-fcab15fc4a84","SCOPUS__Q2",{"id":64,"indexDatabase":65,"url":77,"indexYears":20,"academicFieldIds":78,"indexDatabaseRanking":20},"2b58981a-3c73-424f-84b6-2f0c506579ff",{"id":66,"createTime":20,"updateTime":20,"relativeEntities":67,"label":68,"description":70,"key":73,"publicationTags":74,"standard":20},"a4921856-b128-4d9f-8f1f-e80813d3bbd4",[],{"EN":69,"VI":69},"ISI\u002FSCIE - Science Citation Index Expanded",{"EN":71,"VI":72},"SCIE database","Cơ sở dữ liệu SCIE","scie",[75,76],"SCIE","ISI","https:\u002F\u002Fmjl.clarivate.com\u002Fsearch-results?issn=0177-798X",[79],"743809e9-ecc4-4c97-9a58-e2cbbb0d0ce9",{"impactFactor":21,"impactFactorByYear":81,"i10Index":93,"i10IndexLast5Year":94,"totalPublication":95,"totalPublicationByYear":96,"totalCitation":147,"totalCitationByYear":148,"totalCitationPerPublication":192,"totalCitationPerPublicationByYear":193,"hindexLast5Year":130,"hindex":130},{"2012":82,"2013":83,"2014":84,"2015":85,"2016":86,"2017":87,"2018":84,"2019":88,"2020":89,"2021":90,"2022":91,"2023":92},0.31,0.26,0.47,0.45,0.3,0.33,0.42,0.75,1.05,0.86,0.65,461,108,4869,{"1948":97,"1949":98,"1950":99,"1951":100,"1952":101,"1953":102,"1954":103,"1955":104,"1956":105,"1957":106,"1958":107,"1959":108,"1960":109,"1961":110,"1962":111,"1963":105,"1964":108,"1965":112,"1966":97,"1967":111,"1968":102,"1969":112,"1970":109,"1971":104,"1972":109,"1973":113,"1974":105,"1975":107,"1976":113,"1977":113,"1978":114,"1979":113,"1980":115,"1981":111,"1982":116,"1983":114,"1984":115,"1985":99,"1986":104,"1987":102,"1988":110,"1989":117,"1990":118,"1991":116,"1992":119,"1993":120,"1994":121,"1995":122,"1996":123,"1997":124,"1998":125,"1999":126,"2000":119,"2001":119,"2002":127,"2003":125,"2004":128,"2005":129,"2006":130,"2007":128,"2008":131,"2009":94,"2010":132,"2011":133,"2012":134,"2013":135,"2014":136,"2015":137,"2016":138,"2017":139,"2018":140,"2019":141,"2020":142,"2021":143,"2022":144,"2023":145,"2024":146},5,11,8,23,16,18,27,25,14,22,24,9,20,10,19,17,21,31,26,32,30,43,38,33,37,35,49,40,41,47,42,53,50,67,72,102,124,168,165,169,205,202,228,254,259,269,264,311,271,94,20294,{"1948":149,"1949":149,"1951":114,"1952":108,"1953":107,"1954":150,"1955":105,"1956":101,"1957":113,"1958":97,"1959":99,"1960":151,"1961":101,"1962":152,"1964":153,"1965":111,"1967":125,"1968":100,"1969":127,"1970":119,"1971":104,"1972":107,"1973":125,"1974":154,"1975":102,"1976":155,"1977":156,"1978":157,"1979":158,"1980":151,"1986":120,"1987":151,"1988":159,"1989":119,"1990":160,"1991":98,"1992":161,"1993":162,"1994":163,"1995":164,"1996":165,"1997":166,"1998":167,"1999":94,"2000":168,"2001":169,"2002":170,"2003":171,"2004":172,"2005":173,"2006":174,"2007":175,"2008":176,"2009":177,"2010":178,"2011":179,"2012":180,"2013":181,"2014":182,"2015":183,"2016":184,"2017":185,"2018":186,"2019":187,"2020":188,"2021":189,"2022":190,"2023":191,"2024":108},1,34,6,105,2,77,65,7,39,28,4,418,195,163,54,247,456,112,224,545,249,376,971,329,239,837,601,783,1770,680,382,1207,1178,850,525,1069,672,833,1515,815,622,308,74,4.17,{"1948":194,"1949":195,"1951":196,"1952":197,"1953":198,"1954":199,"1955":197,"1956":200,"1957":201,"1958":202,"1959":203,"1960":86,"1961":204,"1962":205,"1964":206,"1965":207,"1967":208,"1968":209,"1969":210,"1970":211,"1971":149,"1972":212,"1973":213,"1974":214,"1975":89,"1976":215,"1977":87,"1978":199,"1979":198,"1980":216,"1986":217,"1987":87,"1988":218,"1989":219,"1990":220,"1991":221,"1992":222,"1993":223,"1994":224,"1995":225,"1996":226,"1997":227,"1998":228,"1999":229,"2000":230,"2001":231,"2002":232,"2003":233,"2004":234,"2005":235,"2006":236,"2007":237,"2008":238,"2009":239,"2010":240,"2011":241,"2012":242,"2013":243,"2014":244,"2015":245,"2016":246,"2017":247,"2018":248,"2019":249,"2020":250,"2021":251,"2022":252,"2023":253,"2024":254},0.2,0.09,1.35,0.56,1.33,1.26,1.14,0.95,0.21,0.89,1.6,5.53,0.22,1.12,2.16,1.28,2.47,1.9,1.2,1.95,5.5,3.1,0.23,1.32,0.4,1.27,9.72,0.34,5.13,4.94,1.46,7.06,9.31,2.8,5.46,2.3,14.34,6.55,8.95,23.68,6.21,4.78,12.49,11.34,10.88,16.39,6.67,3.08,7.18,7.14,5.03,2.56,5.29,2.95,3.28,5.85,3.03,2.36,0.99,0.27,0.1,{"meta":256,"data":258},{"total":257},"4873",[259,375,476,560,708,1111,1421,1685,1809,1945],{"id":260,"createTime":261,"updateTime":262,"relativeEntities":263,"slug":264,"properties":265,"entityType":275,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":276,"viewCount":21,"primaryUrl":278,"fullTextUrl":20,"authors":279,"publicationType":322,"publisherRelationship":323,"citationCount":20,"citationInfo":20,"publishDate":371,"publishYear":372,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":373,"openAccess":20,"references":20,"isForceReanalyzing":374},"0018b398-9aa5-418c-b5d4-c5dd7961a4eb","2024-01-18T23:22:16.752+00:00","2026-09-08T10:14:39.484+00:00",[],"Characterization-of-ultraviolet-radiation-UVA-in-the-desert-climate-of-the-Central-Arabian-Peninsula",{"abstract":266,"title":268,"references":271,"doi":273},{"EN":267},"Knowledge of ultraviolet radiation (UVA) at the Earth’s surface is of great importance in different technological and scientific applications. In this study, UVA (315–400 nm) and global solar radiation (G, 400–1100 nm) data from Riyadh (Central Saudi Arabia) for the period between 2015 and April 2020 are used to characterize the UVA at different cloudiness levels. The sky was classified into several categories according to the clearness index. For all sky conditions, the mean values of UVA, G, and the ratio UVA\u002FG were 11.58 ± 6.1 W\u002Fm2, 549.35 ± 264.55 W\u002Fm2, and 0.021 ± 0.003, respectively. While the mean UVA and G values under totally overcast skies were 5.51 ± 2.7 W\u002Fm2 and 267.90120.44 W\u002Fm2, respectively, the UVA was 21.63 ± 2.14 W\u002Fm2 and G was 933.19 ± 39.94 under clear skies. For partly cloudy skies, the amount of UVA and G increases as the sky gets clearer. The annual mean value of UVA decreased gradually from 2016 to 2018. In comparison with the mean value of UVA in 2016, the mean values of UVA were down about 7% and 18% in 2017 and 2018, respectively. This may be due to the heavy dust storms that occurred in those two years. The monthly and hourly variations in UVA and G are investigated and discussed. The distribution of the monthly values of UVA and G exhibits high symmetry. The UVA and G are at the maximum in summer and the minimum in winter. The amount of radiation appears similar in spring and summer and in autumn and winter. This may be explained by the seasonal symmetry of the summer and winter solstices. The hourly variations in the average UVA and G attain their minimum values in the early morning (06:00 local time) and reach their maximum values at around midday. Finally, several empirical models relating ultraviolet (UV), with solar global radiation (G), and the clearness index (Kt) under all sky conditions are established. The results reveal that the proposed empirical models accurately predict hourly values.",{"EN":269,"VI":270},"Characterization of ultraviolet radiation (UVA) in the desert climate of the Central Arabian Peninsula","Đặc trưng hóa bức xạ tử ngoại (UVA) trong khí hậu sa mạc tại miền trung bán đảo Ả Rập",{"VOID":272},"Alados I, Mellado J, Ramos F, Alados-Arboledas I (2004) Estimating UV erythemal irradiance by means of neural networks. J Photochem Photobiol 80:351–358\nAl-Aruri SD (1990) The empirical relationship between global radiation and global ultraviolet (0.290–0.385) mm solar radiation components. Sol Energy 45:61–64\nBilbao J, Mateos D, Miguel A (2011) Analysis and cloudiness influence on UV total irradiation. Int J Climatol 31:451–460\nBarbero FJ, López G, Batles FJ (2006) Determination of daily solar ultraviolet radiation using statistical models and artificial neural networks. Ann Geophys 24:2105–2114\nBilbao J et al (2015) Global, diffuse, beam and ultraviolet solar irradiance recorded in Malta and atmospheric component influences under cloudless skies. Sol Energy 121:131–138\nCañada J, Pedros G, Bosca J (2003) Relationships between UV (0.290-0.385 μm) and broad band solar radiation hourly values in Valencia and Córdoba. Spain Energy 28:199–217\nCañada J, Pedrós G, López A, Boscà J (2000) Influence of the clearness index for the whole spectrum and of the relative optical air mass on UV solar irradiance for two locations in the Mediterranean area, Valencia and Córdoba. J of Geophys Res 110:4759–4766\nCasale G, Meloni D, Miano S, Palmieri S, Siani A (2000) Solar UV-B irradiance and total ozone in Italy: fluctuations and trends. J Geophys Res 105:4895–4901\nDi Sarra A, Cacciani M, Chamard P et al (2018) Effects of desert dust on ozone on the ultraviolet irradiance at the Mediterranean island of Lampedusa during PAUR II. J Geophys Res 107(D18):2–14\nDiffey B (1991) Solar ultraviolet effects on biological systems. Phys Med Biol 36:299–328\nFeister U, Grasnick KH (1992) Solar UV radiation measurements at Postdam (528229N, 13859E). Sol Energy 49:541–548\nFioletov E et al (2009) On the relationship between erythemal and vitamin D action spectrum weighted ultraviolet radiation. J Photochem Photobiol B 95:9–16\nFoyo-Moreno I, Vida J, Alados-Arboledas L (1999) A simple all weather model to estimate ultraviolet solar radiation (290–385 nm). J Appl Meteorol 38:1020–1026\nFoyo-Moreno I, Alados I, Olmo F, Alados-Arboledas L (2003) The influence of cloudiness on UV global irradiance (295–385 nm). Agri and Forest Meteorol 120:101–111\nFoyo-Moreno I, Vida J, Alados-Arboledas I (1998) Ground-based ultraviolet (290–385 nm) and broadband solar radiation measurements in south-eastern Spain. Int J Climatol 18:1389–1400\nGueymard C (2004) The sun’s total and spectral irradiance for solar energy applications and solar radiation models. Sol Energy 76:423–453\nHe Y, Zheng Y, He D (2002) A summary of research on the effects of enhanced ultraviolet radiation on field ecosystems. Chinese J Agrometeorol 1:47–52\nIqbal M (1983) An introduction to solar radiation. Academic Press, New York\nJacovides C, Tymvios F, Assimakopoulos D et al (2009) Solar UVB (280–315 nm) and UVA (315–380 nm) radiant fluxes and their relationships with broadband global radiant flux at an eastern Mediterranean site. Agricultural and Forest Meteorol 149:1188–1200\nJacovides C, Tymvios F, Boland J, Tsitouri M (2015) Artificial neural network models for estimating daily solar global UV, PAR and broadband radiant fluxes in an eastern Mediterranean site. Atmos Res 152:138–145\nKaskaoutis D, Kambezidis H, Jacovides C, Steven M (2006) Modification of solar radiation components under different atmospheric conditions in the Greater Athens Area, Greece. J Atmos Sol-Terr Phys 68:1043–1052\nKrzyscin J, Puchalsky S (1998) Aerosol impact on the surface UV radiation from the groundbased measurements taken at Belsk. Poland J Geophys Res 103(D13):16175–16181\nKudish A, Lyubanksky V, Evseev E, Ianetz A (2005) Statistical analysis and intercomparison of the solar UVB, UVA and global radiation for Beer Sheva and Neve Zohar (Dead Sea), Israel. Ther Appl Climatol 80:1–15\nMacKie R (2006) Long-term health risk to the skin of ultraviolet radiation. Prog Biophys Mol Bio 92:92–96\nMaghrabi A (2012) Modification of the IR sky temperature under different atmospheric conditions in an arid region in central Saudi Arabia: experimental and theoretical justification. J Geophys Res 117:D19207\nMartinez-Lozano J, Tena F, Utrillas P (1996) Measurement and analysis of ultraviolet solar irradiation in Valencia. Spain in J Climatol 16:947–955\nMartínez-Lozano J, Tena F, Utrillas M (1999) Ratio of UV to global broad band irradiation in Valencia, Spain. Int J Climatol 19:903–911\nMateos D, Miguel A, Bilbao J (2010) Empirical models of UV total radiation and cloud effect study. J Climatol 30:1407–1415\nMurillo W, Cañada J, Pedrós G (2003) Correlation between global ultraviolet (290–385 nm) and global irradiation in Valencia and Córdoba (Spain). Renew Energy 28:409–418\nOgunjobi K, Kim Y (2004) Ultraviolet (0.280-0.400) and broadband solar hourly radiation at Kwangju, South Korea: analysis of their correlation with aerosol optical depth and clearness index. Atmos Res 71:193–214\nPashiardis S, Kalogirou SA, Pelengaris A (2017) Statistical analysis and inter-comparison of solar UV and global radiation for Athalassa and Larnaca. Cyprus SM J Biometrics Biostat 2(2):1012\nRobaa SM (2004) A study of ultraviolet solar radiation at Cairo urban area. Egypt Sol Energy 77:251–259\nRoyal Commission of Riyadh City (2020) Riyadh Environment. https:\u002F\u002Fwww.riyadhenv.gov.sa\u002F\nSkye Instrument (2014). http:\u002F\u002Fwww.skyeinstruments.info\u002Findex_htm_files\u002FUVA%20SENSOR%20v3.pdf\nHeuklon V (1979) Estimating atmospheric ozone for solar radiation models. Sol Energy 22:63\nZerefos CS, Bais AF (1997) Solar ultraviolet radiation, modeling, measurements and effects. Springer Verlag, New York",{"VOID":274},"10.1007\u002Fs00704-021-03766-y","PUBLICATION",[277],"VI","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs00704-021-03766-y",[280,296,309],{"id":281,"sortIndex":21,"researcher":20,"roles":282,"affiliations":284,"properties":293,"displayName":295,"givenName":20,"familyName":20},"951e43b0-b038-4f95-8aae-116965bc4730",[283],"AUTHOR",[285],{"id":286,"sortIndex":21,"affiliation":287,"properties":20},"78f18250-6e45-48de-8a82-acbfc16ef99c",{"id":286,"createTime":20,"updateTime":20,"relativeEntities":288,"slug":20,"properties":289,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":292,"statistic":20},[],{"title":290},{"VI":291},"National Centre for Applied Physics, King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia",[],{"title":294},{"VI":295},"Abdullrahman Maghrabi",{"id":297,"sortIndex":149,"researcher":20,"roles":298,"affiliations":299,"properties":306,"displayName":308,"givenName":20,"familyName":20},"f18e850e-80de-49c7-ba98-359e03270324",[283],[300],{"id":286,"sortIndex":21,"affiliation":301,"properties":20},{"id":286,"createTime":20,"updateTime":20,"relativeEntities":302,"slug":20,"properties":303,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":305,"statistic":20},[],{"title":304},{"VI":291},[],{"title":307},{"VI":308},"Abdulah Aldosari",{"id":310,"sortIndex":153,"researcher":20,"roles":311,"affiliations":312,"properties":319,"displayName":321,"givenName":20,"familyName":20},"fef93a00-baaa-444c-9f64-0f56b7c50a5b",[283],[313],{"id":286,"sortIndex":21,"affiliation":314,"properties":20},{"id":286,"createTime":20,"updateTime":20,"relativeEntities":315,"slug":20,"properties":316,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":318,"statistic":20},[],{"title":317},{"VI":291},[],{"title":320},{"VI":321},"Mohammed Altilasi","ARTICLE",{"url":278,"publisher":324,"properties":366},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":325,"slug":10,"properties":326,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":330,"manageAffiliations":335,"indexDatabases":346,"url":20,"thumbnailPath":20,"statistic":361,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":327,"title":328,"eissn":329},{"VOID":13},{"EN":15},{"VOID":17},[331],{"id":24,"createTime":20,"updateTime":20,"relativeEntities":332,"label":333,"description":334,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":27},{},[336,341],{"id":31,"createTime":20,"updateTime":20,"relativeEntities":337,"slug":20,"properties":338,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":340,"statistic":20},[],{"title":339},{"EN":35},[37],{"id":39,"createTime":20,"updateTime":20,"relativeEntities":342,"slug":20,"properties":343,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":345,"statistic":20},[],{"title":344},{"EN":43},[37],[347,354],{"id":47,"indexDatabase":348,"url":58,"indexYears":59,"academicFieldIds":353,"indexDatabaseRanking":62},{"id":49,"createTime":20,"updateTime":20,"relativeEntities":349,"label":350,"description":351,"key":55,"publicationTags":352,"standard":20},[],{"EN":52,"VI":52},{"EN":52,"VI":54},[57],[61],{"id":64,"indexDatabase":355,"url":77,"indexYears":20,"academicFieldIds":360,"indexDatabaseRanking":20},{"id":66,"createTime":20,"updateTime":20,"relativeEntities":356,"label":357,"description":358,"key":73,"publicationTags":359,"standard":20},[],{"EN":69,"VI":69},{"EN":71,"VI":72},[75,76],[79],{"impactFactor":21,"impactFactorByYear":362,"i10Index":93,"i10IndexLast5Year":94,"totalPublication":95,"totalPublicationByYear":363,"totalCitation":147,"totalCitationByYear":364,"totalCitationPerPublication":192,"totalCitationPerPublicationByYear":365,"hindexLast5Year":130,"hindex":130},{"2012":82,"2013":83,"2014":84,"2015":85,"2016":86,"2017":87,"2018":84,"2019":88,"2020":89,"2021":90,"2022":91,"2023":92},{"1948":97,"1949":98,"1950":99,"1951":100,"1952":101,"1953":102,"1954":103,"1955":104,"1956":105,"1957":106,"1958":107,"1959":108,"1960":109,"1961":110,"1962":111,"1963":105,"1964":108,"1965":112,"1966":97,"1967":111,"1968":102,"1969":112,"1970":109,"1971":104,"1972":109,"1973":113,"1974":105,"1975":107,"1976":113,"1977":113,"1978":114,"1979":113,"1980":115,"1981":111,"1982":116,"1983":114,"1984":115,"1985":99,"1986":104,"1987":102,"1988":110,"1989":117,"1990":118,"1991":116,"1992":119,"1993":120,"1994":121,"1995":122,"1996":123,"1997":124,"1998":125,"1999":126,"2000":119,"2001":119,"2002":127,"2003":125,"2004":128,"2005":129,"2006":130,"2007":128,"2008":131,"2009":94,"2010":132,"2011":133,"2012":134,"2013":135,"2014":136,"2015":137,"2016":138,"2017":139,"2018":140,"2019":141,"2020":142,"2021":143,"2022":144,"2023":145,"2024":146},{"1948":149,"1949":149,"1951":114,"1952":108,"1953":107,"1954":150,"1955":105,"1956":101,"1957":113,"1958":97,"1959":99,"1960":151,"1961":101,"1962":152,"1964":153,"1965":111,"1967":125,"1968":100,"1969":127,"1970":119,"1971":104,"1972":107,"1973":125,"1974":154,"1975":102,"1976":155,"1977":156,"1978":157,"1979":158,"1980":151,"1986":120,"1987":151,"1988":159,"1989":119,"1990":160,"1991":98,"1992":161,"1993":162,"1994":163,"1995":164,"1996":165,"1997":166,"1998":167,"1999":94,"2000":168,"2001":169,"2002":170,"2003":171,"2004":172,"2005":173,"2006":174,"2007":175,"2008":176,"2009":177,"2010":178,"2011":179,"2012":180,"2013":181,"2014":182,"2015":183,"2016":184,"2017":185,"2018":186,"2019":187,"2020":188,"2021":189,"2022":190,"2023":191,"2024":108},{"1948":194,"1949":195,"1951":196,"1952":197,"1953":198,"1954":199,"1955":197,"1956":200,"1957":201,"1958":202,"1959":203,"1960":86,"1961":204,"1962":205,"1964":206,"1965":207,"1967":208,"1968":209,"1969":210,"1970":211,"1971":149,"1972":212,"1973":213,"1974":214,"1975":89,"1976":215,"1977":87,"1978":199,"1979":198,"1980":216,"1986":217,"1987":87,"1988":218,"1989":219,"1990":220,"1991":221,"1992":222,"1993":223,"1994":224,"1995":225,"1996":226,"1997":227,"1998":228,"1999":229,"2000":230,"2001":231,"2002":232,"2003":233,"2004":234,"2005":235,"2006":236,"2007":237,"2008":238,"2009":239,"2010":240,"2011":241,"2012":242,"2013":243,"2014":244,"2015":245,"2016":246,"2017":247,"2018":248,"2019":249,"2020":250,"2021":251,"2022":252,"2023":253,"2024":254},{"pages":367,"volume":369},{"VOID":368},"631-644",{"VOID":370},"146","2021-08-26",2021,[62,75],false,{"id":376,"createTime":377,"updateTime":378,"relativeEntities":379,"slug":380,"properties":381,"entityType":275,"verifyStatus":389,"verifyTime":390,"verifyNote":391,"languages":20,"translateLanguages":392,"viewCount":21,"primaryUrl":393,"fullTextUrl":20,"authors":394,"publicationType":322,"publisherRelationship":425,"citationCount":20,"citationInfo":20,"publishDate":473,"publishYear":474,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":475,"openAccess":20,"references":20,"isForceReanalyzing":374},"200c6905-1654-4e3d-9efe-539374182e7b","2024-02-09T07:56:06.464+00:00","2026-09-07T12:17:51.042+00:00",[],"Fractal-Characterisation-of-Geophysical-Measuring-Networks-and-its-Implication-for-an-Optimal-Location-of-Additional-Stations-An-Application-to-a-Rain-Gauge-Network",{"title":382,"doi":385,"abstract":387},{"EN":383,"VI":384},"Fractal Characterisation of Geophysical Measuring Networks and its Implication for an Optimal Location of Additional Stations: An Application to a Rain-Gauge Network","Xác định đặc trưng fractal của mạng lưới đo địa vật lý và ý nghĩa cho vị trí tối ưu của các trạm bổ sung: Ứng dụng cho mạng lưới đo mưa",{"VOID":386},"10.1007\u002Fs007040070040",{"EN":388}," The locations of measuring stations are often inhomogeneously distributed in space, possibly because of both geophysical interests and access problems. The areal inhomogeneity of a network can be well characterised by its fractal dimension, that is an index ranging progressively from 0 (when all stations are distributed on a single point or on isolated points) to 2 (when all stations are uniformly distributed). Appreciating the scaling region, inside which the station-co-ordinates are fractally distributed, provides valuable information both on the minimum detectable scale and on the minimum resolvable dimension. The increase in the measuring capability of a network must occur through its strategic enlargement resulting in a compromise between the fractal dimension increase and local topographic necessities. An application to a rain-gauge network belonging to the Naples Section of the Italian Hydrographic Service is reported.","VERIFIED","2025-01-20T18:03:49.316+00:00","Auto Verify",[277],"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs007040070040",[395,410],{"id":396,"sortIndex":21,"researcher":20,"roles":397,"affiliations":398,"properties":407,"displayName":409,"givenName":20,"familyName":20},"9c35a8f7-c639-4de5-b99b-345e808cf3c0",[283],[399],{"id":400,"sortIndex":21,"affiliation":401,"properties":20},"8c6e2ea5-d47a-443a-baf1-ac5cce03269f",{"id":400,"createTime":20,"updateTime":20,"relativeEntities":402,"slug":20,"properties":403,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":406,"statistic":20},[],{"title":404},{"VI":405}," Department of Geophysics and Volcanology, University of Naples Federico II, Naples, Italy, , IT",[],{"title":408},{"VI":409},"A. Mazzarella",{"id":411,"sortIndex":149,"researcher":20,"roles":412,"affiliations":413,"properties":422,"displayName":424,"givenName":20,"familyName":20},"690ecb70-83e2-47cc-973e-787af98be7a5",[283],[414],{"id":415,"sortIndex":21,"affiliation":416,"properties":20},"d6b395c9-1962-47f9-9997-21b9dfdf60cd",{"id":415,"createTime":20,"updateTime":20,"relativeEntities":417,"slug":20,"properties":418,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":421,"statistic":20},[],{"title":419},{"VI":420}," National Hydrographic Service, Naples Section Italy, Naples, Italy, , IT",[],{"title":423},{"VI":424},"G. Tranfaglia",{"url":393,"publisher":426,"properties":468},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":427,"slug":10,"properties":428,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":432,"manageAffiliations":437,"indexDatabases":448,"url":20,"thumbnailPath":20,"statistic":463,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":429,"title":430,"eissn":431},{"VOID":13},{"EN":15},{"VOID":17},[433],{"id":24,"createTime":20,"updateTime":20,"relativeEntities":434,"label":435,"description":436,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":27},{},[438,443],{"id":31,"createTime":20,"updateTime":20,"relativeEntities":439,"slug":20,"properties":440,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":442,"statistic":20},[],{"title":441},{"EN":35},[37],{"id":39,"createTime":20,"updateTime":20,"relativeEntities":444,"slug":20,"properties":445,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":447,"statistic":20},[],{"title":446},{"EN":43},[37],[449,456],{"id":47,"indexDatabase":450,"url":58,"indexYears":59,"academicFieldIds":455,"indexDatabaseRanking":62},{"id":49,"createTime":20,"updateTime":20,"relativeEntities":451,"label":452,"description":453,"key":55,"publicationTags":454,"standard":20},[],{"EN":52,"VI":52},{"EN":52,"VI":54},[57],[61],{"id":64,"indexDatabase":457,"url":77,"indexYears":20,"academicFieldIds":462,"indexDatabaseRanking":20},{"id":66,"createTime":20,"updateTime":20,"relativeEntities":458,"label":459,"description":460,"key":73,"publicationTags":461,"standard":20},[],{"EN":69,"VI":69},{"EN":71,"VI":72},[75,76],[79],{"impactFactor":21,"impactFactorByYear":464,"i10Index":93,"i10IndexLast5Year":94,"totalPublication":95,"totalPublicationByYear":465,"totalCitation":147,"totalCitationByYear":466,"totalCitationPerPublication":192,"totalCitationPerPublicationByYear":467,"hindexLast5Year":130,"hindex":130},{"2012":82,"2013":83,"2014":84,"2015":85,"2016":86,"2017":87,"2018":84,"2019":88,"2020":89,"2021":90,"2022":91,"2023":92},{"1948":97,"1949":98,"1950":99,"1951":100,"1952":101,"1953":102,"1954":103,"1955":104,"1956":105,"1957":106,"1958":107,"1959":108,"1960":109,"1961":110,"1962":111,"1963":105,"1964":108,"1965":112,"1966":97,"1967":111,"1968":102,"1969":112,"1970":109,"1971":104,"1972":109,"1973":113,"1974":105,"1975":107,"1976":113,"1977":113,"1978":114,"1979":113,"1980":115,"1981":111,"1982":116,"1983":114,"1984":115,"1985":99,"1986":104,"1987":102,"1988":110,"1989":117,"1990":118,"1991":116,"1992":119,"1993":120,"1994":121,"1995":122,"1996":123,"1997":124,"1998":125,"1999":126,"2000":119,"2001":119,"2002":127,"2003":125,"2004":128,"2005":129,"2006":130,"2007":128,"2008":131,"2009":94,"2010":132,"2011":133,"2012":134,"2013":135,"2014":136,"2015":137,"2016":138,"2017":139,"2018":140,"2019":141,"2020":142,"2021":143,"2022":144,"2023":145,"2024":146},{"1948":149,"1949":149,"1951":114,"1952":108,"1953":107,"1954":150,"1955":105,"1956":101,"1957":113,"1958":97,"1959":99,"1960":151,"1961":101,"1962":152,"1964":153,"1965":111,"1967":125,"1968":100,"1969":127,"1970":119,"1971":104,"1972":107,"1973":125,"1974":154,"1975":102,"1976":155,"1977":156,"1978":157,"1979":158,"1980":151,"1986":120,"1987":151,"1988":159,"1989":119,"1990":160,"1991":98,"1992":161,"1993":162,"1994":163,"1995":164,"1996":165,"1997":166,"1998":167,"1999":94,"2000":168,"2001":169,"2002":170,"2003":171,"2004":172,"2005":173,"2006":174,"2007":175,"2008":176,"2009":177,"2010":178,"2011":179,"2012":180,"2013":181,"2014":182,"2015":183,"2016":184,"2017":185,"2018":186,"2019":187,"2020":188,"2021":189,"2022":190,"2023":191,"2024":108},{"1948":194,"1949":195,"1951":196,"1952":197,"1953":198,"1954":199,"1955":197,"1956":200,"1957":201,"1958":202,"1959":203,"1960":86,"1961":204,"1962":205,"1964":206,"1965":207,"1967":208,"1968":209,"1969":210,"1970":211,"1971":149,"1972":212,"1973":213,"1974":214,"1975":89,"1976":215,"1977":87,"1978":199,"1979":198,"1980":216,"1986":217,"1987":87,"1988":218,"1989":219,"1990":220,"1991":221,"1992":222,"1993":223,"1994":224,"1995":225,"1996":226,"1997":227,"1998":228,"1999":229,"2000":230,"2001":231,"2002":232,"2003":233,"2004":234,"2005":235,"2006":236,"2007":237,"2008":238,"2009":239,"2010":240,"2011":241,"2012":242,"2013":243,"2014":244,"2015":245,"2016":246,"2017":247,"2018":248,"2019":249,"2020":250,"2021":251,"2022":252,"2023":253,"2024":254},{"pages":469,"volume":471},{"VOID":470},"157-163",{"VOID":472},"65","2000-04-01",2000,[62,75],{"id":477,"createTime":478,"updateTime":479,"relativeEntities":480,"slug":481,"properties":482,"entityType":275,"verifyStatus":389,"verifyTime":492,"verifyNote":391,"languages":20,"translateLanguages":493,"viewCount":21,"primaryUrl":494,"fullTextUrl":20,"authors":495,"publicationType":322,"publisherRelationship":511,"citationCount":20,"citationInfo":20,"publishDate":557,"publishYear":558,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":559,"openAccess":20,"references":20,"isForceReanalyzing":374},"fc920223-4ca2-4284-ac5b-dcf4e22844fe","2024-02-07T01:30:14.390+00:00","2026-09-07T12:17:23.122+00:00",[],"Unit-indicators-of-the-greenhouse-effect-for-CO2-and-steam-from-H2O-and-anthropogenic-impact-on-the-climate",{"abstract":483,"title":485,"references":488,"doi":490},{"EN":484},"The greenhouse effect from anthropogenic CO2 emissions into the atmosphere is currently determined at the level of expert assessments, and the unit of measurement of the effect of gases on the greenhouse effect is the one. The article is devoted to the establishment by mathematical methods of physical units of the greenhouse effect for CO2 and steam from H2O and their influence on the climate. From the formula of the radiation balance of the Earth’s surface, it is established that the radiation equilibrium of the surface and the atmosphere occurs in the evening. Data from Mars Pathfinder on this equilibrium were used to determine the unit greenhouse index for CO2, which was 0.0138 ± 0.001 K m2 kg−1. A similar indicator was found for H2O vapor equal to 0.0834 ± 0.005 K m2 kg−1 from the difference in temperature and humidity of desert and coastal areas of the same latitudinal zone. The value of the integral temperature index was determined by the method of mathematical statistics equal to 0.263 ± 0.021 K m2 kg−1 pair of H2O by the dependence of humidity from temperature. The greenhouse effect of CO2 and steam from H2O is insignificant due to the low average content. However, a slight temperature from anthropogenic CO2 concentration contributes to the formation of a small portion of steam. An increase in temperature from this steam gives a new portion of steam, and therefore, until noon, the additional steam content and heating of the atmosphere increase exponentially. The anthropogenic increase in CO2 caused a rising in the H2O vapor content in the atmosphere and from him the near-surface temperature by 1.43 ± 0.11, and for human habitation areas—by 1.55 ± 0.12 K. The results of this work can be used to predict climate change and take measures to neutralize it.",{"EN":486,"VI":487},"Unit indicators of the greenhouse effect for CO2 and steam from H2O and anthropogenic impact on the climate","Các chỉ số đơn vị của hiệu ứng nhà kính của CO2 và hơi nước từ H2O cùng tác động của con người lên khí hậu",{"VOID":489},"Climate Change (2013) Physical scientific basis. Summary for politicians. Fifth report of the Intergovernmental Panel on Climate Change. IPCC, p 1522\nDemidov NE, Bazilevsky AT, Kuzmin RO (2015) The soil of Mars: varieties, structure, composition, physical properties, drill ability, hazards for landers. Astroph Herald 4:243–261\nDoustimotlagh N, Mirzaee S (2016) Increasing CO2 in atmosphere cannot increase the Earth’s temperature. Conference: World Conference on Climate change. At: Valencia, Spain, p 12\nIPCC report AR6 (2021) Climate Change: The on Climate change. The Physical Science Basis, p 221\nKhromov SP, Petrosyants MA (2006) Meteorology and climatology. Nauka, Russia, p 527\nMangold N, Baratoux D, Witasse O, Encrenaz T, Sotin C (2016) Mars: a small terrestrial planet. Astron Astrophys Rev 107. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00159-016-0099-5\nMartynov DY (1988) Course of general astrophysics. Nauka, Russia, p 640\nNeumann GA, Smith DE, Zuber MT (2003) Two Mars years of clouds detected by the Mars Orbiter Laser Altimeter. J Geophys Res 4:1–17. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2002JE001849\nSchofield JT, Barnes JR, Crisp D, Haberte RM, Larsen S, Magalhaes JA, Murphy JR, Seiff A, Wilson G (1997) The Mars pathfinder atmospheric structure investigation Meteorology (ASI\u002FMET) Experiment. Science 5:1752–1758\nSivkov S (1968) Methods calculating the characteristics of solar radiation. Russia. Gidrom, p 234\nVorobyev VN, Sarukhanyan EI, Smirnov NP (2005) Global warming. Hypothesis or reality? Sci Notes RSSU Russia 1:6–21\nWang Z, Barlage M, Zeng X, Dickinson RE, Schaaf CB (2005) The solar zenith angle dependence of desert albedo. Geoph Res Lett 32:5403. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2004GL021835\nWillett KM, Jones PD, Gillett NP, Thorne PW (2008) Recent changes in surface humidity: development of the Had CRUH Dataset. J Clim 21:534–538\nZhmakin VM (2012) Estimation of the greenhouse effect from H2O and CO2 in the atmosphere. Bull State Munic Adm Russia 1:82–89\nZhmakin VM (2021) Synthesis and preservation of organic molecules with homochiral excess by adsorption on carbon in carbonaceous chondrites. Chem Scien Int J 10:46–53. https:\u002F\u002Fdoi.org\u002F10.9734\u002FCSJI\u002F2021\u002Fv30i1030259",{"VOID":491},"10.1007\u002Fs00704-023-04738-0","2025-02-12T08:08:05.311+00:00",[277],"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs00704-023-04738-0",[496],{"id":497,"sortIndex":21,"researcher":20,"roles":498,"affiliations":499,"properties":508,"displayName":510,"givenName":20,"familyName":20},"656098fd-1aa5-4aef-aaae-c3f13a7cc851",[283],[500],{"id":501,"sortIndex":21,"affiliation":502,"properties":20},"b4e77ed4-2f81-4485-81f6-096c3ce3d944",{"id":501,"createTime":20,"updateTime":20,"relativeEntities":503,"slug":20,"properties":504,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":507,"statistic":20},[],{"title":505},{"VI":506},"Ministry of Ecology and Nature Management of the Moscow Region, Kursk, Russia",[],{"title":509},{"VI":510},"V. M. Zhmakin",{"url":494,"publisher":512,"properties":554},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":513,"slug":10,"properties":514,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":518,"manageAffiliations":523,"indexDatabases":534,"url":20,"thumbnailPath":20,"statistic":549,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":515,"title":516,"eissn":517},{"VOID":13},{"EN":15},{"VOID":17},[519],{"id":24,"createTime":20,"updateTime":20,"relativeEntities":520,"label":521,"description":522,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":27},{},[524,529],{"id":31,"createTime":20,"updateTime":20,"relativeEntities":525,"slug":20,"properties":526,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":528,"statistic":20},[],{"title":527},{"EN":35},[37],{"id":39,"createTime":20,"updateTime":20,"relativeEntities":530,"slug":20,"properties":531,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":533,"statistic":20},[],{"title":532},{"EN":43},[37],[535,542],{"id":47,"indexDatabase":536,"url":58,"indexYears":59,"academicFieldIds":541,"indexDatabaseRanking":62},{"id":49,"createTime":20,"updateTime":20,"relativeEntities":537,"label":538,"description":539,"key":55,"publicationTags":540,"standard":20},[],{"EN":52,"VI":52},{"EN":52,"VI":54},[57],[61],{"id":64,"indexDatabase":543,"url":77,"indexYears":20,"academicFieldIds":548,"indexDatabaseRanking":20},{"id":66,"createTime":20,"updateTime":20,"relativeEntities":544,"label":545,"description":546,"key":73,"publicationTags":547,"standard":20},[],{"EN":69,"VI":69},{"EN":71,"VI":72},[75,76],[79],{"impactFactor":21,"impactFactorByYear":550,"i10Index":93,"i10IndexLast5Year":94,"totalPublication":95,"totalPublicationByYear":551,"totalCitation":147,"totalCitationByYear":552,"totalCitationPerPublication":192,"totalCitationPerPublicationByYear":553,"hindexLast5Year":130,"hindex":130},{"2012":82,"2013":83,"2014":84,"2015":85,"2016":86,"2017":87,"2018":84,"2019":88,"2020":89,"2021":90,"2022":91,"2023":92},{"1948":97,"1949":98,"1950":99,"1951":100,"1952":101,"1953":102,"1954":103,"1955":104,"1956":105,"1957":106,"1958":107,"1959":108,"1960":109,"1961":110,"1962":111,"1963":105,"1964":108,"1965":112,"1966":97,"1967":111,"1968":102,"1969":112,"1970":109,"1971":104,"1972":109,"1973":113,"1974":105,"1975":107,"1976":113,"1977":113,"1978":114,"1979":113,"1980":115,"1981":111,"1982":116,"1983":114,"1984":115,"1985":99,"1986":104,"1987":102,"1988":110,"1989":117,"1990":118,"1991":116,"1992":119,"1993":120,"1994":121,"1995":122,"1996":123,"1997":124,"1998":125,"1999":126,"2000":119,"2001":119,"2002":127,"2003":125,"2004":128,"2005":129,"2006":130,"2007":128,"2008":131,"2009":94,"2010":132,"2011":133,"2012":134,"2013":135,"2014":136,"2015":137,"2016":138,"2017":139,"2018":140,"2019":141,"2020":142,"2021":143,"2022":144,"2023":145,"2024":146},{"1948":149,"1949":149,"1951":114,"1952":108,"1953":107,"1954":150,"1955":105,"1956":101,"1957":113,"1958":97,"1959":99,"1960":151,"1961":101,"1962":152,"1964":153,"1965":111,"1967":125,"1968":100,"1969":127,"1970":119,"1971":104,"1972":107,"1973":125,"1974":154,"1975":102,"1976":155,"1977":156,"1978":157,"1979":158,"1980":151,"1986":120,"1987":151,"1988":159,"1989":119,"1990":160,"1991":98,"1992":161,"1993":162,"1994":163,"1995":164,"1996":165,"1997":166,"1998":167,"1999":94,"2000":168,"2001":169,"2002":170,"2003":171,"2004":172,"2005":173,"2006":174,"2007":175,"2008":176,"2009":177,"2010":178,"2011":179,"2012":180,"2013":181,"2014":182,"2015":183,"2016":184,"2017":185,"2018":186,"2019":187,"2020":188,"2021":189,"2022":190,"2023":191,"2024":108},{"1948":194,"1949":195,"1951":196,"1952":197,"1953":198,"1954":199,"1955":197,"1956":200,"1957":201,"1958":202,"1959":203,"1960":86,"1961":204,"1962":205,"1964":206,"1965":207,"1967":208,"1968":209,"1969":210,"1970":211,"1971":149,"1972":212,"1973":213,"1974":214,"1975":89,"1976":215,"1977":87,"1978":199,"1979":198,"1980":216,"1986":217,"1987":87,"1988":218,"1989":219,"1990":220,"1991":221,"1992":222,"1993":223,"1994":224,"1995":225,"1996":226,"1997":227,"1998":228,"1999":229,"2000":230,"2001":231,"2002":232,"2003":233,"2004":234,"2005":235,"2006":236,"2007":237,"2008":238,"2009":239,"2010":240,"2011":241,"2012":242,"2013":243,"2014":244,"2015":245,"2016":246,"2017":247,"2018":248,"2019":249,"2020":250,"2021":251,"2022":252,"2023":253,"2024":254},{"pages":555},{"VOID":556},"1-7","2023-11-30",2023,[62,75],{"id":561,"createTime":562,"updateTime":563,"relativeEntities":564,"slug":565,"properties":566,"entityType":275,"verifyStatus":389,"verifyTime":576,"verifyNote":391,"languages":20,"translateLanguages":577,"viewCount":21,"primaryUrl":578,"fullTextUrl":20,"authors":579,"publicationType":322,"publisherRelationship":657,"citationCount":20,"citationInfo":20,"publishDate":705,"publishYear":706,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":707,"openAccess":20,"references":20,"isForceReanalyzing":374},"d6a0229c-d672-4094-a50d-e1721e6e278e","2024-01-01T16:03:58.544+00:00","2026-09-07T09:14:35.770+00:00",[],"Statistical-bias-correction-of-regional-climate-model-simulations-for-climate-change-projection-in-the-Jemma-sub-basin-upper-Blue-Nile-Basin-of-Ethiopia",{"abstract":567,"title":569,"references":572,"doi":574},{"EN":568},"This study evaluates bias correction methods and develops future climate scenarios using the output of a better bias correction technique at the Jemma sub-basin. The performance of different bias correction techniques was evaluated using several statistical metrics. The bias correction methods performance under climate condition different from the current climate was also evaluated using the differential split sample testing (DSST) and reveals that the distribution mapping technique is valid under climate condition different from the current climate. All bias correction methods were effective in adjusting mean monthly and annual RCM simulations of rainfall and temperature to the observed rainfall and temperature values. However, distribution mapping method was better in capturing the 90th percentile of observed rainfall and temperature and wet day probability of observed rainfall than other methods. As a result, we use the future (2021–2100) simulation of RCMs which are bias corrected using distribution mapping technique. The output of bias-adjusted RCMs unfolds a decline of rainfall, a persistent increase of temperature and an increase of extremes of rainfall and temperature in the future climate under emission scenarios of Representative Concentration Pathways 4.5, 8.5 and 2.6 (RCP4.5, RCP8.5 and RCP2.6). Thus, climate adaptation strategies that can provide optimal benefits under different climate scenarios should be developed to reduce the impact of future climate change.",{"EN":570,"VI":571},"Statistical bias correction of regional climate model simulations for climate change projection in the Jemma sub-basin, upper Blue Nile Basin of Ethiopia","Hiệu chỉnh độ chệch thống kê của các mô phỏng mô hình khí hậu khu vực cho dự phóng biến đổi khí hậu ở tiểu lưu vực Jemma, thượng lưu lưu vực sông Nile Xanh của Ethiopia",{"VOID":573},"Abdo KS, Fiseha BM, Rientjes THM, Gieske ASM, Haile AT (2009) Assessment of climate change impacts on the hydrology of Gilgel Abay catchment in Lake Tana Basin. Ethiopia Hydrol Process 23:3661–3669\nAdem AA, Tilahun SA, Ayana EK, Worqlul A.W, Assefa TT, Dessu SB, Melesse AM, (2016). Climate Change Impact on Stream Flow in the Upper Gilgel Abay Catchment, Blue Nile basin, Ethiopia. Landscape Dynamics, Soils and Hydrological Processes in Varied Climates 645–673. https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-319-18787-7\nAddor N, R€ossler O, K€oplin N, Huss M, Weingartner R, Seibert J (2014) Robust changes and sources of uncertainty in the projected hydrological regimes of Swiss catchments. Water Resour. Res., 50, 7541–7562. https:\u002F\u002Fdoi.org\u002F10.1002\u002F2013WR014132\nAzmat M, Uzair M, Huggel C, Hussain E (2018) Future climate and cryosphere impacts on the hydrology of a scarcely gauged catchment on the Jhelum river basin, Northern Pakistan. Sci Total Environ. 639, 961–976. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.scitotenv.2018.05.206\nBaldauf M, Seifert A, FöRstner J, Majewski D, Matthias R (2011) Operational convective-scale numerical weather prediction with the COSMO model : description and sensitivities. Am Meteorol Soc:3887–3905. https:\u002F\u002Fdoi.org\u002F10.1175\u002FMWR-D-10-05013.1\nBerhanu B, Seleshi Y, Demisse SS, Melesse AM (2016) Bias correction and characterization of climate forecast system re-analysis daily precipitation in Ethiopia using fuzzy overlay 243, 230–243. Berhanu B, Seleshi Y, Demisse SS, Melesse AM (2016) Bias correction and characterization of climate forecast system re-analysis daily precipitation in Ethiopia using fuzzy overlay. Meteorol. Appl. 23:230–243. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fmet.1549\nBeyene T, Lettenmaier DP, Kabat P (2010) Hydrologic impacts of climate change on the Nile River basin : implications of the 2007 IPCC scenarios 2007–2008. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10584-009-9693-0\nChen J, Brissette P, Poulin A, Leconte R (2011) Overall uncertainty study of the hydrological impacts of climate change for a Canadian watershed 47:1–16. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2011WR010602\nChen J, Brissette FP, Chaumont D, Braun M (2013) Finding appropriate bias correction methods in downscaling precipitation for hydrologic impact studies over North America. Water Resour Res 49:4187–4205. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fwrcr.20331\nChristensen JH, Carter TR (2007) Evaluating the performance and utility of regional climate models : the PRUDENCE project. Climatic Change 81:1–6. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10584-006-9211-6\nConway D, Schipper ELF (2011) Adaptation to climate change in Africa : challenges and opportunities identified from Ethiopia. Glob Environ Chang 21:227–237. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.gloenvcha.2010.07.013\nCramér H (1999) Mathematical methods of statistics, ninth. edn. Princeton University Press\nDile YT, Berndtsson R, Setegn SG (2013) Hydrological response to climate change for Gilgel Abay River, in the Lake Tana Basin - upper Blue Nile Basin of Ethiopia. PLoS One 8:12–17. https:\u002F\u002Fdoi.org\u002F10.1371\u002Fjournal.pone.0079296\nDoms G, Förstner J, Heise E, Herzog H-J, Mironov D, Raschendorfer M, Reinhardt T, Ritter B, Schrodin R, Schulz J-P, Vogel G (2011) COSMO II: Physical Parameterizations\nDosio A, Jürgen H, Schubert M, Daniel F (2015) Dynamical downscaling of CMIP5 global circulation models over CORDEX - Africa with COSMO - CLM : evaluation over the present climate and analysis of the added value. Clim Dyn 44:2637–2661. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00382-014-2262-x\nEdwards PN (2011) History of climate modeling. WIREs Clim Change 2:128–139. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fwcc.95\nElshamy ME, Seierstad IA, Sorteberg A (2009) Impacts of climate change on Blue Nile flows using bias-corrected GCM scenarios. Hydrol Earth Syst Sci 13:551–565. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fhess-13-551-2009\nFang GH, Yang J, Chen YN, Zammit C (2015) Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China. Hydrol Earth Syst Sci 19:2547–2559. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fhess-19-2547-2015\nFeyissa G, Gete Z, Woldeamlak B, Gebremariam E (2018) Downscaling of Future Temperature and Precipitation Extremes in Addis Ababa under Climate Change. Climate 6(3):58. https:\u002F\u002Fdoi.org\u002F10.3390\u002Fcli6030058\nFlato G, Marotzke J, Abiodun B, Braconnot P, Chou SC, Collins W, Cox P, Driouech F, Emori S, Eyring V, Forest C, Gleckler P, Guilyardi E, Jakob C, Kattsov V, And CR, Rummukainen M (2013) Evaluation of Climate Models. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge\nFouquart Y, Bonnel B (1980) Computations of solar heating of the earth’s atmosphere: A new parameterization.Beitr. Phys Atmos 53:35–62\nFowler HJ, Blenkinsop S, Tebaldi C (2007) Linking climate change modelling to impacts studies : recent advances in downscaling techniques for hydrological. Int J Climatol. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fjoc.1556\nGarland RM, Matooane M, Engelbrecht FA (2015) Regional Projections of Extreme Apparent Temperature Days in Africa and the Related Potential Risk to Human Health. Int. J. Environ. Res. Public Health 12:12577–12604. https:\u002F\u002Fdoi.org\u002F10.3390\u002Fijerph121012577\nGebrehiwot SG, Ilstedt U (2011a) Hydrological characterization of watersheds in the Blue Nile Basin, 15:11–20. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fhess-15-11-2011\nGiorgi F, Jones C, Asrar GR (2009) Addressing climate information needs at the regional level : the CORDEX framework. WMO Bulletin 58:175–183\nGudmundsson L, Bremnes JB, Haugen JE, Engen-Skaugen T (2012) Technical note: downscaling RCM precipitation to the station scale using statistical transformations – a comparison of methods. Hydrol Earth Syst Sci 16:3383–3390. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fhess-16-3383-2012\nGutowski WJ, Giorgi F, Timbal B, Frigon A, Jacob D, Kang H, Raghavan K, Lee B, Lennard C, Nikulin G, Rourke EO, Rixen M (2016) WCRP COordinated Regional Downscaling EXperiment ( CORDEX ): a diagnostic MIP for CMIP6. Geosci Model Dev:4087–4095. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fgmd-9-4087-2016\nHaile AT, Rientjes T (2015) Evaluation of regional climate model simulations of rainfall over the upper Blue Nile basin. Atmos Res 161–162:57–64. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.atmosres.2015.03.013\nHurni H, Tato K, Zeleke G (2005) The Implications of Changes in Population , Land Use , and Land Management for Surface Runoff in the Upper Nile Basin Area of Ethiopia Basin of Ethiopia. Mountain Research and Development 25(2):147–154. https:\u002F\u002Fdoi.org\u002F10.2307\u002F3674675\nIPCC (2013) Climate Change 2013: The Physical Science Basis. Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change\nKlemeš V (2016) Operational testing of hydrological simulation models. Hydrolog Sci J 31(1):13–24. https:\u002F\u002Fdoi.org\u002F10.1080\u002F02626668609491024\nLeander R, Buishand TA (2007) Resampling of regional climate model output for the simulation of extreme river flows. Journal of Hydrology 332:487–496. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jhydrol.2006.08.006\nLenderink G, Buishand A, van Deursen W (2007) Estimates of future discharges of the river Rhine using two scenario methodologies: direct versus delta approach. Hydrol Earth Syst Sci 11:1145–1159. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fhess-11-1145-2007\nLiersch S, Tecklenburg J, Rust H, Dobler A, Fischer M, Kruschke T, Koch H, Hattermann FF (2016) Are we using the right fuel to drive hydrological models ? A climate impact study in the Upper Blue Nile. Hydrol Earth Syst Sci Discuss 1–34. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fhess-2016-422\nMaraun D (2012) Nonstationarities of regional climate model biases in European seasonal mean temperature and precipitation sums. Geophys Res Lett 39:1–5. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2012GL051210\nMaraun D (2016) Bias correcting climate change simulations - a critical review. Curr Clim Change Rep 2:211–220. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs40641-016-0050-x\nMearns LO, Sain S, Leung LR, Bukovsky MS, Mcginnis S, Biner S, Caya D, Arritt RW, Gutowski W, Takle E, Snyder M, Jones RG, Nunes AMB, Tucker S, Herzmann D, Mcdaniel L, Sloan L (2013) Climate change projections of the North American Regional Climate Change Assessment Program. Climatic Change 120(4):965–975. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10584-013-0831-3\nMekonnen DF, Disse M, (2016) Analyzing the future climate change of Upper Blue Nile River Basin ( UBNRB ) using statistical down scaling techniques. Hydrol. Earth Syst. Sci. Discuss. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fhess-2016-543\nMellander P, Gebrehiwot SG, Gardenas A, Bewket W, Bishop K (2013) Summer rains and dry seasons in the Upper Blue Nile Basin : the predictability of half a century of past and future spatiotemporal patterns. PLoS ONE 8:1–12. https:\u002F\u002Fdoi.org\u002F10.1371\u002Fjournal.pone.0068461\nMoss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, van Vuuren DP, Carter TR, Emori S, Kainuma M, Kram T, Meehl GA, Mitchell JFB, Nakicenovic N, Riahi K, Smith SJ, Stouffer RJ, Thomson AM, Weyant JP, Wilbanks TJ (2010) The next generation of scenarios for climate change research and assessment. Nature 463:747–756. https:\u002F\u002Fdoi.org\u002F10.1038\u002Fnature08823\nNikulin G, Jones C, Giorgi F, Asrar G, Chner MB, Cerezo-Mota R, Christensen OB, Qué MD, Fernandez J, Nsler AH, Van Meijgaard IE, Samuelsson P, Sylla MB, Sushama L (2012) Precipitation climatology in an ensemble of CORDEX-Africa regional climate simulations. J Clim 25:6057–6078. https:\u002F\u002Fdoi.org\u002F10.1175\u002FJCLI-D-11-00375.1\nPiani C, Weedon GP, Best M, Gomes SM, Viterbo P, Hagemann S, Haerter JO (2010) Statistical bias correction of global simulated precipitation.pdf. J Hydrol 395:199–215\nRandall DA, Wood RA, Bony S, Colman R, Fichefet T, Fyfe J, Kattsov V, Pitman A, Shukla J, Srinivasan J, Stouffer RJ, Sumi A, Taylor KE (2007) Cilmate Models and Their Evaluation. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge\nRathjens H, Bieger K, Srinivasan R, Arnold JG (2016) CMhyd User Manual: Documentation for preparing simulated climate change data for hydrologic impact studies\nRitter B, Geleyn J-F (1992) A comprehensive rRadiation scheme for numerical and weather prediction models with potential application in Climate Simulations. American Meteorological Society 120:303–325\nRockel B, Will A, Hense A (2008) The regional climate model COSMO-CLM. Meteorologist Zeitschrift 17:347–348. https:\u002F\u002Fdoi.org\u002F10.1127\u002F0941-2948\u002F2008\u002F0309\nSanderson B, Tebaldi C, O’Neill B (2016) What would it take to achieve the Paris temperature targets? Geophys Res Lett 43:7133–7142. https:\u002F\u002Fdoi.org\u002F10.1002\u002F2016GL069563\nSchmidli J, Frei C, Vidale PL (2006) Downscaling from GCM precipitation: a benchmark for dynamical and statistical downscaling methods. Int J Climatol 26:679–689. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fjoc.1287\nSCRP (2000) Area of Andit Tid, Shewa , Ethiopia : Long-term Monitoring of the Agricultural Environment 1982-1994. Centre for Development and Environment, University of Berne, Switzerland, in Association with The Ministry of Agriculture, Ethiopia\nSetegn SG, Rayner D, Melesse AM, Dargahi B, Srinivasan R (2011) Impact of climate change on the hydroclimatology of Lake Tana Basin, Ethiopia. Water Resour Res 47:1–13. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2010WR009248\nTaye MT, Willems P, Block P (2015) Implications of climate change on hydrological extremes in the Blue Nile basin: a review. J Hydrol Reg Stud 4:280–293. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ejrh.2015.07.001\nTaylor K, Ronald EJ, Touffer SGAM (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93(4):485–498. https:\u002F\u002Fdoi.org\u002F10.1175\u002FBAMS-D-11-00094.1\nTesso G, Emana B, Ketema M (2012) A time series analysis of climate variability and its impacts on food production in North Shewa zone in Ethiopia. Afr Crop Sci J 20:261–274\nTeutschbein C, Seibert J (2012) Bias correction of regional climate model simulations for hydrological climate-change impact studies: review and evaluation of different methods. J Hydrol 456–457:12–29. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jhydrol.2012.05.052\nTeutschbein C, Seibert J (2013) Is bias correction of regional climate model (RCM) simulations possible for non-stationary conditions. Hydrol Earth Syst Sci 17:5061–5077. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fhess-17-5061-2013\nTiedtke M (1989) A comprehesive mass flux scheme for cumulus parameterization in large-scale models. Am J Meteorol Soc 117:1779–1800\nUN (2015) Adoption of the Paris Agreement. Conference of the Parties to the United Nations Framework Convention on Climate Change. Geneva : UN\nVan Vuuren DP, Edmonds J, Kainuma M, Riahi K, Thomson A, Hibbard K et al (2011) The representative concentration pathways: an overview. Clim Change 109:5–31. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10584-011-0148-z\nWang J, Kotamarthi VR (2015) High-resolution dynamically downscaled projections of precipitation in the mid and late 21st century over North America. Earth’s Future 3:268–288. https:\u002F\u002Fdoi.org\u002F10.1002\u002F2015EF000304.Received\nWilby RL, Wigley TM (1997) Downscaling general circulation model output: a review of methods and limitations methods and limitations. Progress in Physical Geography 21:530–548. https:\u002F\u002Fdoi.org\u002F10.1177\u002F030913339702100403\nWMO (World Meteorological Organization) (2009) Guidelines on: analysis of extremes in a changing climate in support of informed decisions for adaptation. Climate Data and Monitoring WCDMP-No. 72. Geneva, Switzerland\nWMO (World Meteorological Organization) (2009) Guidelines on: analysis of extremes in a changing climate in support of informed decisions for adaptation. Climate Data and Monitoring WCDMP-No 72\nWoldemeskel FM, Sharma A, Sivakumar B, Mehrotra R (2015) Quantification of precipitation and temperature uncertainties simulated by CMIP3 and CMIP5 models. J. Geophys. Res. Atmos. 107, 3–17. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2002JD002155\nWorku G, Teferi E, Bantider A, Dile YT (2018a) Observed changes in extremes of daily rainfall and temperature in Jemma Sub-Basin, Upper Blue Nile Basin, Ethiopia. Dyn Atmos Oceans 135:839–854. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00704-018-2412-x\nWorku G, Teferi E, Bantider A, Dile YT, Taye MT (2018b) Evaluation of regional climate models performance in simulating rainfall climatology of Jemma sub-basin, upper Blue Nile Basin, Ethiopia. Dyn Atmos Oceans 83:53–63. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.dynatmoce.2018.06.002\nYang X, Wood EF, Sheffield J, Ren L, Zhang M, Wang Y (2018). Bias correction of historical and future simulations of precipitation and temperature for China from CMIP5 models bias correction of historical and future simulations of precipitation and temperature for China from CMIP5 models. J. Hydrometeorol. 19. https:\u002F\u002Fdoi.org\u002F10.1175\u002FJHM-D-17-0180.1\nZhang X and Yang F (2004) RClimDex (1.0): user manual 1–23. Climate Research Branch Environment Canada Downsview, Ontario Canada",{"VOID":575},"10.1007\u002Fs00704-019-03053-x","2025-01-30T21:20:50.638+00:00",[277],"https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs00704-019-03053-x",[580,604,617,641],{"id":581,"sortIndex":21,"researcher":20,"roles":582,"affiliations":583,"properties":601,"displayName":603,"givenName":20,"familyName":20},"3fc0fd81-88d6-4d7c-a8ec-ab1225df20d9",[283],[584,592],{"id":585,"sortIndex":21,"affiliation":586,"properties":20},"8b71734f-c62c-4fd7-b93b-c682ac0d7904",{"id":585,"createTime":20,"updateTime":20,"relativeEntities":587,"slug":20,"properties":588,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":591,"statistic":20},[],{"title":589},{"VI":590},"Centre for Environment and Development Studies, Addis Ababa University, Addis Ababa, Ethiopia",[],{"id":593,"sortIndex":149,"affiliation":594,"properties":600},"a72c31a8-84e4-484d-987d-2dde92fa3685",{"id":593,"createTime":20,"updateTime":20,"relativeEntities":595,"slug":20,"properties":596,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":599,"statistic":20},[],{"title":597},{"VI":598},"Department of Natural Resources Management, Debretabor University, Debra Tabor, Ethiopia",[],{},{"title":602},{"VI":603},"Gebrekidan Worku",{"id":605,"sortIndex":149,"researcher":20,"roles":606,"affiliations":607,"properties":614,"displayName":616,"givenName":20,"familyName":20},"896f7ee6-c425-48ca-8fb7-83896fbb6b79",[283],[608],{"id":585,"sortIndex":21,"affiliation":609,"properties":20},{"id":585,"createTime":20,"updateTime":20,"relativeEntities":610,"slug":20,"properties":611,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":613,"statistic":20},[],{"title":612},{"VI":590},[],{"title":615},{"VI":616},"Ermias Teferi",{"id":618,"sortIndex":153,"researcher":20,"roles":619,"affiliations":620,"properties":638,"displayName":640,"givenName":20,"familyName":20},"cedd7ea5-ed0d-42eb-81c7-90b149e8f62d",[283],[621,629],{"id":622,"sortIndex":21,"affiliation":623,"properties":20},"8bf2f165-65ba-4149-a999-e424b161b2c9",{"id":622,"createTime":20,"updateTime":20,"relativeEntities":624,"slug":20,"properties":625,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":628,"statistic":20},[],{"title":626},{"VI":627},"Centre for Food Security Studies, Addis Ababa University, Addis Ababa, Ethiopia",[],{"id":630,"sortIndex":149,"affiliation":631,"properties":637},"17b76f49-3d33-4be1-9486-b5a00a2dc030",{"id":630,"createTime":20,"updateTime":20,"relativeEntities":632,"slug":20,"properties":633,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":636,"statistic":20},[],{"title":634},{"VI":635},"Water and Land Resources Centre, Addis Ababa University, Addis Ababa, Ethiopia",[],{},{"title":639},{"VI":640},"Amare Bantider",{"id":642,"sortIndex":643,"researcher":20,"roles":644,"affiliations":645,"properties":654,"displayName":656,"givenName":20,"familyName":20},"b283860c-99a3-41a1-b764-f77e8b131156",3,[283],[646],{"id":647,"sortIndex":21,"affiliation":648,"properties":20},"c82bf96d-29d8-4903-a2a2-8e74df830a39",{"id":647,"createTime":20,"updateTime":20,"relativeEntities":649,"slug":20,"properties":650,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":653,"statistic":20},[],{"title":651},{"EN":652},"College of Agriculture and Life Sciences, Texas A&M University, College Station, USA",[],{"title":655},{"VI":656},"Yihun T. Dile",{"url":578,"publisher":658,"properties":700},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":659,"slug":10,"properties":660,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":664,"manageAffiliations":669,"indexDatabases":680,"url":20,"thumbnailPath":20,"statistic":695,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":661,"title":662,"eissn":663},{"VOID":13},{"EN":15},{"VOID":17},[665],{"id":24,"createTime":20,"updateTime":20,"relativeEntities":666,"label":667,"description":668,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":27},{},[670,675],{"id":31,"createTime":20,"updateTime":20,"relativeEntities":671,"slug":20,"properties":672,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":674,"statistic":20},[],{"title":673},{"EN":35},[37],{"id":39,"createTime":20,"updateTime":20,"relativeEntities":676,"slug":20,"properties":677,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":679,"statistic":20},[],{"title":678},{"EN":43},[37],[681,688],{"id":47,"indexDatabase":682,"url":58,"indexYears":59,"academicFieldIds":687,"indexDatabaseRanking":62},{"id":49,"createTime":20,"updateTime":20,"relativeEntities":683,"label":684,"description":685,"key":55,"publicationTags":686,"standard":20},[],{"EN":52,"VI":52},{"EN":52,"VI":54},[57],[61],{"id":64,"indexDatabase":689,"url":77,"indexYears":20,"academicFieldIds":694,"indexDatabaseRanking":20},{"id":66,"createTime":20,"updateTime":20,"relativeEntities":690,"label":691,"description":692,"key":73,"publicationTags":693,"standard":20},[],{"EN":69,"VI":69},{"EN":71,"VI":72},[75,76],[79],{"impactFactor":21,"impactFactorByYear":696,"i10Index":93,"i10IndexLast5Year":94,"totalPublication":95,"totalPublicationByYear":697,"totalCitation":147,"totalCitationByYear":698,"totalCitationPerPublication":192,"totalCitationPerPublicationByYear":699,"hindexLast5Year":130,"hindex":130},{"2012":82,"2013":83,"2014":84,"2015":85,"2016":86,"2017":87,"2018":84,"2019":88,"2020":89,"2021":90,"2022":91,"2023":92},{"1948":97,"1949":98,"1950":99,"1951":100,"1952":101,"1953":102,"1954":103,"1955":104,"1956":105,"1957":106,"1958":107,"1959":108,"1960":109,"1961":110,"1962":111,"1963":105,"1964":108,"1965":112,"1966":97,"1967":111,"1968":102,"1969":112,"1970":109,"1971":104,"1972":109,"1973":113,"1974":105,"1975":107,"1976":113,"1977":113,"1978":114,"1979":113,"1980":115,"1981":111,"1982":116,"1983":114,"1984":115,"1985":99,"1986":104,"1987":102,"1988":110,"1989":117,"1990":118,"1991":116,"1992":119,"1993":120,"1994":121,"1995":122,"1996":123,"1997":124,"1998":125,"1999":126,"2000":119,"2001":119,"2002":127,"2003":125,"2004":128,"2005":129,"2006":130,"2007":128,"2008":131,"2009":94,"2010":132,"2011":133,"2012":134,"2013":135,"2014":136,"2015":137,"2016":138,"2017":139,"2018":140,"2019":141,"2020":142,"2021":143,"2022":144,"2023":145,"2024":146},{"1948":149,"1949":149,"1951":114,"1952":108,"1953":107,"1954":150,"1955":105,"1956":101,"1957":113,"1958":97,"1959":99,"1960":151,"1961":101,"1962":152,"1964":153,"1965":111,"1967":125,"1968":100,"1969":127,"1970":119,"1971":104,"1972":107,"1973":125,"1974":154,"1975":102,"1976":155,"1977":156,"1978":157,"1979":158,"1980":151,"1986":120,"1987":151,"1988":159,"1989":119,"1990":160,"1991":98,"1992":161,"1993":162,"1994":163,"1995":164,"1996":165,"1997":166,"1998":167,"1999":94,"2000":168,"2001":169,"2002":170,"2003":171,"2004":172,"2005":173,"2006":174,"2007":175,"2008":176,"2009":177,"2010":178,"2011":179,"2012":180,"2013":181,"2014":182,"2015":183,"2016":184,"2017":185,"2018":186,"2019":187,"2020":188,"2021":189,"2022":190,"2023":191,"2024":108},{"1948":194,"1949":195,"1951":196,"1952":197,"1953":198,"1954":199,"1955":197,"1956":200,"1957":201,"1958":202,"1959":203,"1960":86,"1961":204,"1962":205,"1964":206,"1965":207,"1967":208,"1968":209,"1969":210,"1970":211,"1971":149,"1972":212,"1973":213,"1974":214,"1975":89,"1976":215,"1977":87,"1978":199,"1979":198,"1980":216,"1986":217,"1987":87,"1988":218,"1989":219,"1990":220,"1991":221,"1992":222,"1993":223,"1994":224,"1995":225,"1996":226,"1997":227,"1998":228,"1999":229,"2000":230,"2001":231,"2002":232,"2003":233,"2004":234,"2005":235,"2006":236,"2007":237,"2008":238,"2009":239,"2010":240,"2011":241,"2012":242,"2013":243,"2014":244,"2015":245,"2016":246,"2017":247,"2018":248,"2019":249,"2020":250,"2021":251,"2022":252,"2023":253,"2024":254},{"pages":701,"volume":703},{"VOID":702},"1569-1588",{"VOID":704},"139","2019-12-17",2019,[62,75],{"id":709,"createTime":710,"updateTime":711,"relativeEntities":712,"slug":713,"properties":714,"entityType":275,"verifyStatus":389,"verifyTime":725,"verifyNote":391,"languages":726,"translateLanguages":20,"viewCount":21,"primaryUrl":728,"fullTextUrl":20,"authors":729,"publicationType":322,"publisherRelationship":808,"citationCount":858,"citationInfo":859,"publishDate":862,"publishYear":860,"citationAnalyzeStatus":863,"lastCitationAnalyze":864,"indexDatabases":865,"openAccess":20,"references":866,"isForceReanalyzing":374},"f2bea4f2-7df6-4846-8075-4d327421836b","2024-04-17T02:39:30.075+00:00","2026-08-24T16:03:53.911+00:00",[],"Validation-of-IPCC-AR4-models-over-the-Iberian-Peninsula",{"openalex":715,"mag":717,"title":719,"gsPaper":721,"doi":723},{"VOID":716},"W2031740445",{"VOID":718},"2031740445",{"EN":720},"Validation of IPCC AR4 models over the Iberian Peninsula",{"VOID":722},"[\"2174429238819389711\"]",{"VOID":724},"10.1007\u002Fs00704-010-0282-y","2024-05-03T13:43:40.616+00:00",[727],"EN","http:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs00704-010-0282-y",[730,751,768,789],{"id":731,"sortIndex":21,"researcher":20,"roles":732,"affiliations":733,"properties":742,"displayName":746,"givenName":20,"familyName":20},"48393cd3-04b3-4a3e-b010-672689011b55",[],[734],{"id":735,"sortIndex":21,"affiliation":736,"properties":20},"382f670e-47d6-4179-9fac-75bb012b1261",{"id":735,"createTime":20,"updateTime":20,"relativeEntities":737,"slug":20,"properties":738,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":741,"statistic":20},[],{"title":739},{"EN":740},"Department of Nuclear Engineering and Fluids Mechanics, University of the Basque Country, Vitoria-Gasteiz, Spain",[],{"orcid":743,"title":745,"gsAuthor":747,"openalex":749},{"VOID":744},"https:\u002F\u002Forcid.org\u002F0000-0003-0465-344X",{"EN":746},"Iñigo Errasti",{"VOID":748},"[\"zZqAu5cAAAAJ\"]",{"VOID":750},"A5081849185",{"id":752,"sortIndex":149,"researcher":20,"roles":753,"affiliations":754,"properties":763,"displayName":765,"givenName":20,"familyName":20},"744036e4-baac-46f4-932a-367538449d4b",[],[755],{"id":756,"sortIndex":21,"affiliation":757,"properties":20},"68a76bf1-51ac-416c-8bac-a6d6c1f76ba9",{"id":756,"createTime":20,"updateTime":20,"relativeEntities":758,"slug":20,"properties":759,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":762,"statistic":20},[],{"title":760},{"EN":761},"Department of Applied Physics II, University of the Basque Country, Vitoria-Gasteiz, Spain",[],{"title":764,"openalex":766},{"EN":765},"A. Ezcurra",{"VOID":767},"A5013155665",{"id":769,"sortIndex":153,"researcher":20,"roles":770,"affiliations":771,"properties":780,"displayName":784,"givenName":20,"familyName":20},"03aa7e85-73d4-4a47-b590-274b8f3bd767",[],[772],{"id":773,"sortIndex":21,"affiliation":774,"properties":20},"c3d60972-07b1-489f-a60e-640c9f4fa433",{"id":773,"createTime":20,"updateTime":20,"relativeEntities":775,"slug":20,"properties":776,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":779,"statistic":20},[],{"title":777},{"EN":778},"Department of Applied Physics II, University of the Basque Country, Bilbao, Spain",[],{"orcid":781,"title":783,"gsAuthor":785,"openalex":787},{"VOID":782},"https:\u002F\u002Forcid.org\u002F0000-0002-5920-7570",{"EN":784},"Jon Sáenz",{"VOID":786},"[\"c1XRv5UAAAAJ\"]",{"VOID":788},"A5028025095",{"id":790,"sortIndex":643,"researcher":20,"roles":791,"affiliations":792,"properties":801,"displayName":805,"givenName":20,"familyName":20},"be8aebf1-3872-4869-9ec5-898326cc133a",[],[793],{"id":794,"sortIndex":21,"affiliation":795,"properties":20},"245277af-5665-44a8-9ff4-de33b90ed2a4",{"id":794,"createTime":20,"updateTime":20,"relativeEntities":796,"slug":20,"properties":797,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":800,"statistic":20},[],{"title":798},{"EN":799},"Department of Nuclear Engineering and Fluids Mechanics, University of the Basque Country, Bilbao, Spain",[],{"orcid":802,"title":804,"openalex":806},{"VOID":803},"https:\u002F\u002Forcid.org\u002F0000-0001-8681-3755",{"EN":805},"Gabriel Ibarra-Berastegi",{"VOID":807},"A5086960314",{"url":20,"publisher":809,"properties":851},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":810,"slug":10,"properties":811,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":815,"manageAffiliations":820,"indexDatabases":831,"url":20,"thumbnailPath":20,"statistic":846,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":812,"title":813,"eissn":814},{"VOID":13},{"EN":15},{"VOID":17},[816],{"id":24,"createTime":20,"updateTime":20,"relativeEntities":817,"label":818,"description":819,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":27},{},[821,826],{"id":31,"createTime":20,"updateTime":20,"relativeEntities":822,"slug":20,"properties":823,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":825,"statistic":20},[],{"title":824},{"EN":35},[37],{"id":39,"createTime":20,"updateTime":20,"relativeEntities":827,"slug":20,"properties":828,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":830,"statistic":20},[],{"title":829},{"EN":43},[37],[832,839],{"id":47,"indexDatabase":833,"url":58,"indexYears":59,"academicFieldIds":838,"indexDatabaseRanking":62},{"id":49,"createTime":20,"updateTime":20,"relativeEntities":834,"label":835,"description":836,"key":55,"publicationTags":837,"standard":20},[],{"EN":52,"VI":52},{"EN":52,"VI":54},[57],[61],{"id":64,"indexDatabase":840,"url":77,"indexYears":20,"academicFieldIds":845,"indexDatabaseRanking":20},{"id":66,"createTime":20,"updateTime":20,"relativeEntities":841,"label":842,"description":843,"key":73,"publicationTags":844,"standard":20},[],{"EN":69,"VI":69},{"EN":71,"VI":72},[75,76],[79],{"impactFactor":21,"impactFactorByYear":847,"i10Index":93,"i10IndexLast5Year":94,"totalPublication":95,"totalPublicationByYear":848,"totalCitation":147,"totalCitationByYear":849,"totalCitationPerPublication":192,"totalCitationPerPublicationByYear":850,"hindexLast5Year":130,"hindex":130},{"2012":82,"2013":83,"2014":84,"2015":85,"2016":86,"2017":87,"2018":84,"2019":88,"2020":89,"2021":90,"2022":91,"2023":92},{"1948":97,"1949":98,"1950":99,"1951":100,"1952":101,"1953":102,"1954":103,"1955":104,"1956":105,"1957":106,"1958":107,"1959":108,"1960":109,"1961":110,"1962":111,"1963":105,"1964":108,"1965":112,"1966":97,"1967":111,"1968":102,"1969":112,"1970":109,"1971":104,"1972":109,"1973":113,"1974":105,"1975":107,"1976":113,"1977":113,"1978":114,"1979":113,"1980":115,"1981":111,"1982":116,"1983":114,"1984":115,"1985":99,"1986":104,"1987":102,"1988":110,"1989":117,"1990":118,"1991":116,"1992":119,"1993":120,"1994":121,"1995":122,"1996":123,"1997":124,"1998":125,"1999":126,"2000":119,"2001":119,"2002":127,"2003":125,"2004":128,"2005":129,"2006":130,"2007":128,"2008":131,"2009":94,"2010":132,"2011":133,"2012":134,"2013":135,"2014":136,"2015":137,"2016":138,"2017":139,"2018":140,"2019":141,"2020":142,"2021":143,"2022":144,"2023":145,"2024":146},{"1948":149,"1949":149,"1951":114,"1952":108,"1953":107,"1954":150,"1955":105,"1956":101,"1957":113,"1958":97,"1959":99,"1960":151,"1961":101,"1962":152,"1964":153,"1965":111,"1967":125,"1968":100,"1969":127,"1970":119,"1971":104,"1972":107,"1973":125,"1974":154,"1975":102,"1976":155,"1977":156,"1978":157,"1979":158,"1980":151,"1986":120,"1987":151,"1988":159,"1989":119,"1990":160,"1991":98,"1992":161,"1993":162,"1994":163,"1995":164,"1996":165,"1997":166,"1998":167,"1999":94,"2000":168,"2001":169,"2002":170,"2003":171,"2004":172,"2005":173,"2006":174,"2007":175,"2008":176,"2009":177,"2010":178,"2011":179,"2012":180,"2013":181,"2014":182,"2015":183,"2016":184,"2017":185,"2018":186,"2019":187,"2020":188,"2021":189,"2022":190,"2023":191,"2024":108},{"1948":194,"1949":195,"1951":196,"1952":197,"1953":198,"1954":199,"1955":197,"1956":200,"1957":201,"1958":202,"1959":203,"1960":86,"1961":204,"1962":205,"1964":206,"1965":207,"1967":208,"1968":209,"1969":210,"1970":211,"1971":149,"1972":212,"1973":213,"1974":214,"1975":89,"1976":215,"1977":87,"1978":199,"1979":198,"1980":216,"1986":217,"1987":87,"1988":218,"1989":219,"1990":220,"1991":221,"1992":222,"1993":223,"1994":224,"1995":225,"1996":226,"1997":227,"1998":228,"1999":229,"2000":230,"2001":231,"2002":232,"2003":233,"2004":234,"2005":235,"2006":236,"2007":237,"2008":238,"2009":239,"2010":240,"2011":241,"2012":242,"2013":243,"2014":244,"2015":245,"2016":246,"2017":247,"2018":248,"2019":249,"2020":250,"2021":251,"2022":252,"2023":253,"2024":254},{"issue":852,"pages":854,"volume":856},{"VOID":853},"1-2",{"VOID":855},"61-79",{"VOID":857},"103",83,{"total":858,"publishYear":860,"statisticByYear":861},2011,{"2011":643,"2012":108,"2013":99,"2014":156,"2015":108,"2016":151,"2017":156,"2018":97,"2019":153,"2020":151,"2021":151,"2022":156,"2023":97,"2024":153,"2025":149},"2011-01-01","ERROR_IN_ANALYZE_CITATION","2026-08-24T16:03:53.910+00:00",[62,75],[867,871,874,877,881,885,889,893,896,900,904,907,911,915,918,922,926,929,933,937,941,944,948,951,955,959,963,967,971,975,978,982,986,990,994,997,1001,1005,1009,1013,1017,1021,1025,1028,1032,1036,1039,1043,1047,1051,1055,1059,1063,1066,1070,1073,1077,1081,1084,1088,1092,1095,1099,1103,1107],{"id":20,"text":868,"url":20,"identifiers":869},"Adler RF, Huffman GJ, Chang A, Ferraro R, Xie P, Janowiak J, Rudolf B, Schneider U, Curtis S, Bolvin D, Gruber A, Susskind J, Arkin P, Nelkin E (2003) The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–Present). J Hydrometeor 4:1147–1167",{"doi":870},"10.1175\u002F1525-7541(2003)004\u003C1147:TVGPCP>2.0.CO;2",{"id":20,"text":872,"url":20,"identifiers":873},"Ahlfeld DP (2006) Comparison of climate model precipitation forecasts with North American Observations. Proceedings of the XVI International Conference on Computational Methods in Water Resources",{},{"id":20,"text":875,"url":20,"identifiers":876},"Alexander LV, Zhang X, Peterson TC, Caesar J, Gleason B, Klein Tank AMG, Haylock M, Collins D, Trewin B, Rahimzadeh F, Tagipour A, Rupa Kumar K, Revadekar J, Griffiths G, Vincent L, Stephenson DB, Burn J, Aguilar E, Brunet M, Taylor M, New M, Zhai P, Rusticcucci M, Vazquez-Aguirre JL (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111:D05109. doi: 10.1029\u002F 2005JD006290",{},{"id":20,"text":878,"url":20,"identifiers":879},"Bengtsson L, Hagemann S, Hodges KI (2004) Can climate trends be calculated from reanalysis data? J Geophys Res 109:D11111",{"doi":880},"10.1029\u002F2004JD004536",{"id":20,"text":882,"url":20,"identifiers":883},"Biasutti M, Giannini A (2006) Robust Sahel drying in response to late 20th century forcings. Geophys Res Lett 33:L11706. doi: 10.1029\u002F2006GL026067",{"doi":884},"10.1029\u002F2006GL026067",{"id":20,"text":886,"url":20,"identifiers":887},"Chelliah M, Ropelewski CF (2000) Reanalyses-based tropospheric temperature estimates: uncertainties in the context of global climate change detection. J Climate 13:3187–3205",{"doi":888},"10.1175\u002F1520-0442(2000)013\u003C3187:RBTTEU>2.0.CO;2",{"id":20,"text":890,"url":20,"identifiers":891},"Collins WD et al (2006) The Community Climate System Model version 3 (CCSM3). J Climate 19:2122–2143",{"doi":892},"10.1175\u002FJCLI3761.1",{"id":20,"text":894,"url":20,"identifiers":895},"De Castro M, Martín-Vide J, Alonso S (2005) El clima de España: pasado, presente y escenarios de clima para el siglo XXI. In: Moreno JM (ed) Evaluación Preliminar general de los Impactos en España por Efecto del Cambio Climático. Ministerio de Medio Ambiente. Universidad de Castilla La Mancha, Madrid",{},{"id":20,"text":897,"url":20,"identifiers":898},"Delworth TL et al (2006) GFDL’s CM2 global coupled climate models. Part I: formulation and simulation characteristics. J Climate 19:643–674",{"doi":899},"10.1175\u002FJCLI3629.1",{"id":20,"text":901,"url":20,"identifiers":902},"Dessai S, Lu X, Hulme M (2005) Limited sensitivity analysis of regional climate change probabilities for the 21st century. J Geophys Res 110:D19108. doi: 10.1029\u002F 2005JD005919",{"doi":903},"10.1029\u002F2005JD005919",{"id":20,"text":905,"url":20,"identifiers":906},"Diansky NA, Volodin EM (2002) Simulation of present-day climate with a coupled atmosphere–ocean general circulation model. Izv Atmos Ocean Phys 38:732–747",{},{"id":20,"text":908,"url":20,"identifiers":909},"Fernández-Mills G (1995) Principal component analysis of precipitation and rainfall regionalization in Spain. Theor Appl Climatol 50:169–183",{"doi":910},"10.1007\u002FBF00866115",{"id":20,"text":912,"url":20,"identifiers":913},"Flato GM, Boer GJ, Lee WG, McFarlane NA, Ramsden D, Reader MC, Weaver AJ (2000) The Canadian Centre for Climate Modeling and Analysis global coupled model at its climate. Climate Dyn 16:451–467",{"doi":914},"10.1007\u002Fs003820050339",{"id":20,"text":916,"url":20,"identifiers":917},"Font Tullot I (1983) Climatología de España y Portugal. Instituto Nacional Meteorología, 296 pp",{},{"id":20,"text":919,"url":20,"identifiers":920},"Furevik T, Bentsen M, Drange H, Kvamsto N, Sorteberg A (2003) Description and evaluation of the Bergen climate model: ARPEGE coupled with MICOM. Climate Dyn 21:27–51",{"doi":921},"10.1007\u002Fs00382-003-0317-5",{"id":20,"text":923,"url":20,"identifiers":924},"Gordon C, Cooper C, Senior CA, Banks HT, Gregory JM, Johns TC, Mitchell JFB, Wood RA (2000) The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Climate Dynamics 16:147–168",{"doi":925},"10.1007\u002Fs003820050010",{"id":20,"text":927,"url":20,"identifiers":928},"Gordon HB et al (2002) The CSIRO Mk3 climate system model. CSIRO Atmos Res Tech Rep 60:130",{},{"id":20,"text":930,"url":20,"identifiers":931},"Gualdi S, Scoccimarro E, Navarra A (2008) Changes in tropical cyclone activity due to global warming: results from a high-resolution coupled general circulation model. J Climate 21:5204–5228",{"doi":932},"10.1175\u002F2008JCLI1921.1",{"id":20,"text":934,"url":20,"identifiers":935},"Hagemann S, Gates LD (2001) Validation of the hydrological cycle of ECMWF and NCEP reanalyses using the MPI hydrological discharge model. J Geophys Res 106:1503–1510",{"doi":936},"10.1029\u002F2000JD900568",{"id":20,"text":938,"url":20,"identifiers":939},"Harrison MSJ, Palmer TN, Richardson DS, Buizza R (1999) Analysis and model dependencies in medium-range ensembles: two transplant case studies. Q J Roy Meteor Soc 125:2487–2515",{"doi":940},"10.1002\u002Fqj.49712555908",{"id":20,"text":942,"url":20,"identifiers":943},"Hasumi H, Emori S (2004). K-1 coupled model (MIROC) description. Center for Climate System Research, University of Tokio, K-1 Tech. Rep. 1, 34 pp",{},{"id":20,"text":945,"url":20,"identifiers":946},"Huffman GJ, Adler RF, Morrissey M, Bolvin DT, Curtis S, Joyce R, McGavock B, Susskind J (2001) Global precipitation at one-degree daily resolution from multi-satellite observations. J Hydrometeor 2:36–50",{"doi":947},"10.1175\u002F1525-7541(2001)002\u003C0036:GPAODD>2.0.CO;2",{"id":20,"text":949,"url":20,"identifiers":950},"Johns T, Durman C, Banks H, Roberts M, McLaren A, Ridley J, Sebior C, Williams K, Jones A, Keen A, Rickard G, Cusack S, Joshi M, Ringer M, Dong B, Spencer H, Hill R, Gregory J, Pardaens A, Lowe J, Bodas-Salcedo A, Stark S, Dearl Y (2004) HadGEM1-model description and analysis of preliminary experiments for the IPCC Fourth Assessment Report. Tech. Rep, 55, UK. Met Office, Exeter, UK",{},{"id":20,"text":952,"url":20,"identifiers":953},"Jungclaus JH et al (2006) Ocean circulation and tropical variability in the coupled model ECHAM5\u002FMPI-OM. J Climate 19:3952–3972",{"doi":954},"10.1175\u002FJCLI3827.1",{"id":20,"text":956,"url":20,"identifiers":957},"Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Leetmaa A, Reynolds R, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo K, Ropelewski C, Wang J, Jenne R, Joseph D (1996) The NCEP\u002FNCAR 40-year reanalysis project. Bull Amer Meteor Soc 77:437–471",{"doi":958},"10.1175\u002F1520-0477(1996)077\u003C0437:TNYRP>2.0.CO;2",{"id":20,"text":960,"url":20,"identifiers":961},"Lawson JS (1989) The wet spell in southern Spain, mid-October 1988. Weather 44:475–478",{"doi":962},"10.1002\u002Fj.1477-8696.1989.tb04994.x",{"id":20,"text":964,"url":20,"identifiers":965},"Lucarini L, Russell GL (2002) Comparison of mean climate trends in the northern hemisphere between National Centers for Environmental Prediction and two atmosphere–ocean model forced runs. J Geophys Res 107(D15):ACL7.1–ACL7.13. doi: 10.1029\u002F2001JD001247",{"doi":966},"10.1029\u002F2001JD001247",{"id":20,"text":968,"url":20,"identifiers":969},"Lucarini V, Calmanti S, Della Aquila A, Ruti PM, Speranza A (2007) Intercomparison of the northern hemisphere winter mid-latitude atmospheric variability of the IPCC models. Climate Dynamics 28(7–8):829",{"doi":970},"10.1007\u002Fs00382-006-0213-x",{"id":20,"text":972,"url":20,"identifiers":973},"Maxino CC, McAvaney BJ, Pitman AJ, Perkins SE (2007) Ranking the AR4 climate models over the Murray Darling Basin using simulated maximum temperature, minimum temperature and precipitation. Int J Climatol 28:1097–1112",{"doi":974},"10.1002\u002Fjoc.1612",{"id":20,"text":976,"url":20,"identifiers":977},"Marti O, Braconnot P, Bellier R et al. (2005) The new IPSL climate system model: IPSL-CM4. Note du Pole de Modelisation 26, Institute Pierre Laplace Simon, 84 pp",{},{"id":20,"text":979,"url":20,"identifiers":980},"Meehl GA, Covey C, Delworth T, Latif M, McAvaney B, Mitchell JFB, Stouffer RJ, Taylor KE (2007a) The WCRP CMIP3 multi-model dataset: a new era in climate change research. Bull Am Meteorol Soc 88:1383–1394",{"doi":981},"10.1175\u002FBAMS-88-9-1383",{"id":20,"text":983,"url":20,"identifiers":984},"Meehl GA, Arblaster JM, Tebaldi C (2007b) Contributions of natural and anthropogenic forcing to changes in temperature extremes over the United States. Geophys Res Lett 34:L19709. doi: 10.1029\u002F2007GL030948",{"doi":985},"10.1029\u002F2007GL030948",{"id":20,"text":987,"url":20,"identifiers":988},"Millan M, Estrela MJ, Caselles V (1995) Torrential precipitation on the Spanish east coast: the role of the Mediterranean sea surface temperature. Atmos Res 36:1–16",{"doi":989},"10.1016\u002F0169-8095(94)00048-I",{"id":20,"text":991,"url":20,"identifiers":992},"Min SK, Legutke S, Hense A, Kwon WT (2005) Internal variability in a 1000-year control simulation with the coupled climate model ECHO-G. Part I: near surface temperature, precipitation, and mean sea level pressure. Tellus 57A:605–621",{"doi":993},"10.1111\u002Fj.1600-0870.2005.00133.x",{"id":20,"text":995,"url":20,"identifiers":996},"Nakicenovic N, Alcamo J, Davis G, de Vries B, Fenhann J, Gaffin S, Gregory K, Grübler A, Jung TY, Kram T, La Rovere EL, Michaelis L, Mori S, Morita T, Pepper W, Pitcher H, Price L, Riahi K, Roehrl A, Rogner HH, Sankovski A, Schlesinger M, Shukla P, Smith S, Swart R, van Rooijen S, Victor N, Dadi Z (2000) IPCC special report on emissions scenarios. Cambridge University Press, Cambridge",{},{"id":20,"text":998,"url":20,"identifiers":999},"Nieto S, Rodríguez-Puebla C (2006) Comparison of precipitation from observed data and general circulation models over the Iberian Peninsula. J Climate 19:4254–4275",{"doi":1000},"10.1175\u002FJCLI3859.1",{"id":20,"text":1002,"url":20,"identifiers":1003},"Reichler T, Kim J (2008) How well do coupled models simulate today’s climate? Bull Am Meteorol Soc 8:303–311. doi: 10.1175\u002FBAMS-89-3-303",{"doi":1004},"10.1175\u002FBAMS-89-3-303",{"id":20,"text":1006,"url":20,"identifiers":1007},"Rodríguez-Puebla C, Encinas AH, Nieto S, Garmendía J (1998) Spatial and temporal patterns of annual precipitation variability over the Iberian peninsula. Int J Climatol 18:299–316",{"doi":1008},"10.1002\u002F(SICI)1097-0088(19980315)18:3\u003C299::AID-JOC247>3.0.CO;2-L",{"id":20,"text":1010,"url":20,"identifiers":1011},"Rodríguez-Puebla C, Encinas AH, Sáenz J (2001) Winter precipitation over the Iberian peninsula and its relationships to circulation indices. Hydrol Earth Syst Sci 5:233–244",{"doi":1012},"10.5194\u002Fhess-5-233-2001",{"id":20,"text":1014,"url":20,"identifiers":1015},"Russell J, Stouffer RJ, Dixon KW (2006) Intercomparison of the Southern Ocean circulations in IPCC coupled model control simulations. J Climate 19:4560–4575",{"doi":1016},"10.1175\u002FJCLI3869.1",{"id":20,"text":1018,"url":20,"identifiers":1019},"Sáenz J, Zubillaga J, Rodríguez Puebla C (2001a) Interannual variability of winter precipitation in northern Iberian Peninsula. Int J Climatol 21:1503–1513",{"doi":1020},"10.1002\u002Fjoc.699",{"id":20,"text":1022,"url":20,"identifiers":1023},"Sáenz J, Rodríguez-Puebla C, Fernández J, Zubillaga J (2001b) Interpretation of interannual winter temperature variations over Southwestern Europe. J Geophys Res 106:20641–20652",{"doi":1024},"10.1029\u002F2001JD900247",{"id":20,"text":1026,"url":20,"identifiers":1027},"Salas-Meliá D, Chauvin F, Déqué M et al. (2005). Description and validation of the CNRM-CM3 global coupled model. CNRM, Note de Centre no. 103, 36 pp",{},{"id":20,"text":1029,"url":20,"identifiers":1030},"Schmidt GA et al (2006) Present-day atmospheric simulations using GISS ModelE: comparison to in-situ, satellite and reanalysis data. J Climate 19:153–192",{"doi":1031},"10.1175\u002FJCLI3612.1",{"id":20,"text":1033,"url":20,"identifiers":1034},"Silverman BW (1986) Density estimation for statistics and data analysis. Chapman and Hall, Bristol",{"doi":1035},"10.1007\u002F978-1-4899-3324-9",{"id":20,"text":1037,"url":20,"identifiers":1038},"Simmons AJ, Gibson JK (2000) The ERA-40 project Plan, ERA-40 Project Report Series No. 1, European Centre for Medium-Range Weather Forecasts, Reading",{},{"id":20,"text":1040,"url":20,"identifiers":1041},"Sturaro G (2003) A closer look at the climatological discontinuities present in the NCEP\u002FNCAR reanalysis temperature due to the introduction of satellite data. Clim Dynam 21:309–316",{"doi":1042},"10.1007\u002Fs00382-003-0334-4",{"id":20,"text":1044,"url":20,"identifiers":1045},"Tebaldi C, Hayhoe K, Arblaster J, Meehl GA (2006) Going to the extremes. An intercomparison of model-simulated historical and future changes in extreme events. Climatic Change 79(3–4):185–211",{"doi":1046},"10.1007\u002Fs10584-006-9051-4",{"id":20,"text":1048,"url":20,"identifiers":1049},"Trenberth KE, Guillemot CJ (1995) Evaluation of the global atmospheric moisture budget as seen from analyses. J Climate 8:2255–2272",{"doi":1050},"10.1175\u002F1520-0442(1995)008\u003C2255:EOTGAM>2.0.CO;2",{"id":20,"text":1052,"url":20,"identifiers":1053},"Trenberth KE, Guillemot CJ (1998) Evaluation of the atmospheric moisture and hydrological cycle in the NCEP\u002FNCAR reanalyses. Clim Dynamics 14:213–231",{"doi":1054},"10.1007\u002Fs003820050219",{"id":20,"text":1056,"url":20,"identifiers":1057},"Trigo R, Palutikof J (2001) Precipitation scenarios over Iberia: a comparison between direct GCM output and different downscaling techniques. J Climate 14:4422–4446",{"doi":1058},"10.1175\u002F1520-0442(2001)014\u003C4422:PSOIAC>2.0.CO;2",{"id":20,"text":1060,"url":20,"identifiers":1061},"Ulbrich U, Christoph M, Pinto JG, Corte-Real J (1999) Dependence of winter precipitation over Portugal on NAO and baroclinic wave activity. Int J Climatol 19:379–390",{"doi":1062},"10.1002\u002F(SICI)1097-0088(19990330)19:4\u003C379::AID-JOC357>3.0.CO;2-8",{"id":20,"text":1064,"url":20,"identifiers":1065},"Ulbrich U, Pinto JG, Kupfer H, Leckebusch G, Spangehl T, Reyers M (2008) Changing Northern Hemisphere storm tracks in an ensemble of IPCC climate change simulations. Am Meteorol Soc 21:1669–1679",{},{"id":20,"text":1067,"url":20,"identifiers":1068},"Uppala SM, Kollberg PW, Simmons AJ, Andrae U, Da Costa BV, Fiorino M, Gibson JK, Haseler J, Hernandez A, Kelly GA, Li X, Onogi K, Saarinen S, Sokka N, Allan RP, Andersson E, Arpe K, Balmaseda MA, Beljaars ACM, Van De Berg L, Bidlot J, Bormann N, Caires S, Chevallier F, Dethof A, Dragosavac M, Fisher M, Fuentes M, Hagemann S, Hólm E, Hoskins BJ, Isaksen L, Janssen PAEM, Jenne R, McNally AP, Mahfouf JF, Morcrette JJ, Rayner NA, Saunders RW, Simon P, Sterl A, Trenberth KE, Untch A, Vasiljevic D, Viterbo P (2005) The ERA-40 re-analysis. Q J Roy Meteorol Soc 131(612):2961–3012",{"doi":1069},"10.1256\u002Fqj.04.176",{"id":20,"text":1071,"url":20,"identifiers":1072},"Vera C, Silvestri G, Liebmann B, Gonzalez P (2006) Precipitation variability in South America from IPCC-AR4 models. Part II: influence of circulation leading patterns. Proceedings of 8 ICSHMO, Foz do Iguaçu, Brazil, INPE, April 24–28, pp 477–485",{},{"id":20,"text":1074,"url":20,"identifiers":1075},"Von Storch H, Zwiers FW (1999) Statistical analysis in climate research. Cambridge University Press, New York",{"doi":1076},"10.1017\u002FCBO9780511612336",{"id":20,"text":1078,"url":20,"identifiers":1079},"Washington WM et al (2000) Parallel climate model (PCM) control and transient simulations. Climate Dynamics 16(10\u002F11):755–774",{"doi":1080},"10.1007\u002Fs003820000079",{"id":20,"text":1082,"url":20,"identifiers":1083},"Wang M, Overland JE, Kattsov V, Walsh JE, Zhang X, Pavlova T (2007) Intrinsic versus forced variation in coupled climate model arctic during the twentieth century. J Climate 20:1094–1107",{},{"id":20,"text":1085,"url":20,"identifiers":1086},"Wild M (2008) Short-wave and long wave surface radiation budgets in GCMs: a review based on the IPCC-AR4\u002FCMIP3 models. Tellus 60A:932–945",{"doi":1087},"10.1111\u002Fj.1600-0870.2008.00342.x",{"id":20,"text":1089,"url":20,"identifiers":1090},"Yin X, Gruber A, Arkin P (2004) Comparison of the GPCP and CMAP merged gauge-satellite monthly precipitation products for the period 1979–2001. J Hydrometeor 5:1207–1222",{"doi":1091},"10.1175\u002FJHM-392.1",{"id":20,"text":1093,"url":20,"identifiers":1094},"Yu Y, Yu R, Zhang X, Liu H (2004) Global coupled ocean–atmosphere general circulation models in LASG\u002FIAP. Adv Atmos Sci 19:169–190",{},{"id":20,"text":1096,"url":20,"identifiers":1097},"Yukimoto S et al (2006) Present-day climate and climate sensitivity in the Meteorological Research Institute coupled GCM version 2.3 (MRI-CGCM2.3). J Meteor Soc Japan 84:333–363",{"doi":1098},"10.2151\u002Fjmsj.84.333",{"id":20,"text":1100,"url":20,"identifiers":1101},"Xie P, Arkin PA (1997) Global precipitation: a 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull Amer Meteor Soc 78:2539–2558",{"doi":1102},"10.1175\u002F1520-0477(1997)078\u003C2539:GPAYMA>2.0.CO;2",{"id":20,"text":1104,"url":20,"identifiers":1105},"Zolina O et al (2004) Analysis of extreme precipitation over Europe from different reanalyses: a comparative assessment. Global Planet Change 44:129–161",{"doi":1106},"10.1016\u002Fj.gloplacha.2004.06.009",{"id":20,"text":1108,"url":20,"identifiers":1109},"Zorita E, Kharin V, Von Storch H (1992) The atmospheric circulation and sea surface temperature in the North Atlantic area in winter: their interaction and relevance for Iberian precipitation. J Climate 5:1097–1108",{"doi":1110},"10.1175\u002F1520-0442(1992)005\u003C1097:TACASS>2.0.CO;2",{"id":1112,"createTime":1113,"updateTime":1114,"relativeEntities":1115,"slug":1116,"properties":1117,"entityType":275,"verifyStatus":389,"verifyTime":1128,"verifyNote":391,"languages":1129,"translateLanguages":20,"viewCount":21,"primaryUrl":1130,"fullTextUrl":20,"authors":1131,"publicationType":322,"publisherRelationship":1187,"citationCount":21,"citationInfo":1230,"publishDate":20,"publishYear":20,"citationAnalyzeStatus":863,"lastCitationAnalyze":1232,"indexDatabases":1233,"openAccess":20,"references":1234,"isForceReanalyzing":374},"6dc489e5-af6d-4ed4-802b-cc0f93166617","2024-04-16T10:05:00.337+00:00","2026-08-17T21:38:17.067+00:00",[],"Projections-of-meteorological-drought-events-in-the-upper-K%C4%B1z%C4%B1l%C4%B1rmak-basin-under-climate-change-scenarios",{"openalex":1118,"abstract":1120,"title":1122,"gsPaper":1124,"doi":1126},{"VOID":1119},"W4394786371",{"EN":1121},"\u003Cjats:title>Abstract\u003C\u002Fjats:title>\u003Cjats:p>Climate change, whose negative impacts are becoming increasingly apparent as a result of human actions, intensifies the drought problems to dangerous levels. The development of local-scale drought projections is crucial to take necessary precautions for potential risks and possible effects of drought. In this study, drought analysis was conducted in the Upper Kızılırmak Basin using the standard precipitation index (SPI) method for the near future (2020–2049), mid-century (2050–2074), and late century (2075–2099). The precipitation data required for the SPI were gathered from the data sets developed for the SSP climate change scenarios of the four chosen global climate models. Precipitation data has been made more convenient for local analysis studies with the statistical downscaling method. Forecasts have been created for the temporal variation and spatial distribution of drought events. The study findings indicate that, under the SSP 2-4.5 scenario, drought-related effects of climate change will decrease until 2100. On the other hand, the number and severity of drought events, as well as the duration of dry periods, will increase until 2100 under the SSP 5-8.5 scenario. According to the SSP 5-8.5 scenario, consisting of the most pessimistic forecasts, moderate drought will last 0–60 months, severe drought will last 0–30 months, and extreme drought will last 0–20 months in different regions of the area in the late century. The spatial distribution of droughts will differ based on the SPI index and climate change scenarios. Comparison of SPI and CZI data showed that both indices are effective in meteorological drought analyses.\u003C\u002Fjats:p>",{"EN":1123},"Projections of meteorological drought events in the upper Kızılırmak basin under climate change scenarios",{"VOID":1125},"[\"8230652210977543160\"]",{"VOID":1127},"10.1007\u002Fs00704-024-04952-4","2024-04-29T23:31:50.189+00:00",[727],"https:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs00704-024-04952-4",[1132,1151,1168],{"id":1133,"sortIndex":21,"researcher":20,"roles":1134,"affiliations":1135,"properties":1144,"displayName":1148,"givenName":20,"familyName":20},"a239a115-e23c-48bc-9b57-32f8a4361d08",[],[1136],{"id":1137,"sortIndex":21,"affiliation":1138,"properties":20},"b77276d2-0463-438a-a218-5fe56facf3e7",{"id":1137,"createTime":20,"updateTime":20,"relativeEntities":1139,"slug":20,"properties":1140,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1143,"statistic":20},[],{"title":1141},{"EN":1142},"Faculty of Engineering, Environmental Engineering Department, Artvin Coruh University, Artvin, Turkey",[],{"orcid":1145,"title":1147,"openalex":1149},{"VOID":1146},"https:\u002F\u002Forcid.org\u002F0000-0002-3700-4377",{"EN":1148},"Sefa Furkan SELÇUK",{"VOID":1150},"A5079958401",{"id":1152,"sortIndex":149,"researcher":20,"roles":1153,"affiliations":1154,"properties":1163,"displayName":1165,"givenName":20,"familyName":20},"5b6ec67b-50f7-4612-92f6-97cbde49b417",[],[1155],{"id":1156,"sortIndex":21,"affiliation":1157,"properties":20},"e0b7acb6-1c90-48d5-b42c-d8ff55ff94cf",{"id":1156,"createTime":20,"updateTime":20,"relativeEntities":1158,"slug":20,"properties":1159,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1162,"statistic":20},[],{"title":1160},{"EN":1161},"Faculty of Architecture, Fine Arts and Design, Department of City and Regional Planning, Sivas Cumhuriyet University, Sivas, Turkey",[],{"title":1164,"openalex":1166},{"EN":1165},"Burcu ÇİRCİ SELÇUK",{"VOID":1167},"A5060505004",{"id":1169,"sortIndex":153,"researcher":20,"roles":1170,"affiliations":1171,"properties":1180,"displayName":1184,"givenName":20,"familyName":20},"82ca3310-cb4d-4e1b-9a5a-4f4b6611e3db",[],[1172],{"id":1173,"sortIndex":21,"affiliation":1174,"properties":20},"bfa9f2b5-f0b3-4292-b8bf-b8930881dfb3",{"id":1173,"createTime":20,"updateTime":20,"relativeEntities":1175,"slug":20,"properties":1176,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1179,"statistic":20},[],{"title":1177},{"EN":1178},"Faculty of Engineering, Environmental Engineering Department, Sivas Cumhuriyet University, Sivas, Turkey",[],{"orcid":1181,"title":1183,"openalex":1185},{"VOID":1182},"https:\u002F\u002Forcid.org\u002F0000-0002-3636-0388",{"EN":1184},"Meltem Sarıoğlu Cebeci",{"VOID":1186},"A5004021071",{"url":20,"publisher":1188,"properties":20},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1189,"slug":10,"properties":1190,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":1194,"manageAffiliations":1199,"indexDatabases":1210,"url":20,"thumbnailPath":20,"statistic":1225,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":1191,"title":1192,"eissn":1193},{"VOID":13},{"EN":15},{"VOID":17},[1195],{"id":24,"createTime":20,"updateTime":20,"relativeEntities":1196,"label":1197,"description":1198,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":27},{},[1200,1205],{"id":31,"createTime":20,"updateTime":20,"relativeEntities":1201,"slug":20,"properties":1202,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1204,"statistic":20},[],{"title":1203},{"EN":35},[37],{"id":39,"createTime":20,"updateTime":20,"relativeEntities":1206,"slug":20,"properties":1207,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1209,"statistic":20},[],{"title":1208},{"EN":43},[37],[1211,1218],{"id":47,"indexDatabase":1212,"url":58,"indexYears":59,"academicFieldIds":1217,"indexDatabaseRanking":62},{"id":49,"createTime":20,"updateTime":20,"relativeEntities":1213,"label":1214,"description":1215,"key":55,"publicationTags":1216,"standard":20},[],{"EN":52,"VI":52},{"EN":52,"VI":54},[57],[61],{"id":64,"indexDatabase":1219,"url":77,"indexYears":20,"academicFieldIds":1224,"indexDatabaseRanking":20},{"id":66,"createTime":20,"updateTime":20,"relativeEntities":1220,"label":1221,"description":1222,"key":73,"publicationTags":1223,"standard":20},[],{"EN":69,"VI":69},{"EN":71,"VI":72},[75,76],[79],{"impactFactor":21,"impactFactorByYear":1226,"i10Index":93,"i10IndexLast5Year":94,"totalPublication":95,"totalPublicationByYear":1227,"totalCitation":147,"totalCitationByYear":1228,"totalCitationPerPublication":192,"totalCitationPerPublicationByYear":1229,"hindexLast5Year":130,"hindex":130},{"2012":82,"2013":83,"2014":84,"2015":85,"2016":86,"2017":87,"2018":84,"2019":88,"2020":89,"2021":90,"2022":91,"2023":92},{"1948":97,"1949":98,"1950":99,"1951":100,"1952":101,"1953":102,"1954":103,"1955":104,"1956":105,"1957":106,"1958":107,"1959":108,"1960":109,"1961":110,"1962":111,"1963":105,"1964":108,"1965":112,"1966":97,"1967":111,"1968":102,"1969":112,"1970":109,"1971":104,"1972":109,"1973":113,"1974":105,"1975":107,"1976":113,"1977":113,"1978":114,"1979":113,"1980":115,"1981":111,"1982":116,"1983":114,"1984":115,"1985":99,"1986":104,"1987":102,"1988":110,"1989":117,"1990":118,"1991":116,"1992":119,"1993":120,"1994":121,"1995":122,"1996":123,"1997":124,"1998":125,"1999":126,"2000":119,"2001":119,"2002":127,"2003":125,"2004":128,"2005":129,"2006":130,"2007":128,"2008":131,"2009":94,"2010":132,"2011":133,"2012":134,"2013":135,"2014":136,"2015":137,"2016":138,"2017":139,"2018":140,"2019":141,"2020":142,"2021":143,"2022":144,"2023":145,"2024":146},{"1948":149,"1949":149,"1951":114,"1952":108,"1953":107,"1954":150,"1955":105,"1956":101,"1957":113,"1958":97,"1959":99,"1960":151,"1961":101,"1962":152,"1964":153,"1965":111,"1967":125,"1968":100,"1969":127,"1970":119,"1971":104,"1972":107,"1973":125,"1974":154,"1975":102,"1976":155,"1977":156,"1978":157,"1979":158,"1980":151,"1986":120,"1987":151,"1988":159,"1989":119,"1990":160,"1991":98,"1992":161,"1993":162,"1994":163,"1995":164,"1996":165,"1997":166,"1998":167,"1999":94,"2000":168,"2001":169,"2002":170,"2003":171,"2004":172,"2005":173,"2006":174,"2007":175,"2008":176,"2009":177,"2010":178,"2011":179,"2012":180,"2013":181,"2014":182,"2015":183,"2016":184,"2017":185,"2018":186,"2019":187,"2020":188,"2021":189,"2022":190,"2023":191,"2024":108},{"1948":194,"1949":195,"1951":196,"1952":197,"1953":198,"1954":199,"1955":197,"1956":200,"1957":201,"1958":202,"1959":203,"1960":86,"1961":204,"1962":205,"1964":206,"1965":207,"1967":208,"1968":209,"1969":210,"1970":211,"1971":149,"1972":212,"1973":213,"1974":214,"1975":89,"1976":215,"1977":87,"1978":199,"1979":198,"1980":216,"1986":217,"1987":87,"1988":218,"1989":219,"1990":220,"1991":221,"1992":222,"1993":223,"1994":224,"1995":225,"1996":226,"1997":227,"1998":228,"1999":229,"2000":230,"2001":231,"2002":232,"2003":233,"2004":234,"2005":235,"2006":236,"2007":237,"2008":238,"2009":239,"2010":240,"2011":241,"2012":242,"2013":243,"2014":244,"2015":245,"2016":246,"2017":247,"2018":248,"2019":249,"2020":250,"2021":251,"2022":252,"2023":253,"2024":254},{"total":21,"publishYear":20,"statisticByYear":1231},{},"2026-08-17T21:38:17.066+00:00",[],[1235,1239,1243,1247,1251,1255,1259,1263,1266,1269,1273,1277,1281,1285,1288,1292,1296,1300,1304,1308,1312,1315,1319,1323,1327,1330,1333,1337,1341,1345,1349,1352,1356,1360,1363,1367,1371,1375,1379,1383,1387,1391,1394,1397,1401,1405,1409,1413,1417],{"id":20,"text":1236,"url":20,"identifiers":1237},"Afshar MH, Şorman AÜ, Tosunoğlu F, Bulut B, Yilmaz MT, Danandeh Mehr A (2020) Climate change impact assessment on mild and extreme drought events using copulas over Ankara, Turkey. Theoretical Appl Climatology 141(3):1045–1055. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00704-020-03257-6",{"doi":1238},"10.1007\u002Fs00704-020-03257-6",{"id":20,"text":1240,"url":20,"identifiers":1241},"Anuchaivong P, Sukawat D, Luadsong A (2017) Statistical downscaling for Rainfall forecasts using modified constructed Analog Method in Thailand. Sci World J 2017:1075868. https:\u002F\u002Fdoi.org\u002F10.1155\u002F2017\u002F1075868",{"doi":1242},"10.1155\u002F2017\u002F1075868",{"id":20,"text":1244,"url":20,"identifiers":1245},"Asong ZE, Khaliq MN, Wheater HS (2016) Multisite multivariate modeling of daily precipitation and temperature in the Canadian Prairie provinces using generalized linear models. Clim Dyn 47(9):2901–2921. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00382-016-3004-z",{"doi":1246},"10.1007\u002Fs00382-016-3004-z",{"id":20,"text":1248,"url":20,"identifiers":1249},"Azizi H, Nejatian N (2022) Evaluation of the climate change impact on the intensity and return period for drought indices of SPI and SPEI (study area: Varamin plain). Water Supply 22(4):4373–4386. https:\u002F\u002Fdoi.org\u002F10.2166\u002Fws.2022.056",{"doi":1250},"10.2166\u002Fws.2022.056",{"id":20,"text":1252,"url":20,"identifiers":1253},"Blanco-Gómez P, Jimeno-Sáez P, Senent-Aparicio J, Pérez-Sánchez J (2019) Impact of Climate Change on Water Balance Components and droughts in the Guajoyo River Basin (El Salvador). Water 11:2360. https:\u002F\u002Fdoi.org\u002F10.3390\u002Fw11112360",{"doi":1254},"10.3390\u002Fw11112360",{"id":20,"text":1256,"url":20,"identifiers":1257},"Bolch T, Kulkarni A, Kääb A, Huggel C, Paul F, Cogley J, Scheel M (2012) The state and fate of himalayan glaciers. Sci 336(6079):310–314. https:\u002F\u002Fdoi.org\u002F10.1126\u002Fscience.1215828",{"doi":1258},"10.1126\u002Fscience.1215828",{"id":20,"text":1260,"url":20,"identifiers":1261},"Bong CHJ, Richard J (2020) Drought and climate change assessment using standardized precipitation index (SPI) for Sarawak River Basin. J Water Clim Change 11(4):956–965. https:\u002F\u002Fdoi.org\u002F10.2166\u002Fwcc.2019.036",{"doi":1262},"10.2166\u002Fwcc.2019.036",{"id":20,"text":1264,"url":20,"identifiers":1265},"Circi Selcuk B, Irmak MA (2022) A study on the adequacy and requirement of urban active green areas in Sivas. Fresenius Environ Bull 31(02):2209–2220",{},{"id":20,"text":1267,"url":20,"identifiers":1268},"Corell R (2007) Downscaling: An Imperative to Assess Climate Change at Regional to Local Scales. Workshop on Adaptation of Climate Scenarios to Arctic Climate Impact Assessments, May 14–16, Oslo.",{},{"id":20,"text":1270,"url":20,"identifiers":1271},"Crane RG, Hewitson BC (1998) Doubled CO2 precipitation changes for the Susquehanna Basin: down-scaling from the genesis general circulation model. International J Climatology 18(1):65–76. https:\u002F\u002Fdoi.org\u002F10.1002\u002F(SICI)1097-0088(199801)18:13.0.CO;2-9",{"doi":1272},"10.1002\u002F(SICI)1097-0088(199801)18:13.0.CO;2-9",{"id":20,"text":1274,"url":20,"identifiers":1275},"Danandeh Mehr A, Sorman AU, Kahya E, Hesami Afshar M (2020) Climate change impacts on meteorological drought using SPI and SPEI: case study of Ankara, Turkey. Hydrol Sci J 65(2):254–268. https:\u002F\u002Fdoi.org\u002F10.1080\u002F02626667.2019.1691218",{"doi":1276},"10.1080\u002F02626667.2019.1691218",{"id":20,"text":1278,"url":20,"identifiers":1279},"Dile YT, Srinivasan R (2014) Evaluation of CFSR climate data for hydrologic prediction in data-scarce watersheds: an application in the Blue Nile River Basin. J Am Water Resour Association (JAWRA) 50(5):1–16. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fjawr.12182",{"doi":1280},"10.1111\u002Fjawr.12182",{"id":20,"text":1282,"url":20,"identifiers":1283},"Dosio A, Paruolo P (2011) Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: evaluation on the present climate. J Geophys Res Atmos 116(22):1–22. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2011JD015934",{"doi":1284},"10.1029\u002F2011JD015934",{"id":20,"text":1286,"url":20,"identifiers":1287},"Edwards DC, McKee TB (1997) Characteristics of 20th century drought in the United States at multiple time scales. Climatology Report 97 – 2, Department of Atmospheric Science, Colorado State University, Fort Collins CO",{},{"id":20,"text":1289,"url":20,"identifiers":1290},"Ercan B, Yüce Mİ (2017) Trend Analysis of Hydro-Meteorological variables of Kızılırmak Basin. Nevsehir J Sci Technol 6:333–340. ICOCEE 2017 Special Issuehttps:\u002F\u002Fdoi.org\u002F10.17100\u002Fnevbiltek.323640",{"doi":1291},"10.17100\u002Fnevbiltek.323640",{"id":20,"text":1293,"url":20,"identifiers":1294},"Gomez-Gomez JF, Pulido-Velazquez D, Collados-Lara AJ, Fernandez-Chacon F (2022) The impact of climate change scenarios on droughts and their propagation in an arid Mediterranean basin. A useful approach for planning adaptation strategies. Sci Total Environ 820:153128. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.scitotenv.2022.153128",{"doi":1295},"10.1016\u002Fj.scitotenv.2022.153128",{"id":20,"text":1297,"url":20,"identifiers":1298},"Gudmundsson L, Seneviratne SI (2016) Anthropogenic climate change affects meteorological drought risk in Europe. Environ Res Lett 11(4):044005. https:\u002F\u002Fdoi.org\u002F10.1088\u002F1748-9326\u002F11\u002F4\u002F044005",{"doi":1299},"10.1088\u002F1748-9326\u002F11\u002F4\u002F044005",{"id":20,"text":1301,"url":20,"identifiers":1302},"Hagemann S, Chen C, Haerter JO, Heinke J, Gerten D, Piani C (2011) Impact of a statistical bias correction on the projected hydrological changes obtained from three GCMs and two hydrology models. J Hydrometeorology 12(4):556–578. https:\u002F\u002Fdoi.org\u002F10.1175\u002F2011JHM1336.1",{"doi":1303},"10.1175\u002F2011JHM1336.1",{"id":20,"text":1305,"url":20,"identifiers":1306},"Hamed KH, Rao AR (1998) A modified Mann-Kendall trend test for autocorrelated data. J Hydrology 204(1–4):182–196. https:\u002F\u002Fdoi.org\u002F10.1016\u002FS0022-1694(97)00125-X",{"doi":1307},"10.1016\u002FS0022-1694(97)00125-X",{"id":20,"text":1309,"url":20,"identifiers":1310},"Hayes M, Svoboda M, Wall N, Widhalm M (2011) The Lincoln Declaration on drought indices: universal meteological drought index recommended. Bull Am Meteorogical Soc 92(4):485–488",{"doi":1311},"10.1175\u002F2010BAMS3103.1",{"id":20,"text":1313,"url":20,"identifiers":1314},"IPCC (2013) In: Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J et al (eds) Climate Change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA",{},{"id":20,"text":1316,"url":20,"identifiers":1317},"IPCC (2021) In: Masson-Delmotte V, Zhai P, Pirani A, Connors SL, Péan C, Berger S, Caud N et al (eds) Climate Change 2021: the physical science basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. https:\u002F\u002Fdoi.org\u002F10.1017\u002F9781009157896",{"doi":1318},"10.1017\u002F9781009157896",{"id":20,"text":1320,"url":20,"identifiers":1321},"John JG, Blanton C, McHugh C et al (2018) NOAA-GFDL GFDL-ESM4 model output prepared for CMIP6. https:\u002F\u002Fdoi.org\u002F10.22033\u002FESGF\u002FCMIP6.8691. Earth System Grid Federation",{"doi":1322},"10.22033\u002FESGF\u002FCMIP6.8691",{"id":20,"text":1324,"url":20,"identifiers":1325},"Kelley CP, Mohtadi S, Cane MA, Seager R, Kushnir Y (2015) Climate change in the Fertile Crescent and implications of the recent Syrian drought. Proc Natl Acad Sci 112(11):3241–3246. https:\u002F\u002Fdoi.org\u002F10.1073\u002Fpnas.1421533112",{"doi":1326},"10.1073\u002Fpnas.1421533112",{"id":20,"text":1328,"url":20,"identifiers":1329},"Kendall MG (1975) Rank correlation methods. Griffin, London, UK",{},{"id":20,"text":1331,"url":20,"identifiers":1332},"Kendall MG, Stuart A (1977) The Advanced Theory of statistics. Charles Griffin & Company, London, High Wycombe",{},{"id":20,"text":1334,"url":20,"identifiers":1335},"Knutson TR, Zeng F (2018) Model assessment of observed precipitation trends over land regions: detectable human influences and possible low bias in model trends. J Clim 31(12):4617–4637. https:\u002F\u002Fdoi.org\u002F10.1175\u002FJCLI-D-17-0672.1",{"doi":1336},"10.1175\u002FJCLI-D-17-0672.1",{"id":20,"text":1338,"url":20,"identifiers":1339},"Lee SH, Yoo SH, Choi JY, Bae S (2017) Assessment of the impact of climate change on drought characteristics in the Hwanghae Plain, North Korea using time series SPI and SPEI: 1981–2100. Water 9(8):579",{"doi":1340},"10.3390\u002Fw9080579",{"id":20,"text":1342,"url":20,"identifiers":1343},"Lornezhad E, Ebrahimi H, Rabieifar HR (2023) Analysis of precipitation and drought trends by a modified Mann–Kendall method: a case study of Lorestan province, Iran. Water Supply 23(4):1557–1570. https:\u002F\u002Fdoi.org\u002F10.2166\u002Fws.2023.068",{"doi":1344},"10.2166\u002Fws.2023.068",{"id":20,"text":1346,"url":20,"identifiers":1347},"Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259. https:\u002F\u002Fdoi.org\u002F10.2307\u002F1907187",{"doi":1348},"10.2307\u002F1907187",{"id":20,"text":1350,"url":20,"identifiers":1351},"McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scale. In: Proceedings of the Eighth Conference on Applied Climatology, Anaheim, California, 17–22 January 1993, 179–184",{},{"id":20,"text":1353,"url":20,"identifiers":1354},"Merabti A, Martins DS, Meddi M, Pereira LS (2018) Spatial and time variability of drought based on SPI and RDI with various time scales. Water Resour Manage 32:1087–1100. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11269-017-1856-6",{"doi":1355},"10.1007\u002Fs11269-017-1856-6",{"id":20,"text":1357,"url":20,"identifiers":1358},"Ndhlovu GZ, Woyessa YE (2021) Use of gridded climate data for hydrological modelling in the Zambezi River Basin, Southern Africa. J Hydrology 602:126749. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jhydrol.2021.126749",{"doi":1359},"10.1016\u002Fj.jhydrol.2021.126749",{"id":20,"text":1361,"url":20,"identifiers":1362},"Sağdıç M, Koç H (2012) Climate of the Upper Kızılırmak Basin. Turkish Geographical Rev 58:1–20 (In Turkish)",{},{"id":20,"text":1364,"url":20,"identifiers":1365},"Saha S, Moorthi S, Pan HL, Wu X, Wang J, Nadiga S et al (2010) The NCEP climate forecast system reanalysis. Bull Am Meteorol Soc 91(8):1015–1057. https:\u002F\u002Fdoi.org\u002F10.1175\u002F2010BAMS3001.1",{"doi":1366},"10.1175\u002F2010BAMS3001.1",{"id":20,"text":1368,"url":20,"identifiers":1369},"Selçuk SF, Cebeci MS, Cerit O, Selçuk BÇ, Karagözoğlu MB (2022) Climate change projections of Sivas province. Nigde Omer Halisdemir Univ J Eng Sci 11(3):522–533 (In Turkish). https:\u002F\u002Fdoi.org\u002F10.28948\u002Fngumuh.1091466",{"doi":1370},"10.28948\u002Fngumuh.1091466",{"id":20,"text":1372,"url":20,"identifiers":1373},"Sen B, Topcu S, Türkeș M, Sen B, Warner JF (2012) Projecting climate change, drought conditions and crop productivity in Turkey. Clim Res 52:175–191. https:\u002F\u002Fdoi.org\u002F10.3354\u002Fcr01074",{"doi":1374},"10.3354\u002Fcr01074",{"id":20,"text":1376,"url":20,"identifiers":1377},"Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Association 63(324):1379–1389",{"doi":1378},"10.1080\u002F01621459.1968.10480934",{"id":20,"text":1380,"url":20,"identifiers":1381},"Singh VK, Kumar D (2020) Downscaling daily precipitation over the Upper Shivnath basin: a comparison of three statistical downscaling techniques. Int J Curr Microbiol Appl Sci 9(1):1676–1688. https:\u002F\u002Fdoi.org\u002F10.20546\u002Fijcmas.2020.901.185",{"doi":1382},"10.20546\u002Fijcmas.2020.901.185",{"id":20,"text":1384,"url":20,"identifiers":1385},"Timbal B, Fernandez E, Li Z (2009) Generalization of a statistical downscaling model to provide local climate change projections for Australia. Environ Modelling Softw 24:341–358. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.envsoft.2008.07.007",{"doi":1386},"10.1016\u002Fj.envsoft.2008.07.007",{"id":20,"text":1388,"url":20,"identifiers":1389},"Tramblay Y, Koutroulis A, Samaniego L, Vicente-Serrano SM, Volaire F, Boone A et al (2020) Challenges for drought assessment in the Mediterranean region under future climate scenarios. Earth-Sci Rev 210:103348. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.earscirev.2020.103348",{"doi":1390},"10.1016\u002Fj.earscirev.2020.103348",{"id":20,"text":1392,"url":20,"identifiers":1393},"Türkeş M (2012) Observed and projected Climate Change, Drought and Desertification in Turkey. Ankara Univ J Environ Sci 4(2):1–32 (In Turkish)",{},{"id":20,"text":1395,"url":20,"identifiers":1396},"Türkeş M (2019) Climate Change Education Modules Series 1: Scientific Basis of Climate Change, Effects on Turkey, 1st Edition. WEglobal Danışmanlık AŞ, Ankara,Turkey. (In Turkish)",{},{"id":20,"text":1398,"url":20,"identifiers":1399},"Vaghefi S, Abbaspour N, Kamali B, Abbaspour KC (2017) A toolkit for climate change analysis and pattern recognition for extreme weather conditions – case study: California-Baja California Peninsula. Environ Modelling Softw 96:181–198. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.envsoft.2017.06.033",{"doi":1400},"10.1016\u002Fj.envsoft.2017.06.033",{"id":20,"text":1402,"url":20,"identifiers":1403},"Volodin E, Mortikov E, Gritsun A et al (2019) INM INM-CM5-0 model output prepared for CMIP6. https:\u002F\u002Fdoi.org\u002F10.22033\u002FESGF\u002FCMIP6.12330. Earth System Grid Federation",{"doi":1404},"10.22033\u002FESGF\u002FCMIP6.12330",{"id":20,"text":1406,"url":20,"identifiers":1407},"Wu H, Hayes MJ, Weiss A, Hu QI (2001) An evaluation of the standardized precipitation index, the China-Z Index and the statistical Z‐Score. Int J Climatology: J Royal Meteorological Soc 21(6):745–758. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fjoc.658",{"doi":1408},"10.1002\u002Fjoc.658",{"id":20,"text":1410,"url":20,"identifiers":1411},"Xin X, Wu T, Shi X et al (2019) BCC BCC-CSM2MR model output prepared for CMIP6. https:\u002F\u002Fdoi.org\u002F10.22033\u002FESGF\u002FCMIP6.3035. Earth System Grid Federation",{"doi":1412},"10.22033\u002FESGF\u002FCMIP6.3035",{"id":20,"text":1414,"url":20,"identifiers":1415},"Yukimoto S, Koshiro T, Kawai H et al (2019) MRI MRI-ESM2.0 model output prepared for CMIP6. https:\u002F\u002Fdoi.org\u002F10.22033\u002FESGF\u002FCMIP6.6915. Earth System Grid Federation",{"doi":1416},"10.22033\u002FESGF\u002FCMIP6.6915",{"id":20,"text":1418,"url":20,"identifiers":1419},"Zhang Q, Li J, Singh VP, Bai Y (2012) SPI-based evaluation of drought events in Xinjiang, China. Nat Hazards 64:481–492. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11069-012-0251-0",{"doi":1420},"10.1007\u002Fs11069-012-0251-0",{"id":1422,"createTime":1423,"updateTime":1424,"relativeEntities":1425,"slug":1426,"properties":1427,"entityType":275,"verifyStatus":389,"verifyTime":1438,"verifyNote":391,"languages":1439,"translateLanguages":20,"viewCount":21,"primaryUrl":1440,"fullTextUrl":20,"authors":1441,"publicationType":322,"publisherRelationship":1478,"citationCount":643,"citationInfo":1528,"publishDate":1531,"publishYear":1529,"citationAnalyzeStatus":1532,"lastCitationAnalyze":1424,"indexDatabases":1533,"openAccess":20,"references":1534,"isForceReanalyzing":374},"f00da0a6-9ead-436c-8171-55921a8a09fd","2024-04-17T08:03:24.002+00:00","2026-08-17T15:13:53.438+00:00",[],"Regional-maximum-rainfall-analysis-using-L-moments-at-the-Titicaca-Lake-drainage-Peru",{"openalex":1428,"mag":1430,"title":1432,"gsPaper":1434,"doi":1436},{"VOID":1429},"W2469672754",{"VOID":1431},"2469672754",{"EN":1433},"Regional maximum rainfall analysis using L-moments at the Titicaca Lake drainage, Peru",{"VOID":1435},"[]",{"VOID":1437},"10.1007\u002Fs00704-016-1845-3","2024-09-05T04:48:21.140+00:00",[727],"http:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs00704-016-1845-3",[1442,1461],{"id":1443,"sortIndex":21,"researcher":20,"roles":1444,"affiliations":1445,"properties":1454,"displayName":1458,"givenName":20,"familyName":20},"488575b4-30ec-4a8e-99fc-9bbe0f4d2e3a",[],[1446],{"id":1447,"sortIndex":21,"affiliation":1448,"properties":20},"5fba8c75-2160-45c9-a05d-6810704a8595",{"id":1447,"createTime":20,"updateTime":20,"relativeEntities":1449,"slug":20,"properties":1450,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1453,"statistic":20},[],{"title":1451},{"VI":1452},"Servicio Nacional de Meteorología e Hidrología del Perú (SENAMHI), Lima, Peru",[],{"orcid":1455,"title":1457,"openalex":1459},{"VOID":1456},"https:\u002F\u002Forcid.org\u002F0000-0002-0573-4025",{"EN":1458},"Carlos Antonio Fernández-Palomino",{"VOID":1460},"A5049689839",{"id":1462,"sortIndex":149,"researcher":20,"roles":1463,"affiliations":1464,"properties":1471,"displayName":1475,"givenName":20,"familyName":20},"c6411e4b-d43c-41e3-926a-87eff1969e93",[],[1465],{"id":1447,"sortIndex":21,"affiliation":1466,"properties":20},{"id":1447,"createTime":20,"updateTime":20,"relativeEntities":1467,"slug":20,"properties":1468,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1470,"statistic":20},[],{"title":1469},{"VI":1452},[],{"orcid":1472,"title":1474,"openalex":1476},{"VOID":1473},"https:\u002F\u002Forcid.org\u002F0000-0002-0051-0743",{"EN":1475},"Waldo Lavado‐Casimiro",{"VOID":1477},"A5040285739",{"url":20,"publisher":1479,"properties":1521},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1480,"slug":10,"properties":1481,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":1485,"manageAffiliations":1490,"indexDatabases":1501,"url":20,"thumbnailPath":20,"statistic":1516,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":1482,"title":1483,"eissn":1484},{"VOID":13},{"EN":15},{"VOID":17},[1486],{"id":24,"createTime":20,"updateTime":20,"relativeEntities":1487,"label":1488,"description":1489,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":27},{},[1491,1496],{"id":31,"createTime":20,"updateTime":20,"relativeEntities":1492,"slug":20,"properties":1493,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1495,"statistic":20},[],{"title":1494},{"EN":35},[37],{"id":39,"createTime":20,"updateTime":20,"relativeEntities":1497,"slug":20,"properties":1498,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1500,"statistic":20},[],{"title":1499},{"EN":43},[37],[1502,1509],{"id":47,"indexDatabase":1503,"url":58,"indexYears":59,"academicFieldIds":1508,"indexDatabaseRanking":62},{"id":49,"createTime":20,"updateTime":20,"relativeEntities":1504,"label":1505,"description":1506,"key":55,"publicationTags":1507,"standard":20},[],{"EN":52,"VI":52},{"EN":52,"VI":54},[57],[61],{"id":64,"indexDatabase":1510,"url":77,"indexYears":20,"academicFieldIds":1515,"indexDatabaseRanking":20},{"id":66,"createTime":20,"updateTime":20,"relativeEntities":1511,"label":1512,"description":1513,"key":73,"publicationTags":1514,"standard":20},[],{"EN":69,"VI":69},{"EN":71,"VI":72},[75,76],[79],{"impactFactor":21,"impactFactorByYear":1517,"i10Index":93,"i10IndexLast5Year":94,"totalPublication":95,"totalPublicationByYear":1518,"totalCitation":147,"totalCitationByYear":1519,"totalCitationPerPublication":192,"totalCitationPerPublicationByYear":1520,"hindexLast5Year":130,"hindex":130},{"2012":82,"2013":83,"2014":84,"2015":85,"2016":86,"2017":87,"2018":84,"2019":88,"2020":89,"2021":90,"2022":91,"2023":92},{"1948":97,"1949":98,"1950":99,"1951":100,"1952":101,"1953":102,"1954":103,"1955":104,"1956":105,"1957":106,"1958":107,"1959":108,"1960":109,"1961":110,"1962":111,"1963":105,"1964":108,"1965":112,"1966":97,"1967":111,"1968":102,"1969":112,"1970":109,"1971":104,"1972":109,"1973":113,"1974":105,"1975":107,"1976":113,"1977":113,"1978":114,"1979":113,"1980":115,"1981":111,"1982":116,"1983":114,"1984":115,"1985":99,"1986":104,"1987":102,"1988":110,"1989":117,"1990":118,"1991":116,"1992":119,"1993":120,"1994":121,"1995":122,"1996":123,"1997":124,"1998":125,"1999":126,"2000":119,"2001":119,"2002":127,"2003":125,"2004":128,"2005":129,"2006":130,"2007":128,"2008":131,"2009":94,"2010":132,"2011":133,"2012":134,"2013":135,"2014":136,"2015":137,"2016":138,"2017":139,"2018":140,"2019":141,"2020":142,"2021":143,"2022":144,"2023":145,"2024":146},{"1948":149,"1949":149,"1951":114,"1952":108,"1953":107,"1954":150,"1955":105,"1956":101,"1957":113,"1958":97,"1959":99,"1960":151,"1961":101,"1962":152,"1964":153,"1965":111,"1967":125,"1968":100,"1969":127,"1970":119,"1971":104,"1972":107,"1973":125,"1974":154,"1975":102,"1976":155,"1977":156,"1978":157,"1979":158,"1980":151,"1986":120,"1987":151,"1988":159,"1989":119,"1990":160,"1991":98,"1992":161,"1993":162,"1994":163,"1995":164,"1996":165,"1997":166,"1998":167,"1999":94,"2000":168,"2001":169,"2002":170,"2003":171,"2004":172,"2005":173,"2006":174,"2007":175,"2008":176,"2009":177,"2010":178,"2011":179,"2012":180,"2013":181,"2014":182,"2015":183,"2016":184,"2017":185,"2018":186,"2019":187,"2020":188,"2021":189,"2022":190,"2023":191,"2024":108},{"1948":194,"1949":195,"1951":196,"1952":197,"1953":198,"1954":199,"1955":197,"1956":200,"1957":201,"1958":202,"1959":203,"1960":86,"1961":204,"1962":205,"1964":206,"1965":207,"1967":208,"1968":209,"1969":210,"1970":211,"1971":149,"1972":212,"1973":213,"1974":214,"1975":89,"1976":215,"1977":87,"1978":199,"1979":198,"1980":216,"1986":217,"1987":87,"1988":218,"1989":219,"1990":220,"1991":221,"1992":222,"1993":223,"1994":224,"1995":225,"1996":226,"1997":227,"1998":228,"1999":229,"2000":230,"2001":231,"2002":232,"2003":233,"2004":234,"2005":235,"2006":236,"2007":237,"2008":238,"2009":239,"2010":240,"2011":241,"2012":242,"2013":243,"2014":244,"2015":245,"2016":246,"2017":247,"2018":248,"2019":249,"2020":250,"2021":251,"2022":252,"2023":253,"2024":254},{"issue":1522,"pages":1524,"volume":1526},{"VOID":1523},"3-4",{"VOID":1525},"1295-1307",{"VOID":1527},"129",{"total":643,"publishYear":1529,"statisticByYear":1530},2017,{"2020":149,"2022":149,"2023":149},"2017-08-01","ERROR_IN_GET_PLATFORM_ID",[62,75],[1535,1538,1541,1545,1549,1553,1556,1560,1564,1567,1571,1574,1577,1581,1585,1589,1593,1597,1600,1604,1607,1611,1615,1619,1623,1627,1630,1634,1637,1640,1644,1648,1651,1655,1659,1663,1667,1671,1674,1677,1681],{"id":20,"text":1536,"url":20,"identifiers":1537},"Acuña J, Felipe O, Ordoñez J, Arboleda F (2011) Regional analysis of annual rainfall frequency for the determination of drought maps. Rev Peru GEO-ATMOSFÉRICA RPGA 115:104–115",{},{"id":20,"text":1539,"url":20,"identifiers":1540},"Barnett V, Lewis T (1984) Outliers in statistical data",{},{"id":20,"text":1542,"url":20,"identifiers":1543},"Bourges J, Cortes J, Salas E (1992) Hydrological potential. In: Dejoux C, Iltis A (eds) Lake Titicaca a synthesis of limnological knowledge. Kluwer, Dordrecht, Boston, London, pp. 523–538",{"doi":1544},"10.1007\u002F978-94-011-2406-5_13",{"id":20,"text":1546,"url":20,"identifiers":1547},"Cressie N (1985) Fitting variogram models by weighted least squares. J Int Assoc Math Geol 17:563–586. doi: 10.1007\u002FBF01032109",{"doi":1548},"10.1007\u002FBF01032109",{"id":20,"text":1550,"url":20,"identifiers":1551},"Falvey M, Garreaud RD (2005) Moisture variability over the South American Altiplano during the South American Low Level Jet Experiment (SALLJEX) observing season. J Geophys Res 110:D22105. doi: 10.1029\u002F2005JD006152",{"doi":1552},"10.1029\u002F2005JD006152",{"id":20,"text":1554,"url":20,"identifiers":1555},"Gálvez JM, Orozco RK, Reyes CR, Douglas MW (2006) Observed diurnal circulations and rainfall over the Altiplano during the SALLJEX, pp 1041–1047",{},{"id":20,"text":1557,"url":20,"identifiers":1558},"Garreaud R (1999) Multiscale analysis of the summertime precipitation over the central Andes. Mon Weather Rev 127:901–921",{"doi":1559},"10.1175\u002F1520-0493(1999)127\u003C0901:MAOTSP>2.0.CO;2",{"id":20,"text":1561,"url":20,"identifiers":1562},"Garreaud R, Aceituno P (2001) Interannual rainfall variability over the South American Altiplano. J Clim 14:2779–2789",{"doi":1563},"10.1175\u002F1520-0442(2001)014\u003C2779:IRVOTS>2.0.CO;2",{"id":20,"text":1565,"url":20,"identifiers":1566},"Goovaerts P (1997) Geostatics for natural resources evaluation. Oxford University Press, London",{},{"id":20,"text":1568,"url":20,"identifiers":1569},"Hosking JRM, Wallis JR (1997) Regional frequency analysis: an approach based on L-moments",{"doi":1570},"10.1017\u002FCBO9780511529443",{"id":20,"text":1572,"url":20,"identifiers":1573},"Johnston K, Ver Hoef JM, Krivoruchko K, Lucas N (2001) Using ArcGIS geostatistical analyst. Esri Redlands",{},{"id":20,"text":1575,"url":20,"identifiers":1576},"Kendall MG (1975) Rank correlation methods",{},{"id":20,"text":1578,"url":20,"identifiers":1579},"Kondratieva T, Amarchi H (2015) Regionalization of extreme daily precipitation: case study of the north east region of Algeria. Hydrol Sci J 60:498–507. doi: 10.1080\u002F02626667.2014.988154",{"doi":1580},"10.1080\u002F02626667.2014.988154",{"id":20,"text":1582,"url":20,"identifiers":1583},"Koutsoyiannis D, Baloutsos G (2000) Analysis of a long record of annual maximum rainfall in Athens, Greece, and design rainfall inferences. Nat Hazards 22:29–48",{"doi":1584},"10.1023\u002FA:1008001312219",{"id":20,"text":1586,"url":20,"identifiers":1587},"Lavado Casimiro WS, Ronchail J, Labat D, et al. (2012) Basin-scale analysis of rainfall and runoff in Peru (1969–2004): Pacific, Titicaca and Amazonas drainages. Hydrol Sci J 57:625–642. doi: 10.1080\u002F02626667.2012.672985",{"doi":1588},"10.1080\u002F02626667.2012.672985",{"id":20,"text":1590,"url":20,"identifiers":1591},"Ljung GM, Box GEP (1978) On a measure of lack of fit in time series models. Biometrika 65:297–303",{"doi":1592},"10.1093\u002Fbiomet\u002F65.2.297",{"id":20,"text":1594,"url":20,"identifiers":1595},"Luna Vera JA, Domínguez Mora R (2013) Un método para el análisis de frecuencia regional de lluvias máximas diarias: aplicación en los Andes bolivianos. Ingeniare Rev Chil Ing 21:111–124",{"doi":1596},"10.4067\u002FS0718-33052013000100010",{"id":20,"text":1598,"url":20,"identifiers":1599},"Mann HB (1945) Nonparametric tests against trend. Econ J Econ Soc 13:245–259",{"doi":1348},{"id":20,"text":1601,"url":20,"identifiers":1602},"McBratney AB, Webster R (1986) Choosing functions for semi-variograms of soil properties and fitting them to sampling estimates. J Soil Sci 37:617–639. doi: 10.1111\u002Fj.1365-2389.1986.tb00392.x",{"doi":1603},"10.1111\u002Fj.1365-2389.1986.tb00392.x",{"id":20,"text":1605,"url":20,"identifiers":1606},"Miller JF, Frederick RH, Tracey RS (1973) NOAA ATLAS 2, Precipitation-frequency atlas of the western United States. U.S. Dept. of Commerce, NOAA, National Weather Service, Washington DC, USA",{},{"id":20,"text":1608,"url":20,"identifiers":1609},"Ngongondo CS, Xu C-Y, Tallaksen LM, et al. (2011) Regional frequency analysis of rainfall extremes in Southern Malawi using the index rainfall and L-moments approaches. Stoch Env Res Risk A 25:939–955",{"doi":1610},"10.1007\u002Fs00477-011-0480-x",{"id":20,"text":1612,"url":20,"identifiers":1613},"Noto LV, La Loggia G (2009) Use of L-moments approach for regional flood frequency analysis in Sicily, Italy. Water Resour Manag 23:2207–2229",{"doi":1614},"10.1007\u002Fs11269-008-9378-x",{"id":20,"text":1616,"url":20,"identifiers":1617},"Núñez JH, Verbist K, Wallis JR, et al. (2011) Regional frequency analysis for mapping drought events in north-central Chile. J Hydrol 405:352–366",{"doi":1618},"10.1016\u002Fj.jhydrol.2011.05.035",{"id":20,"text":1620,"url":20,"identifiers":1621},"Pettitt AN (1979) A non-parametric approach to the change-point problem. Appl Stat:126–135",{"doi":1622},"10.2307\u002F2346729",{"id":20,"text":1624,"url":20,"identifiers":1625},"Rahman MM, Sarkar S, Najafi MR, Rai RK (2013) Regional extreme rainfall mapping for Bangladesh using L-moment technique. J Hydrol Eng 18:603–615. doi: 10.1061\u002F(asce)he.1943-5584.0000663",{"doi":1626},"10.1061\u002F(asce)he.1943-5584.0000663",{"id":20,"text":1628,"url":20,"identifiers":1629},"Roche MA, Bourges J, Cortes J, Mattos R (1992) Climatología e hidrología de la cuenca del lago Titicaca. In: Dejoux CA (ed) El Lago Titicaca. Síntesis del conocimiento Limnológico actual. Springer Netherlands, Boston, pp. 83–104 (ORSTOM - HISBOL, La Paz, Bolivia)",{},{"id":20,"text":1631,"url":20,"identifiers":1632},"Salas JD, Obeysekera J (2014) Revisiting the concepts of return period and risk for nonstationary hydrologic extreme events. J Hydrol Eng 19:554–568. doi: 10.1061\u002F(ASCE)HE.1943-5584.0000820",{"doi":1633},"10.1061\u002F(ASCE)HE.1943-5584.0000820",{"id":20,"text":1635,"url":20,"identifiers":1636},"Sanabria J, Marengo J, Valverde M (2009) Climate change scenarios using regional models for the Peruvian Altiplano (Departament of Puno). Rev Peru Geo-Atmosférica 1:133–148",{},{"id":20,"text":1638,"url":20,"identifiers":1639},"Schaefer MG, Barker BL, Taylor GH, Wallis JR (2006) Regional precipitation-frequency analysis and spatial mapping of precipitation for 24-h and 2-h durations in eastern Wahington, Prepared for Washington State Department of Transportation, MGS Engineering Consultants, Olympia, Washington, USA",{},{"id":20,"text":1641,"url":20,"identifiers":1642},"Sylvestre F, Servant-Vildary S, Roux M (2001) Diatom-based ionic concentration and salinity models from the south Bolivian Altiplano (15-23S). J Paleolimnol 25:279–295",{"doi":1643},"10.1023\u002FA:1011157611619",{"id":20,"text":1645,"url":20,"identifiers":1646},"Szolgay J, Parajka J, Kohnová S, Hlavčová K (2009) Comparison of mapping approaches of design annual maximum daily precipitation. Atmos Res 92:289–307",{"doi":1647},"10.1016\u002Fj.atmosres.2009.01.009",{"id":20,"text":1649,"url":20,"identifiers":1650},"Tveito O, Wegehenkel M, Van der Wel F, Dobesch H (2008) Use of geographic information systems in climatology and meteorology",{},{"id":20,"text":1652,"url":20,"identifiers":1653},"Verdon-Kidd DC, Kiem AS (2015) Non–stationarity in annual maxima rainfall across Australia—implications for intensity-frequency-duration (IFD) relationships. Hydrol Earth Syst Sci Discuss 12:3449–3475. doi: 10.5194\u002Fhessd-12-3449-2015",{"doi":1654},"10.5194\u002Fhessd-12-3449-2015",{"id":20,"text":1656,"url":20,"identifiers":1657},"Viglione A, Laio F, Claps P (2007) A comparison of homogeneity tests for regional frequency analysis. Water Resour Res. doi: 10.1029\u002F2006WR005095",{"doi":1658},"10.1029\u002F2006WR005095",{"id":20,"text":1660,"url":20,"identifiers":1661},"Vuille M, Ammann C (1997) Regional snowfall patterns in the high, arid Andes. In: Climatic change at high elevation sites. Springer, Berlin Heidelberg New York, pp. 181–191",{"doi":1662},"10.1007\u002F978-94-015-8905-5_10",{"id":20,"text":1664,"url":20,"identifiers":1665},"Vuille M, Keimig F (2004) Interannual variability of summertime convective cloudiness and precipitation in the central Andes derived from ISCCP-B3 data. J Clim 17:3334–3348",{"doi":1666},"10.1175\u002F1520-0442(2004)017\u003C3334:IVOSCC>2.0.CO;2",{"id":20,"text":1668,"url":20,"identifiers":1669},"Wallis JR, Schaefer MG, Barker BL, Taylor GH (2007) Regional precipitation-frequency analysis and spatial mapping for 24-hour and 2-hour durations for Washington state. Hydrol Earth Syst Sci 11:415–442. doi: 10.5194\u002Fhess-11-415-2007",{"doi":1670},"10.5194\u002Fhess-11-415-2007",{"id":20,"text":1672,"url":20,"identifiers":1673},"Weiss LL (1964) Ratio of true to fixed interval maximum rainfall. J Hydraul ASCE 90:77–82",{},{"id":20,"text":1675,"url":20,"identifiers":1676},"WWAP UN (2003) UN World Water Development Report: Water for People, Water for Life",{},{"id":20,"text":1678,"url":20,"identifiers":1679},"Yang T, Shao Q, Hao Z-C, et al. (2010) Regional frequency analysis and spatio-temporal pattern characterization of rainfall extremes in the Pearl River Basin, China. J Hydrol 380:386–405. doi: 10.1016\u002Fj.jhydrol.2009.11.013",{"doi":1680},"10.1016\u002Fj.jhydrol.2009.11.013",{"id":20,"text":1682,"url":20,"identifiers":1683},"Yue S, Pilon P, Phinney B, Cavadias G (2002) The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrol Process 16:1807–1829. doi: 10.1002\u002Fhyp.1095",{"doi":1684},"10.1002\u002Fhyp.1095",{"id":1686,"createTime":1687,"updateTime":1688,"relativeEntities":1689,"slug":1690,"properties":1691,"entityType":275,"verifyStatus":389,"verifyTime":1702,"verifyNote":391,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":1703,"fullTextUrl":20,"authors":1704,"publicationType":322,"publisherRelationship":1756,"citationCount":119,"citationInfo":1804,"publishDate":1806,"publishYear":372,"citationAnalyzeStatus":863,"lastCitationAnalyze":1807,"indexDatabases":1808,"openAccess":20,"references":20,"isForceReanalyzing":374},"c432b8ab-96e9-4eba-8104-49f8c77ac3b4","2024-01-04T18:40:14.678+00:00","2026-08-17T05:02:38.655+00:00",[],"Application-of-machine-learning-for-solar-radiation-modeling",{"abstract":1692,"title":1694,"gsPaper":1696,"references":1698,"doi":1700},{"EN":1693},"Solar radiation is an important parameter that affects the atmosphere-earth thermal balance and many water and soil processes such as evapotranspiration and plant growth. The modeling of the daily and monthly solar radiation by Gaussian process regression (GPR) with K-fold cross-validation model has been discussed recently. This study evaluated different neural models such as artificial neural network (ANN), support vector machine (SVM), adaptive network-based fuzzy inference system (ANFIS), and multiple linear regression (MLR) for estimating the global solar radiation (daily and monthly) with K-fold cross-validation method. For the appropriate comparison of the models, the randomized complete block (RCB) design applied in the training and test phases. Also, different data sets were evaluated by K-fold cross-validation in each model. The results showed that radial basis function (RBF) model has the lowest error for estimating the monthly and daily solar radiation. In this study, the result of RBF was compared with the GPR models. The conclusion indicated that RBF methodology can predict solar radiation with higher accuracy relative to the GPR model. The results of yearly solar radiation estimation (2009–2014) showed that the RBF model can estimate solar radiation with the MAPE and RMSE of 5.1% and 0.29, respectively. Also, the coefficient of correlation (R2) between actual and estimated values throughout the year is 98% and can be used by the engineers and other researchers for solar and thermal applications.",{"EN":1695},"Application of machine learning for solar radiation modeling",{"VOID":1697},"[\"5513066080383138871\"]",{"VOID":1699},"Alizamir M, Kim S, Kisi O, Zounemat-Kermani M (2020) A comparative study of several machine learning based non-linear regression methods in estimating solar radiation: case studies of the USA and Turkey regions. Energy 197:117239\nAmini S, Taki M, Rohani A (2020) Applied improved RBF neural network model for predicting the broiler output energies. Appl Soft Comp J 87:106006\nArabloo M, Ziaee H, Lee M, Bahadori A (2015) Modeling of the properties of brines using least squares support vector machine (LS-SVM) computational strategy. J Taiwan Inst Chem Eng 50:123–130\nBehrang M, Assareh E, Ghanbarzadeh A, Noghrehabadi A (2010) The potential of different artificial neural network (ANN) techniques in daily global solar radiation modeling based on meteorological data. Sol Energy 84:1468–1480\nBelmahdi B, Louzazni M, Bouardi AE (2020) One month-ahead forecasting of mean daily global solar radiation using time series models. Optik 219:165207\nBenghanem M, Mellit A (2014) A simplified calibrated model for estimating daily global solar radiation in Madinah, Saudi Arabia. Theor Appl Climatol 115:197–205\nBolandnazar E, Rohani A, Taki M (2020) Energy consumption forecasting in agriculture by artificial intelligence and mathematical models. Energy Sourc A Recov Utiliz Environ Effects 42(13):1618–1632. https:\u002F\u002Fdoi.org\u002F10.1080\u002F15567036.2019.1604872\nBurari F, Sambo A, Mshelia E (2001) Estimation of global solar radiation in Bauchi, Nig. J Ren Energy 9:34–36\nCao H, Xin Y, Yuan Q (2016) Modeling of biochar yield from cattle manure pyrolysis via least squares support vector machine intelligent approach. Bioresour Technol 202:158–164\nChandola D, Gupta H, Tikkiwal VA, Bohra MK (2020) Multi-step ahead forecasting of global solar radiation for arid zones using deep learning. Proc Comp Sci 167:626–635\nChe Y, Chen L, Zheng J, Yuan L, Xiao F (2019) A novel hybrid model of WRF and clearness index-based Kalman filter for day-ahead solar radiation forecasting. Appl Sci 9(19):3967. https:\u002F\u002Fdoi.org\u002F10.3390\u002Fapp9193967\nChen R, Ersi K, Yang J, Lu S, Zhao W (2004) Validation of five global radiation models with measured daily data in China. Energy Convers Manag 45:1759–1769\nChen J-L, Li G-S, Wu S-J (2013) Assessing the potential of support vector machine for estimating daily solar radiation using sunshine duration. Energy Convers Manag 75:311–318\nChen J-L, Li G-S, Xiao B-B, Wen Z-F, Lv M-Q, Chen C-D, Jiang Y, Wang X-X, Wu S-J (2015) Assessing the transferability of support vector machine model for estimation of global solar radiation from air temperature. Energy Convers Manag 89:318–329\nFarhadi R, Taki M (2020) The energy gain reduction due to shadow inside a flat-plate solar collector. Renew Energy 147:730–740\nFerreira PM, Gomes JM, Martins IA, Ruano AE (2012) A neural network based intelligent predictive sensor for cloudiness, solar radiation and air temperature. Sensors 12:15750–15777\nFu Z, Cheng J, .Yang M, Batista J, Jiang Y. 2020. Wastewater discharge quality prediction using stratified sampling and wavelet de-noising ANFIS model. Comput Electr Eng 85: 106701.\nGarba AA, Amusat RO, Ngadda YH (2016) Estimation of global solar radiation using sunshine-based model in Maiduguri, North East, Nigeria. Appl Res J 2:19–26\nGhimire S, Deo RC, Raj N, Mi J (2019) Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms. Appl Energy 253:113541. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.apenergy.2019.113541\nGill J, Singh J, Ohunakin OS, Adelekan DS, Atiba OE, Nkiko MO, Atayero AA (2020) Adaptive neuro-fuzzy inference system (ANFIS) approach for the irreversibility analysis of a domestic refrigerator system using LPG\u002FTiO 2 nanolubricant. Energy Rep 6:1405–1417\nHematian A, Ajabshirchi Y, Ranjbar SF, Taki M (2019) An experimental analysis of a solar-assisted heat pump (SAHP) system for heating a semisolar greenhouse, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. https:\u002F\u002Fdoi.org\u002F10.1080\u002F15567036.2019.1663308\nIsikwue B, Amah A, Agada P (2016) Empirical model for the estimation of global solar radiation in Makurdi, Nigeria. Global J Sci Front Res 12\nJović S, Aničić O, Marsenić M, Nedić B (2016) Solar radiation analyzing by neuro-fuzzy approach. Energy Build 129:261–263\nJung HC, Kim JS, Heo H (2015) Modeling of building energy consumption using an improved real coded genetic algorithm based least squares support vector machine approach. Energy Build 90:76–84\nKalogirou SA (2014) Solar energy engineering: processes and systems, second edn. Academic Press, California\nKhorasanizadeh H, Mohammadi K, Mostafaeipour A (2014) Establishing a diffuse solar radiation model for determining the optimum tilt angle of solar surfaces in Tabass, Iran. Energy Convers Manag 78:805–814\nKirmani S, Jamil M, Rizwan M (2015) Empirical correlation of estimating global solar radiation using meteorological parameters. Int J Sustain Energy 34:327–339\nKumar G, Malik H (2016) Generalized regression neural network based wind speed modeling model for western region of India. Proc Computer Sci 93:26–32\nKutucu, H., Almryad, A., 2016. Modeling of solar energy potential in Libya using an artificial neural network model, Data Stream Mining & Processing (DSMP), IEEE First International Conference on. IEEE, pp. 356-359.\nLinares-Rodriguez A, Ruiz-Arias JA, Pozo-Vazquez D, Tovar-Pescador J (2013) An artificial neural network ensemble model for estimating global solar radiation from Meteosat satellite images. Energy 61:636–645\nLiu Y, Zhou Y, Chen Y, Wang D, Wang Y, Zhu Y (2020) Comparison of support vector machine and copula-based nonlinear quantile regression for estimating the daily diffuse solar radiation: a case study in China. Renew Energy 146:1101–1112\nLockart N, Kavetski D, Franks SW (2015) A new stochastic model for simulating daily solar radiation from sunshine hours. Int J Climatol 35:1090–1106\nMardani Najafabadi M, Taki M (2020) Robust data envelopment analysis with Monte Carlo simulation model for optimization the energy consumption in agriculture. In: Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. https:\u002F\u002Fdoi.org\u002F10.1080\u002F15567036.2020.1777221\nMecibah MS, Boukelia TE, Benyahia NE (2015) Management and exploitation of direct normal irradiance resources for concentrating solar collectors: Algeria as a case study. Int J Energy Environ Eng 6:65–73\nMellit A, Benghanem M, Arab AH, Guessoum A (2005) A simplified model for generating sequences of global solar radiation data for isolated sites: using artificial neural network and a library of Markov transition matrices approach. Sol Energy 79:469–482\nMellit A, Menghanem M, Bendekhis M (2005) Artificial neural network model for modeling solar radiation data: application for sizing stand-alone photovoltaic power system, IEEE Power Engineering Society General Meeting, 2005. IEEE, New Jersey, pp 40–44\nMohammadi K, Khorasanizadeh H, Shamshirband S, Tong CW (2016) Influence of introducing various meteorological parameters to the Angström–Prescott model for estimation of global solar radiation. Environ Earth Sci 75:1–12\nMohammadi K, Shamshirband S, Kamsin A, Lai P, Mansor Z (2016) Identifying the most significant input parameters for predicting global solar radiation using an ANFIS selection procedure. Renew Sust Energ Rev 63:423–434\nMohammadi K, Shamshirband S, Tong CW, Alam KA, Petković D (2015) Potential of adaptive neuro-fuzzy system for modeling of daily global solar radiation by day of the year. Energy Convers Manag 93:406–413\nMohammadi K, Shamshirband S, Tong CW, Arif M, Petković D, Ch S (2015) A new hybrid support vector machine–wavelet transform approach for estimation of horizontal global solar radiation. Energy Convers Manag 92:162–171\nMotahari-Nezhad M, Jafari SM (2020) ANFIS system for prognosis of dynamometer high-speed ball bearing based on frequency domain acoustic emission signals. Measurement 165:108154\nNamrata, K., Sharma, S., Saksena, S., 2013. Comparison of different models for estimation of global solar radiation in Jharkhand (India) region.\nNoriega Angarita, E., Sousa Santos, V., Quintero Duran, M.J., Gil Arrieta, C., 2016. Solar Radiation Modeling for Dimensioning Photovoltaic Systems Using Artificial Neural Networks.\nOgunsanwo F, Adepitan J, Ozebo V, Ayanda J (2016) Empirical model for estimation of global radiation from sunshine duration of Ijebu-Ode. Int J Phys Sci 11:32–39\nOlatomiwa L, Mekhilef S, Shamshirband S, Mohammadi K, Petković D, Sudheer C (2015) A support vector machine–firefly algorithm-based model for global solar radiation modeling. Sol Energy 115:632–644\nOlatomiwa L, Mekhilef S, Shamshirband S, Petkovic D (2015) Potential of support vector regression for solar radiation modeling in Nigeria. Nat Hazards 77:1055–1068\nOlatomiwa L, Mekhilef S, Shamshirband S, Petković D (2015) Adaptive neuro-fuzzy approach for solar radiation modeling in Nigeria. Renew Sust Energ Rev 51:1784–1791\nPanahi M, Gayen A, Pourghasemi HR, Rezaie F, Lee S (2020) Spatial prediction of landslide susceptibility using hybrid support vector regression (SVR) and the adaptive neuro-fuzzy inference system (ANFIS) with various metaheuristic algorithms. Sci Total Environ 741:139937\nPiri J, Shamshirband S, Petković D, Tong CW, ur Rehman MH (2015) Modeling of the solar radiation on the Earth using support vector regression technique. Infrared Phys Technol 68:179–185\nRahimikhoob A (2010) Estimating global solar radiation using artificial neural network and air temperature data in a semi-arid environment. Renew Energy 35:2131–2135\nRazmjoo A, Qolipour M (2016) Technical-Economic Evaluation of Solar Energy Potential for the City of Ahvaz. Int J Renew Energy Technol Res 5:1–10\nRehman S, Mohandes M (2008) Artificial neural network estimation of global solar radiation using air temperature and relative humidity. Energy Policy 36:571–576\nRohani A, Taki M, Abdollahpour M (2018) A novel soft computing model (Gaussian process regression with K-fold cross validation) for daily and monthly solar radiation forecasting (Part: I). Renew Energy 115:411–422\nRohani A, Taki M, Bahrami G (2019) Application of artificial intelligence for separation of live and dead rainbow trout fish eggs. Artific Intellig Agricult 1:27–34\nSabet Sarvestani N, Rohani A, Farzad A, Aghkhani MH (2016) Modeling of specific fuel consumption and emission parameters of compression ignition engine using nano fluid combustion experimental data. Fuel Process Technol 154:37–43\nSaoud LS, Rahmoune F, Tourtchine V, Baddari K (2016) A novel method to forecast 24 h of global solar irradiation. Energy Syst:1–23\nShamshirband S, Mohammadi K, Khorasanizadeh H, Yee L, Lee M, Petković D, Zalnezhad E (2016) Estimating the diffuse solar radiation using a coupled support vector machine–wavelet transform model. Renew Sust Energ Rev 56:428–435\nSirabahenda Z, Simon AH, Courtenay SC, van den Heuvel MR (2020) Assessment of the effective width of riparian buffer strips to reduce suspended sediment in an agricultural landscape using ANFIS and SWAT models. CATENA. 195:104762\nSuykens JAK, Vandewalle J (1999) Least squares support vector machine classifiers. Neural Process Lett 9:293–300\nTaki M, Ajabshirchi Y, Mahmoudi A (2012) Modeling of output energy for wheat production using artificial neural networks in Esfahan province of Iran. J Agricult Technol 8(4):1229–1242\nTaki M, Ajabshirchi Y, Ranjbar SF, Rohani A, Matloobi M (2016a) Heat transfer and MLP neural network models to predict inside environment variables and energy lost in a semi-solar greenhouse. Energy Build 110:314–329\nTaki M, Ajabshirchi Y, Ranjbar SF, Rohani A, Matloobi M (2016b) Modeling and experimental validation of heat transfer and energy consumption in an innovative greenhouse structure. Inform Proc Agricult 3:157–174\nTaki M, Mahmoudi A, Ghasemi-mobtaker H, Rahbari H (2012) Energy consumption and modeling of output energy with multilayer feed-forward neural network for corn silage in Iran. Agric Eng Int: CIGR Journal 14(4):93–101\nTaki M, Mehdizade A, Rohani A, Rahnama M, Rahmati-Joneidabad M (2018) Applied machine learning in greenhouse simulation; new application and analysis. Inform Proc Agricult 5:253–268\nTaki M, Rohani A, Rahmati-Joneidabadi M (2018) Solar thermal simulation and applications in greenhouse. Inform Proc Agricult 5:83–113\nTaki M, Rohani A, Soheilifard F, Abdeshahi A (2018) Assessment of energy consumption and modeling of output energy for wheat production by neural network (MLP and RBF) and Gaussian process regression (GPR) models. J Clean Prod 172:3028–3041\nTaki M, Rohani A, Yildizhan H, Farhadi R (2019) Energy-exergy modeling of solar radiation with most influencing input parameters. Energy Sourc A Recov Utiliz Environ Effects 41(17):2128–2144. https:\u002F\u002Fdoi.org\u002F10.1080\u002F15567036.2018.1550126\nTaki M, Yildizhan H (2018) Evaluation the sustainable energy applications for fruit and vegetable productions processes; case study: greenhouse cucumber production. J Clean Prod 199:164–172\nWang L, Kisi O, Zounemat-Kermani M, Zhu Z, Gong W, Niu Z, Liu H, Liu Z (2016) Modeling of solar radiation in China using different adaptive neuro-fuzzy methods and M5 model tree. Int J Climatol 37(3):1141–1155\nZang H, Cheng L, Ding T, Cheung KW, Wang M, Wei Z, Sun G (2020) Application of functional deep belief network for estimating daily global solar radiation: a case study in China. Energy 1919:116502\nZhang H, Cheng S, Li H, Fu K, Xu Y (2020) Groundwater pollution source identification and apportionment using PMF and PCA-APCA-MLR receptor models in a typical mixed land-use area in Southwestern China. Sci Total Environ 741:140383\nZiafati A, Maleki A (2020) Fuzzy ensemble system for SSVEP stimulation frequency detection using the MLR and MsetCCA. J Neurosci Methods 338:108686",{"VOID":1701},"10.1007\u002Fs00704-020-03484-x","2024-05-16T07:08:11.801+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs00704-020-03484-x",[1705,1722,1739],{"id":1706,"sortIndex":21,"researcher":20,"roles":1707,"affiliations":1708,"properties":1717,"displayName":1719,"givenName":20,"familyName":20},"8f30ace1-f6ea-4545-a7a2-11f4777424a6",[283],[1709],{"id":1710,"sortIndex":21,"affiliation":1711,"properties":20},"937838d6-fda7-4be9-8a62-81958c1687e7",{"id":1710,"createTime":20,"updateTime":20,"relativeEntities":1712,"slug":20,"properties":1713,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1716,"statistic":20},[],{"title":1714},{"VI":1715},"Department of Agricultural Machinery and Mechanization, Faculty of Agricultural Engineering and Rural Development, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran",[],{"title":1718,"gsAuthor":1720},{"VI":1719},"Morteza Taki",{"VOID":1721},"[\"9FWme4ohTI8C\"]",{"id":1723,"sortIndex":149,"researcher":20,"roles":1724,"affiliations":1725,"properties":1734,"displayName":1736,"givenName":20,"familyName":20},"c8136038-95fc-4cb9-b70d-146e28d1ee15",[283],[1726],{"id":1727,"sortIndex":21,"affiliation":1728,"properties":20},"0e0cf3b7-0e7e-4c46-a215-366993d985b5",{"id":1727,"createTime":20,"updateTime":20,"relativeEntities":1729,"slug":20,"properties":1730,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1733,"statistic":20},[],{"title":1731},{"EN":1732},"Department of Biosystems Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran",[],{"title":1735,"gsAuthor":1737},{"VI":1736},"Abbas Rohani",{"VOID":1738},"[\"_MZ9_5AAAAAJ\"]",{"id":1740,"sortIndex":153,"researcher":20,"roles":1741,"affiliations":1742,"properties":1751,"displayName":1753,"givenName":20,"familyName":20},"dee84da7-67fa-4d64-8f8e-0e08a0e116b5",[283],[1743],{"id":1744,"sortIndex":21,"affiliation":1745,"properties":20},"eb7c4dae-c718-4767-92c9-586b9f229c6a",{"id":1744,"createTime":20,"updateTime":20,"relativeEntities":1746,"slug":20,"properties":1747,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1750,"statistic":20},[],{"title":1748},{"VI":1749},"Faculty of Engineering, Energy Systems Engineering, Adana Alparslan Türkeş Science and Technology University, Adana, Turkey",[],{"title":1752,"gsAuthor":1754},{"VI":1753},"Hasan Yildizhan",{"VOID":1755},"[\"RpZQQNkAAAAJ\"]",{"url":1703,"publisher":1757,"properties":1799},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1758,"slug":10,"properties":1759,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":1763,"manageAffiliations":1768,"indexDatabases":1779,"url":20,"thumbnailPath":20,"statistic":1794,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":1760,"title":1761,"eissn":1762},{"VOID":13},{"EN":15},{"VOID":17},[1764],{"id":24,"createTime":20,"updateTime":20,"relativeEntities":1765,"label":1766,"description":1767,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":27},{},[1769,1774],{"id":31,"createTime":20,"updateTime":20,"relativeEntities":1770,"slug":20,"properties":1771,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1773,"statistic":20},[],{"title":1772},{"EN":35},[37],{"id":39,"createTime":20,"updateTime":20,"relativeEntities":1775,"slug":20,"properties":1776,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1778,"statistic":20},[],{"title":1777},{"EN":43},[37],[1780,1787],{"id":47,"indexDatabase":1781,"url":58,"indexYears":59,"academicFieldIds":1786,"indexDatabaseRanking":62},{"id":49,"createTime":20,"updateTime":20,"relativeEntities":1782,"label":1783,"description":1784,"key":55,"publicationTags":1785,"standard":20},[],{"EN":52,"VI":52},{"EN":52,"VI":54},[57],[61],{"id":64,"indexDatabase":1788,"url":77,"indexYears":20,"academicFieldIds":1793,"indexDatabaseRanking":20},{"id":66,"createTime":20,"updateTime":20,"relativeEntities":1789,"label":1790,"description":1791,"key":73,"publicationTags":1792,"standard":20},[],{"EN":69,"VI":69},{"EN":71,"VI":72},[75,76],[79],{"impactFactor":21,"impactFactorByYear":1795,"i10Index":93,"i10IndexLast5Year":94,"totalPublication":95,"totalPublicationByYear":1796,"totalCitation":147,"totalCitationByYear":1797,"totalCitationPerPublication":192,"totalCitationPerPublicationByYear":1798,"hindexLast5Year":130,"hindex":130},{"2012":82,"2013":83,"2014":84,"2015":85,"2016":86,"2017":87,"2018":84,"2019":88,"2020":89,"2021":90,"2022":91,"2023":92},{"1948":97,"1949":98,"1950":99,"1951":100,"1952":101,"1953":102,"1954":103,"1955":104,"1956":105,"1957":106,"1958":107,"1959":108,"1960":109,"1961":110,"1962":111,"1963":105,"1964":108,"1965":112,"1966":97,"1967":111,"1968":102,"1969":112,"1970":109,"1971":104,"1972":109,"1973":113,"1974":105,"1975":107,"1976":113,"1977":113,"1978":114,"1979":113,"1980":115,"1981":111,"1982":116,"1983":114,"1984":115,"1985":99,"1986":104,"1987":102,"1988":110,"1989":117,"1990":118,"1991":116,"1992":119,"1993":120,"1994":121,"1995":122,"1996":123,"1997":124,"1998":125,"1999":126,"2000":119,"2001":119,"2002":127,"2003":125,"2004":128,"2005":129,"2006":130,"2007":128,"2008":131,"2009":94,"2010":132,"2011":133,"2012":134,"2013":135,"2014":136,"2015":137,"2016":138,"2017":139,"2018":140,"2019":141,"2020":142,"2021":143,"2022":144,"2023":145,"2024":146},{"1948":149,"1949":149,"1951":114,"1952":108,"1953":107,"1954":150,"1955":105,"1956":101,"1957":113,"1958":97,"1959":99,"1960":151,"1961":101,"1962":152,"1964":153,"1965":111,"1967":125,"1968":100,"1969":127,"1970":119,"1971":104,"1972":107,"1973":125,"1974":154,"1975":102,"1976":155,"1977":156,"1978":157,"1979":158,"1980":151,"1986":120,"1987":151,"1988":159,"1989":119,"1990":160,"1991":98,"1992":161,"1993":162,"1994":163,"1995":164,"1996":165,"1997":166,"1998":167,"1999":94,"2000":168,"2001":169,"2002":170,"2003":171,"2004":172,"2005":173,"2006":174,"2007":175,"2008":176,"2009":177,"2010":178,"2011":179,"2012":180,"2013":181,"2014":182,"2015":183,"2016":184,"2017":185,"2018":186,"2019":187,"2020":188,"2021":189,"2022":190,"2023":191,"2024":108},{"1948":194,"1949":195,"1951":196,"1952":197,"1953":198,"1954":199,"1955":197,"1956":200,"1957":201,"1958":202,"1959":203,"1960":86,"1961":204,"1962":205,"1964":206,"1965":207,"1967":208,"1968":209,"1969":210,"1970":211,"1971":149,"1972":212,"1973":213,"1974":214,"1975":89,"1976":215,"1977":87,"1978":199,"1979":198,"1980":216,"1986":217,"1987":87,"1988":218,"1989":219,"1990":220,"1991":221,"1992":222,"1993":223,"1994":224,"1995":225,"1996":226,"1997":227,"1998":228,"1999":229,"2000":230,"2001":231,"2002":232,"2003":233,"2004":234,"2005":235,"2006":236,"2007":237,"2008":238,"2009":239,"2010":240,"2011":241,"2012":242,"2013":243,"2014":244,"2015":245,"2016":246,"2017":247,"2018":248,"2019":249,"2020":250,"2021":251,"2022":252,"2023":253,"2024":254},{"pages":1800,"volume":1802},{"VOID":1801},"1599-1613",{"VOID":1803},"143",{"total":119,"publishYear":372,"statisticByYear":1805},{"2021":643,"2022":156,"2023":99,"2024":99,"2025":98,"2026":149},"2021-01-08","2026-08-17T05:02:38.652+00:00",[62,75],{"id":1810,"createTime":1811,"updateTime":1812,"relativeEntities":1813,"slug":1814,"properties":1815,"entityType":275,"verifyStatus":389,"verifyTime":1825,"verifyNote":391,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":1826,"fullTextUrl":20,"authors":1827,"publicationType":322,"publisherRelationship":1894,"citationCount":20,"citationInfo":20,"publishDate":1942,"publishYear":372,"citationAnalyzeStatus":1532,"lastCitationAnalyze":1943,"indexDatabases":1944,"openAccess":20,"references":20,"isForceReanalyzing":374},"874c21e2-6993-47af-815a-557da852fc8e","2023-12-14T07:00:31.696+00:00","2026-07-23T13:55:16.726+00:00",[],"Spatio-temporal-variability-of-atmospheric-rivers-and-associated-atmospheric-parameters-in-the-Euro-Atlantic-region",{"abstract":1816,"title":1818,"gsPaper":1820,"references":1821,"doi":1823},{"EN":1817},"We study the spatio-temporal variability of Atmospheric Rivers (ARs) and associated integrated water vapor and atmospheric parameters over the Euro-Atlantic region using long-term reanalysis datasets. Winds, temperature, and specific humidity at different pressure levels during 1979–2018 are used to study the water vapor transport integrated between 1000 and 300 hPa (IVT300) in mapping ARs. The intensity of ARs in the North Atlantic has been increasing in recent times (2009–2018) with large decadal variability and poleward shift (~ 5° towards the North) in landfall during 1999–2018. Though different reanalysis datasets show similar spatial patterns of IVT300 in mapping ARs, bias in specific humidity and wind components led to IVT300 mean bias of 50 kg m−1 s−1 in different reanalysis products compared to ERA5. The magnitude of winds and specific humidity in the lower atmosphere (below 750 hPa) dominates the total column water vapor and intensity of ARs in the North Atlantic. Reanalysis datasets in the central North Atlantic show an IVT300 standard deviation of 200 kg m−1 s−1 which is around 33% of the ARs climatology (~ 600 kg m−1 s−1). Though ARs have a higher frequency of landfalling over Western Europe in winter half-year, the intensity of IVT300 in winter ARs is 3% lower than the annual mean. The lower frequency of ARs in the summer half-year shows 3% higher IVT300 than the annual mean. While ARs in the North Atlantic show a strong decadal change in frequency and path, the impact of the North Atlantic Oscillation (NAO) and Scandinavian blocking on the location of landfall of ARs are significant. Furthermore, there is a strong latitudinal dependence of the source of moisture flux in the open ocean, contributing to the formation and strengthening ARs.",{"EN":1819},"Spatio-temporal variability of atmospheric rivers and associated atmospheric parameters in the Euro-Atlantic region",{"VOID":1435},{"VOID":1822},"Algarra I, Nieto R, Ramos AM, Eiras-Barca J, Trigo RM, Gimeno L (2020) Significant increase of global anomalous moisture uptake feeding landfalling Atmospheric Rivers. Nat Commun 11(1):1–7\nBlamey RC, Ramos AM, Trigo RM, Tomé R, Reason CJC (2018) The influence of atmospheric rivers over the South Atlantic on winter rainfall in South Africa. J Hydrometeorol 19(1):127–142\nChampion AJ, Allan RP, Lavers DA (2015) Atmospheric rivers do not explain UK summer extreme rainfall. J Geophys Res Atmos 120(14):6731–6741\nChapman WE, Subramanian AC, Delle Monache L, Xie SP, Ralph FM (2019) Improving atmospheric river forecasts with machine learning. Geophys Res Lett 46(17–18):10627–10635\nCheng BS, Chang AL, Deck A, Ferner MC (2016) Atmospheric rivers and the mass mortality of wild oysters: insight into an extreme future? Proc R Soc B Biol Sci 283(1844):20161462\nCompo, G. P., Whitaker, J. S., Sardeshmukh, P. D., Matsui, N., Allan, R. J., Yin, X., ... & Worley, S. J. (2011). The twentieth century reanalysis project. Quarterly Journal of the Royal Meteorological Society, 137(654), 1-28\nCordeira JM, Stock J, Dettinger MD, Young AM, Kalansky JF, Ralph FM (2019) A 142-year climatology of northern California landslides and atmospheric rivers. Bull Am Meteor Soc 100(8):1499–1509\nDavini P, Cagnazzo C, Fogli PG, Manzini E, Gualdi S, Navarra A (2014) European blocking and Atlantic jet stream variability in the NCEP\u002FNCAR reanalysis and the CMCC-CMS climate model. Climate Dynamics 43(1–2):71–85\nDawson A, Palmer TN, Corti S (2012) Simulating regime structures in weather and climate prediction models. Geophysical Research Letters, 39(21)\nDe Luca P, Hillier JK, Wilby RL, Quinn NW, Harrigan S (2017) Extreme multi-basin flooding linked with extra-tropical cyclones. Environ Res Lett 12(11):114009\nDee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., ... & Vitart, F. (2011). The ERA‐Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the royal meteorological society, 137(656), 553-597.\nDettinger M (2011) Climate change, atmospheric rivers, and floods in California–a multimodel analysis of storm frequency and magnitude changes 1. JAWRA J Am Water Resour Assoc 47(3):514–523\nDettinger MD, Ralph FM, Das T, Neiman PJ, Cayan DR (2011) Atmospheric rivers, floods and the water resources of California. Water 3:445–478\nEspinoza V, Waliser DE, Guan B, Lavers DA, Ralph FM (2018) Global analysis of climate change projection effects on atmospheric rivers. Geophys Res Lett 45(9):4299–4308\nFish MA, Wilson AM, Ralph FM (2019) Atmospheric river families: definition and associated synoptic conditions. J Hydrometeorol 20(10):2091–2108\nFlorsheim JL, Dettinger MD (2015) Promoting atmospheric-river and snowmelt-fueled biogeomorphic processes by restoring river-floodplain connectivity in California’s Central Valley. In Geomorphic approaches to integrated floodplain management of lowland fluvial systems in North America and Europe (pp. 119–141). Springer, New York, NY\nStohl A, Forster C, Sodemann H (2008) Remote sources of water vapor forming precipitation on the Norwegian west coast at 60 N–a tale of hurricanes and an atmospheric river. J Geophys Res Atmos 113(D5)\nGao Y, Lu J, Leung LR (2016) Uncertainties in projecting future changes in atmospheric rivers and their impacts on heavy precipitation over Europe. J Clim 29(18):6711–6726\nGelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., ... & Zhao, B. (2017). The modern-era retrospective analysis for research and applications, version 2 (MERRA-2). Journal of climate, 30(14), 5419-5454\nGimeno L, Stohl A, Trigo RM, Dominguez F, Yoshimura K, Yu L, ... Nieto R (2012) Oceanic and terrestrial sources of continental precipitation. Rev Geophys 50(4)\nGimeno L, Nieto R, Vázquez M, Lavers DA (2014) Atmospheric rivers: a mini-review. Front Earth Sci 2:2\nGimeno L (2013) Grand challenges in atmospheric science. Front Earth Sci 1:1\nGonzales KR, Swain DL, Nardi KM, Barnes EA, Diffenbaugh NS (2019) Recent warming of landfalling atmospheric rivers along the west coast of the United States. J Geophys Res Atmos 124(13):6810–6826\nGorodetskaya IV, Tsukernik M, Claes K, Ralph MF, Neff WD, Van Lipzig NP (2014) The role of atmospheric rivers in anomalous snow accumulation in East Antarctica. Geophys Res Lett 41(17):6199–6206\nGuan B, Waliser DE (2017) Atmospheric rivers in 20 year weather and climate simulations: a multimodel, global evaluation. J Geophys Res Atmos 122(11):5556–5581\nGuan B, Waliser DE (2015) Detection of atmospheric rivers: evaluation and application of an algorithm for global studies. J Geophys Res Atmos 120(24):12514–12535\nGuan B, Molotch NP, Waliser DE, Fetzer EJ, Neiman PJ (2010) Extreme snowfall events linked to atmospheric rivers and surface air temperature via satellite measurements. Geophys Res Lett 37(20)\nHack JJ, Caron JM, Yeager SG, Oleson KW, Holland MM, Truesdale JE, Rasch PJ (2006) Simulation of the global hydrological cycle in the CCSM Community Atmosphere Model version 3 (CAM3): Mean features. J Clim 19(11):2199–2221\nHannachi A, Straus DM, Franzke CL, Corti S, Woollings T (2017) Low-frequency nonlinearity and regime behavior in the Northern Hemisphere extratropical atmosphere. Rev Geophys 55(1):199–234\nHersbach H, Bell B, Berrisford P, Hirahara S, Horányi A, Muñoz-Sabater J, ... Schepers D (2017) Complete ERA5: Fifth Generation of ECMWF Atmospheric Reanalyses of the Global Climate. Copernicus Climate Change Service (C3S) Data Store (CDS)\nJiang T, Deng Y (2011) Downstream modulation of North Pacific atmospheric river activity by East Asian cold surges. Geophys Res Lett 38(20)\nKamae Y, Mei W, Xie SP (2017) Climatological relationship between warm season atmospheric rivers and heavy rainfall over East Asia. Journal of the Meteorological Society of Japan. Ser. II\nKanamitsu M, Ebisuzaki W, Woollen J, Yang SK, Hnilo JJ, Fiorino M, Potter GL (2002) Ncep–doe amip-ii reanalysis (r-2). Bull Am Meteor Soc 83(11):1631–1644\nKashinath K, Mudigonda M, Kim S, Kapp-Schwoerer L, Graubner A, Karaismailoglu E, ... Collins W (2021) ClimateNet: an expert-labeled open dataset and deep learning architecture for enabling high-precision analyses of extreme weather. Geoscientific Model Development, 14(1), 107-124\nBrubaker KL, Dara Entekhabi, Peter S. Eagleson. Atmospheric water vapor transport and continental hydrology over the Americas. Tech Rep 3–4, 1994\nKhouakhi A, Villarini G (2016) On the relationship between atmospheric rivers and high sea water levels along the US West Coast. Geophys Res Lett 43(16):8815–8822\nKomatsu KK, Alexeev VA, Repina IA, Tachibana Y (2018) Poleward upgliding Siberian atmospheric rivers over sea ice heat up Arctic upper air. Sci Rep 8(1):1–15\nKundzewicz ZW, Radziejewski M, Pinskwar I (2006) Precipitation extremes in the changing climate of Europe. Climate Res 31(1):51–58\nLavers DA, Villarini G (2013a) Atmospheric rivers and flooding over the central United States. J Clim 26(20):7829–7836\nLavers DA, Villarini G (2013b) The nexus between atmospheric rivers and extreme precipitation across Europe. Geophys Res Lett 40(12):3259–3264\nLavers DA, Villarini G (2015) The contribution of atmospheric rivers to precipitation in Europe and the United States. J Hydrol 522:382–390\nLavers DA, Pappenberger F, Richardson DS, Zsoter E (2016) ECMWF Extreme Forecast Index for water vapor transport: a forecast tool for atmospheric rivers and extreme precipitation. Geophys Res Lett 43(22):11–852\nLavers DA, Villarini G, Allan RP, Wood EF, Wade AJ (2012) The detection of atmospheric rivers in atmospheric reanalyses and their links to British winter floods and the large‐scale climatic circulation. J Geophys Res Atmos 117(D20)\nLavers, D. A., Rodwell, M. J., Richardson, D. S., Ralph, F. M., Doyle, J. D., Reynolds, C. A., ... & Pappenberger, F. (2018). The gauging and modeling of rivers in the sky. Geophys Res Lett 45(15), 7828-7834\nLavers DA, Allan RP, Wood EF, Villarini G, Brayshaw DJ, Wade AJ (2011) Winter floods in Britain are connected to atmospheric rivers. Geophys Res Lett 38(23)\nLeung LR, Qian Y (2009) Atmospheric rivers induced heavy precipitation and flooding in the western US simulated by the WRF regional climate model. Geophys Res Lett 36(3)\nLorenz EN (1963) Deterministic nonperiodic flow. J Atmos Sci 20:130–141\nMadonna E, Li C, Grams CM, Woollings T (2017) The link between eddy-driven jet variability and weather regimes in the North Atlantic-European sector. Q J R Meteorol Soc 143(708):2960–2972\nMattingly KS, Mote TL, Fettweis X (2018) Atmospheric river impacts on Greenland Ice Sheet surface mass balance. J Geophys Res Atmos 123(16):8538–8560\nMillán MM (2014) Extreme hydrometeorological events and climate change predictions in Europe. J Hydrol 518:206–224\nNash D, Waliser D, Guan B, Ye H, Ralph FM (2018) The role of atmospheric rivers in extratropical and polar hydroclimate. J Geophys Res Atmos 123(13):6804–6821\nNeff W (2018) Atmospheric rivers melt Greenland. Nat Clim Chang 8(10):857–858\nNeiman PJ, Ralph FM, White AB, Kingsmill DE, Persson POG (2002) The statistical relationship between upslope flow and rainfall in California’s coastal mountains: Observations during CALJET. Mon Weather Rev 130(6):1468–1492\nNeiman PJ, Ralph FM, Wick GA, Lundquist JD, Dettinger MD (2008a) Meteorological characteristics and overland precipitation impacts of atmospheric rivers affecting the West Coast of North America based on eight years of SSM\u002FI satellite observations. J Hydrometeorol 9(1):22–47\nNeiman PJ, Ralph FM, Wick GA, Kuo YH, Wee TK, Ma Z., ... Dettinger MD (2008b) Diagnosis of an intense atmospheric river impacting the Pacific Northwest: Storm summary and offshore vertical structure observed with COSMIC satellite retrievals. Mon Weather Rev 136(11):4398–4420. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00704-021-03776-w\nNeiman PJ, White AB, Ralph FM, Gottas DJ, Gutman SI (2009) A water vapour flux tool for precipitation forecasting. In: Proceedings of the institution of civil engineers-water management (Vol. 162, No. 2, pp. 83–94). Thomas Telford Ltd.\nNeiman PJ, Schick LJ, Ralph FM, Hughes M, Wick GA (2011) Flooding in western Washington: the connection to atmospheric rivers. J Hydrometeorol 12(6):1337–1358\nO'Brien TA, Risser MD, Loring B, Elbashandy AA, Krishnan H, Johnson J, ... Collins WD (2020) Detection of atmospheric rivers with inline uncertainty quantification: TECA-BARD v1. 0.1. Geoscientific Model Development, 13(12), 6131–6148\nPasquier JT, Pfahl S, Grams CM (2019) Modulation of atmospheric river occurrence and associated precipitation extremes in the North Atlantic region by European weather regimes. Geophys Res Lett 46(2):1014–1023\nPayne AE, Demory ME, Leung LR, Ramos AM, Shields CA, Rutz JJ, ... Ralph FM (2020) Responses and impacts of atmospheric rivers to climate change. Nat Rev Earth Environ 1(3), 143-157\nPinto JG, Raible CC (2012) Past and recent changes in the North Atlantic oscillation. Wiley Interdiscip Rev Clim Change 3(1):79–90\nPinto JG, Bellenbaum N, Karremann MK, Della-Marta PM (2013) Serial clustering of extratropical cyclones over the North Atlantic and Europe under recent and future climate conditions. J Geophysl Res Atmos 118(22):12–476\nRalph FM, Neiman PJ, Wick GA (2004) Satellite and CALJET aircraft observations of atmospheric rivers over the eastern North Pacific Ocean during the winter of 1997\u002F98. Mon Weather Rev 132(7):1721–1745\nRalph FM, Neiman PJ, Rotunno R (2005) Dropsonde observations in low-level jets over the northeastern Pacific Ocean from CALJET-1998 and PACJET-2001: Mean vertical-profile and atmospheric-river characteristics. Mon Weather Rev 133(4):889–910\nRalph FM, Dettinger MD (2011) Storms, floods, and the science of atmospheric rivers. EOS Trans Am Geophys Union 92(32):265–266\nRalph FM, Neiman PJ, Wick GA, Gutman SI, Dettinger MD, Cayan DR, White AB (2006) Flooding on California's Russian River: Role of atmospheric rivers. Geophys Res Lett 33(13)\nRalph FM, Rutz JJ, Cordeira JM, Dettinger M, Anderson M, Reynolds D, ... Smallcomb C (2019) A scale to characterize the strength and impacts of atmospheric rivers. Bull Am Meteorol Soc 100(2): 269-289\nRamos AM, Blamey RC, Algarra I, Nieto R, Gimeno L, Tomé R, ... Trigo RM (2018) From Amazonia to southern Africa: atmospheric moisture transport through low-level jets and atmospheric rivers. Ann. NY Acad. Sci 1436: 217-230\nRoberge A, Gyakum JR, Atallah EH (2009) Analysis of intense poleward water vapor transports into high latitudes of western North America. Weather Forecast 24(6):1732–1747\nSaha S, Moorthi S, Wu X, Wang J, Nadiga S, Tripp P, ... Becker E (2014) The NCEP climate forecast system version 2. Journal of climate, 27(6), 2185-2208\nSchneider EK, Kirtman BP, Lindzen RS (1999) Tropospheric water vapor and climate sensitivity. J Atmos Sci 56(11):1649–1658\nShields CA, Rutz JJ, Leung LY, Ralph FM, Wehner M, Kawzenuk B, Nguyen P (2018) Atmospheric river tracking method intercomparison project (ARTMIP): project goals and experimental design. Geosci Model Dev 11(6):2455–2474\nSellars SL, Kawzenuk B, Nguyen P, Ralph FM, Sorooshian S (2017) Genesis, pathways, and terminations of intense global water vapor transport in association with large-scale climate patterns. Geophys Res Lett 44(24):12–465\nSodemann H, Stohl A (2013) Moisture origin and meridional transport in atmospheric rivers and their association with multiple cyclones. Mon Weather Rev 141(8):2850–2868\nThapa K (2015) Atmospheric rivers carry non-monsoon extreme precipitation into western Nepal. State University of New York College of Environmental Science and Forestry\nTrenberth KE (2011) Changes in precipitation with climate change. Climate Res 47(1–2):123–138\nVan den Besselaar EJM, Klein Tank AMG, Buishand TA (2013) Trends in European precipitation extremes over 1951–2010. Int J Climatol 33(12):2682–2689\nViale M, Nuñez MN (2011) Climatology of winter orographic precipitation over the subtropical central Andes and associated synoptic and regional characteristics. J Hydrometeorol 12(4):481–507\nWaliser D, Guan B (2017) Extreme winds and precipitation during landfall of atmospheric rivers. Nat Geosci 10(3):179–183\nWoollings T, Hannachi A, Hoskins B (2010) Variability of the North Atlantic eddy-driven jet stream. Q J R Meteorol Soc 136(649):856–868\nYang Y, Zhao T, Ni G, Sun T (2018) Atmospheric rivers over the Bay of Bengal lead to northern Indian extreme rainfall. Int J Climatol 38(2):1010–1021\nZhu Y, Newell RE (1998) A proposed algorithm for moisture fluxes from atmospheric rivers. Mon Weather Rev 126(3):725–735\nZhu Y, Newell RE (1994) Atmospheric rivers and bombs. Geophys Res Lett 21(18):1999–2002",{"VOID":1824},"10.1007\u002Fs00704-021-03776-w","2024-06-25T07:29:04.706+00:00","https:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs00704-021-03776-w",[1828,1861,1881],{"id":1829,"sortIndex":21,"researcher":20,"roles":1830,"affiliations":1831,"properties":1858,"displayName":1860,"givenName":20,"familyName":20},"d9c2cf44-9f0e-4ee0-9240-7facf63d8ea9",[283],[1832,1840,1849],{"id":1833,"sortIndex":21,"affiliation":1834,"properties":20},"b1a80be4-b286-43f4-88ae-5445f3ed1d12",{"id":1833,"createTime":20,"updateTime":20,"relativeEntities":1835,"slug":20,"properties":1836,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1839,"statistic":20},[],{"title":1837},{"VI":1838},"Department of Earth Sciences, Uppsala University, Uppsala, Sweden",[],{"id":1841,"sortIndex":149,"affiliation":1842,"properties":1848},"158f28ae-f8dd-4aaa-a5ac-096049e7bfd3",{"id":1841,"createTime":20,"updateTime":20,"relativeEntities":1843,"slug":20,"properties":1844,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1847,"statistic":20},[],{"title":1845},{"VI":1846},"Centre of Natural Hazards and Disaster Science, Uppsala University, Uppsala, Sweden",[],{},{"id":1850,"sortIndex":153,"affiliation":1851,"properties":1857},"e3b79715-ca86-4a9a-85f8-56d5250fd52b",{"id":1850,"createTime":20,"updateTime":20,"relativeEntities":1852,"slug":20,"properties":1853,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1856,"statistic":20},[],{"title":1854},{"VI":1855},"Centre for Environment and Development Studies (CEMUS), Uppsala University, Uppsala, Sweden",[],{},{"title":1859},{"VI":1860},"Venugopal Thandlam",{"id":1862,"sortIndex":149,"researcher":20,"roles":1863,"affiliations":1864,"properties":1878,"displayName":1880,"givenName":20,"familyName":20},"415f62e7-ec0a-47db-802a-cbff6556bdb4",[283],[1865,1871],{"id":1833,"sortIndex":21,"affiliation":1866,"properties":20},{"id":1833,"createTime":20,"updateTime":20,"relativeEntities":1867,"slug":20,"properties":1868,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1870,"statistic":20},[],{"title":1869},{"VI":1838},[],{"id":1841,"sortIndex":149,"affiliation":1872,"properties":1877},{"id":1841,"createTime":20,"updateTime":20,"relativeEntities":1873,"slug":20,"properties":1874,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1876,"statistic":20},[],{"title":1875},{"VI":1846},[],{},{"title":1879},{"VI":1880},"Anna Rutgersson",{"id":1882,"sortIndex":153,"researcher":20,"roles":1883,"affiliations":1884,"properties":1891,"displayName":1893,"givenName":20,"familyName":20},"ad21f408-4bb6-4f73-87e3-cab0535420d7",[283],[1885],{"id":1833,"sortIndex":21,"affiliation":1886,"properties":20},{"id":1833,"createTime":20,"updateTime":20,"relativeEntities":1887,"slug":20,"properties":1888,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1890,"statistic":20},[],{"title":1889},{"VI":1838},[],{"title":1892},{"VI":1893},"Erik Sahlee",{"url":1826,"publisher":1895,"properties":1937},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1896,"slug":10,"properties":1897,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":1901,"manageAffiliations":1906,"indexDatabases":1917,"url":20,"thumbnailPath":20,"statistic":1932,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":1898,"title":1899,"eissn":1900},{"VOID":13},{"EN":15},{"VOID":17},[1902],{"id":24,"createTime":20,"updateTime":20,"relativeEntities":1903,"label":1904,"description":1905,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":27},{},[1907,1912],{"id":31,"createTime":20,"updateTime":20,"relativeEntities":1908,"slug":20,"properties":1909,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1911,"statistic":20},[],{"title":1910},{"EN":35},[37],{"id":39,"createTime":20,"updateTime":20,"relativeEntities":1913,"slug":20,"properties":1914,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1916,"statistic":20},[],{"title":1915},{"EN":43},[37],[1918,1925],{"id":47,"indexDatabase":1919,"url":58,"indexYears":59,"academicFieldIds":1924,"indexDatabaseRanking":62},{"id":49,"createTime":20,"updateTime":20,"relativeEntities":1920,"label":1921,"description":1922,"key":55,"publicationTags":1923,"standard":20},[],{"EN":52,"VI":52},{"EN":52,"VI":54},[57],[61],{"id":64,"indexDatabase":1926,"url":77,"indexYears":20,"academicFieldIds":1931,"indexDatabaseRanking":20},{"id":66,"createTime":20,"updateTime":20,"relativeEntities":1927,"label":1928,"description":1929,"key":73,"publicationTags":1930,"standard":20},[],{"EN":69,"VI":69},{"EN":71,"VI":72},[75,76],[79],{"impactFactor":21,"impactFactorByYear":1933,"i10Index":93,"i10IndexLast5Year":94,"totalPublication":95,"totalPublicationByYear":1934,"totalCitation":147,"totalCitationByYear":1935,"totalCitationPerPublication":192,"totalCitationPerPublicationByYear":1936,"hindexLast5Year":130,"hindex":130},{"2012":82,"2013":83,"2014":84,"2015":85,"2016":86,"2017":87,"2018":84,"2019":88,"2020":89,"2021":90,"2022":91,"2023":92},{"1948":97,"1949":98,"1950":99,"1951":100,"1952":101,"1953":102,"1954":103,"1955":104,"1956":105,"1957":106,"1958":107,"1959":108,"1960":109,"1961":110,"1962":111,"1963":105,"1964":108,"1965":112,"1966":97,"1967":111,"1968":102,"1969":112,"1970":109,"1971":104,"1972":109,"1973":113,"1974":105,"1975":107,"1976":113,"1977":113,"1978":114,"1979":113,"1980":115,"1981":111,"1982":116,"1983":114,"1984":115,"1985":99,"1986":104,"1987":102,"1988":110,"1989":117,"1990":118,"1991":116,"1992":119,"1993":120,"1994":121,"1995":122,"1996":123,"1997":124,"1998":125,"1999":126,"2000":119,"2001":119,"2002":127,"2003":125,"2004":128,"2005":129,"2006":130,"2007":128,"2008":131,"2009":94,"2010":132,"2011":133,"2012":134,"2013":135,"2014":136,"2015":137,"2016":138,"2017":139,"2018":140,"2019":141,"2020":142,"2021":143,"2022":144,"2023":145,"2024":146},{"1948":149,"1949":149,"1951":114,"1952":108,"1953":107,"1954":150,"1955":105,"1956":101,"1957":113,"1958":97,"1959":99,"1960":151,"1961":101,"1962":152,"1964":153,"1965":111,"1967":125,"1968":100,"1969":127,"1970":119,"1971":104,"1972":107,"1973":125,"1974":154,"1975":102,"1976":155,"1977":156,"1978":157,"1979":158,"1980":151,"1986":120,"1987":151,"1988":159,"1989":119,"1990":160,"1991":98,"1992":161,"1993":162,"1994":163,"1995":164,"1996":165,"1997":166,"1998":167,"1999":94,"2000":168,"2001":169,"2002":170,"2003":171,"2004":172,"2005":173,"2006":174,"2007":175,"2008":176,"2009":177,"2010":178,"2011":179,"2012":180,"2013":181,"2014":182,"2015":183,"2016":184,"2017":185,"2018":186,"2019":187,"2020":188,"2021":189,"2022":190,"2023":191,"2024":108},{"1948":194,"1949":195,"1951":196,"1952":197,"1953":198,"1954":199,"1955":197,"1956":200,"1957":201,"1958":202,"1959":203,"1960":86,"1961":204,"1962":205,"1964":206,"1965":207,"1967":208,"1968":209,"1969":210,"1970":211,"1971":149,"1972":212,"1973":213,"1974":214,"1975":89,"1976":215,"1977":87,"1978":199,"1979":198,"1980":216,"1986":217,"1987":87,"1988":218,"1989":219,"1990":220,"1991":221,"1992":222,"1993":223,"1994":224,"1995":225,"1996":226,"1997":227,"1998":228,"1999":229,"2000":230,"2001":231,"2002":232,"2003":233,"2004":234,"2005":235,"2006":236,"2007":237,"2008":238,"2009":239,"2010":240,"2011":241,"2012":242,"2013":243,"2014":244,"2015":245,"2016":246,"2017":247,"2018":248,"2019":249,"2020":250,"2021":251,"2022":252,"2023":253,"2024":254},{"pages":1938,"volume":1940},{"VOID":1939},"13-33",{"VOID":1941},"147","2021-10-01","2026-07-23T13:55:16.725+00:00",[62,75],{"id":1946,"createTime":1947,"updateTime":1948,"relativeEntities":1949,"slug":1950,"properties":1951,"entityType":275,"verifyStatus":389,"verifyTime":1962,"verifyNote":391,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":1963,"fullTextUrl":20,"authors":1964,"publicationType":322,"publisherRelationship":2120,"citationCount":150,"citationInfo":2168,"publishDate":2171,"publishYear":2169,"citationAnalyzeStatus":2172,"lastCitationAnalyze":2173,"indexDatabases":2174,"openAccess":20,"references":20,"isForceReanalyzing":374},"007873a7-c042-4752-815a-e63cab75fc3b","2024-01-18T08:58:53.524+00:00","2026-07-23T11:19:21.022+00:00",[],"Warming-slowdown-over-the-Tibetan-plateau-in-recent-decades",{"abstract":1952,"title":1954,"gsPaper":1956,"references":1958,"doi":1960},{"EN":1953},"As the recent global warming hiatus and the warming on high elevations are attracting worldwide attention, this study examined the robustness of the warming slowdown over the Tibetan plateau (TP) and its related driving forces. By integrating multiple-source data from 1982 to 2015 and using trend analysis, we found that the mean temperature (Tmean), maximum temperature (Tmax) and minimum temperature (Tmin) showed a slowdown of the warming trend around 1998, during the period of the global warming hiatus. This was found over both the growing season (GS) and non-growing season (NGS) and suggested a robust warming hiatus over the TP. Due to the differences in trends of Tmax and Tmin, the trend of diurnal temperature range (DTR) also shifted after 1998, especially during the GS temperature. The warming rate was spatially heterogeneous. The northern TP (NTP) experienced more warming than the southern TP (STP) in all seasons from 1982 to 1998, while the pattern was reversed in the period from 1998 to 2015. Water vapour was found to be the main driving force for the trend in Tmean and Tmin by influencing downward long wave radiation. Sunshine duration was the main driving force behind the trend in Tmax and DTR through a change in downward shortwave radiation that altered the energy source of daytime temperature. Water vapour was the major driving force for temperature change over the NTP, while over the STP, sunshine duration dominated the temperature trend.",{"EN":1955},"Warming slowdown over the Tibetan plateau in recent decades",{"VOID":1957},"[\"7460321491577774650\"]",{"VOID":1959},"An ZS, Kutzbach JE, Prell WL, Porter SC (2001) Evolution of Asian monsoons and phased uplift of the Himalayan Tibetan plateau since late Miocene times. Nature 411:62–66\nAn WL, Hou SG, Zhang WB, Wu SY, Xu H, Pang HX, Wang YT, Liu YP (2016) Possible recent warming hiatus on the northwestern Tibetan plateau derived from ice core records. Sci Rep 6:8\nCai DL, You QL, Fraedrich K, Guan YN (2017) Spatiotemporal temperature variability over the Tibetan plateau: altitudinal dependence associated with the global warming hiatus. J Clim 30:969–984\nCowtan K, Way RG (2014) Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends. Q J R Meteorol Soc 140:1935–1944\nDing M, Li L, Zhang Y, Liu L, Wang Z (2014) Temperature change and its elevation dependency on the Tibetan plateau and its vicinity from 1971 to 2012. Resour Sci 36:1509–1518\nDuan AM, Xiao ZX (2015) Does the climate warming hiatus exist over the Tibetan plateau? Sci Rep 5:9\nDuan JP, Li L, Fang YJ (2015) Seasonal spatial heterogeneity of warming rates on the Tibetan plateau over the past 30 years. Sci Rep 5:8\nEasterling DR, Wehner MF (2009) Is the climate warming or cooling? Geophys Res Lett 36:3\nFyfe JC, Gillett NP, Zwiers FW (2013a) Overestimated global warming over the past 20 years. Nat Clim Chang 3:767–769\nFyfe JC, von Salzen K, Cole JNS, Gillett NP, Vernier JP (2013b) Surface response to stratospheric aerosol changes in a coupled atmosphere-ocean model. Geophys Res Lett 40:584–588\nFyfe JC, Meehl GA, England MH, Mann ME, Santer BD, Flato GM, Hawkins E, Gillett NP, Xie SP, Kosaka Y, Swart NC (2016) Making sense of the early-2000s warming slowdown. Nat Clim Chang 6:224–228\nGao YH, Cuo L, Zhang YX (2014) Changes in moisture flux over the Tibetan plateau during 1979-2011 and possible mechanisms. J Clim 27:1876–1893\nGao YH, Xu JW, Chen DL (2015) Evaluation of WRF mesoscale climate simulations over the Tibetan plateau during 1979-2011. J Clim 28:2823–2841\nGuemas V, Doblas-Reyes FJ, Andreu-Burillo I, Asif M (2013) Retrospective prediction of the global warming slowdown in the past decade. Nat Clim Chang 3:649–653\nGuo DL, Wang HJ (2012) The significant climate warming in the northern Tibetan plateau and its possible causes. Int J Climatol 32:1775–1781\nHaywood JM, Jones A, Jones GS (2014) The impact of volcanic eruptions in the period 2000-2013 on global mean temperature trends evaluated in the HadGEM2-ES climate model. Atmos Sci Lett 15:92–96\nHedemann C, Mauritsen T, Jungclaus J, Marotzke J (2017) The subtle origins of surface-warming hiatuses. Nat Clim Chang 7:336–339\nIPCC (2013) Summary for policymakers. In Climate Change 2013: The physical science basis. Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change\nKarl TR, Arguez A, Huang BY, Lawrimore JH, McMahon JR, Menne MJ, Peterson TC, Vose RS, Zhang HM (2015) Possible artifacts of data biases in the recent global surface warming hiatus. Science 348:1469–1472\nKaufmann RK, Kauppi H, Mann ML, Stock JH (2011) Reconciling anthropogenic climate change with observed temperature 1998-2008. Proc Natl Acad Sci U S A 108:11790–11793\nKendall MG (1955) Rank correlation methods. Charles Griffin, London\nKosaka Y, Xie SP (2013) Recent global-warming hiatus tied to equatorial Pacific surface cooling. Nature 501:403–407\nLi QX, Yang S, Xu WH, Wang XLL, Jones P, Parker D, Zhou LM, Feng Y, Gao Y (2015) China experiencing the recent warming hiatus. Geophys Res Lett 42:889–898\nLiu XD, Cheng ZG, Yan LB, Yin ZY (2009) Elevation dependency of recent and future minimum surface air temperature trends in the Tibetan plateau and its surroundings. Glob Planet Chang 68:164–174\nMann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259\nMauritsen T (2016) Global warming clouds cooled the earth. Nat Geosci 9:865–867\nMears CA, Wentz FJ, Thorne P, Bernie D (2011) Assessing uncertainty in estimates of atmospheric temperature changes from MSU and AMSU using a Monte-Carlo estimation technique. J Geophys Res-Atmos 116:16\nMeehl GA, Arblaster JM, Fasullo JT, Hu AX, Trenberth KE (2011) Model-based evidence of deep-ocean heat uptake during surface-temperature hiatus periods. Nat Clim Chang 1:360–364\nMorice CP, Kennedy JJ, Rayner NA, Jones PD (2012) Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: the HadCRUT4 data set. J Geophys Res-Atmos 117:22\nNaud CM, Miller JR, Landry C (2012) Using satellites to investigate the sensitivity of longwave downward radiation to water vapor at high elevations. J Geophys Res-Atmos 117:12\nPepin N, Bradley RS, Diaz HF, Baraer M, Caceres EB, Forsythe N, Fowler H, Greenwood G, Hashmi MZ, Liu XD, Miller JR, Ning L, Ohmura A, Palazzi E, Rangwala I, Schoner W, Severskiy I, Shahgedanova M, Wang MB, Williamson SN, Yang DQ, Mt Res Initiative EDWWG (2015) Elevation-dependent warming in mountain regions of the world. Nat Clim Chang 5:424–430\nPiao SL, Tan K, Nan HJ, Ciais P, Fang JY, Wang T, Vuichard N, Zhu BA (2012) Impacts of climate and CO2 changes on the vegetation growth and carbon balance of Qinghai-Tibetan grasslands over the past five decades. Glob Planet Chang 98-99:73–80\nQin J, Yang K, Liang SL, Guo XF (2009) The altitudinal dependence of recent rapid warming over the Tibetan plateau. Clim Chang 97:321–327\nRangwala I, Miller JR, Xu M (2009) Warming in the Tibetan plateau: possible influences of the changes in surface water vapor. Geophys Res Lett 36:6\nRangwala I, Miller JR, Russell GL, Xu M (2010) Using a global climate model to evaluate the influences of water vapor, snow cover and atmospheric aerosol on warming in the Tibetan plateau during the twenty-first century. Clim Dyn 34:859–872\nRoerink GJ, Menenti M, Verhoef W (2000) Reconstructing cloudfree NDVI composites using Fourier analysis of time series. Int J Remote Sens 21:1911–1917\nRuckstuhl C, Philipona R, Morland J, Ohmura A (2007) Observed relationship between surface specific humidity, integrated water vapor, and longwave downward radiation at different altitudes. J Geophys Res-Atmos 112:7\nSanter BD, Bonfils C, Painter JF, Zelinka MD, Mears C, Solomon S, Schmidt GA, Fyfe JC, Cole JNS, Nazarenko L, Taylor KE, Wentz FJ (2014) Volcanic contribution to decadal changes in tropospheric temperature. Nat Geosci 7:185–189\nSmith DM, Booth BBB, Dunstone NJ, Eade R, Hermanson L, Jones GS, Scaife AA, Sheen KL, Thompson V (2016) Role of volcanic and anthropogenic aerosols in the recent global surface warming slowdown. Nat Clim Chang 6:936–940\nSolomon S, Rosenlof KH, Portmann RW, Daniel JS, Davis SM, Sanford TJ, Plattner GK (2010) Contributions of stratospheric water vapor to decadal changes in the rate of global warming. Science 327:1219–1223\nSolomon S, Daniel JS, Neely RR, Vernier JP, Dutton EG, Thomason LW (2011) The persistently variable “background” stratospheric aerosol layer and global climate change. Science 333:866–870\nTao J, Zhang YJ, Zhu JT, Jiang YB, Zhang XZ, Zhang T, Xi Y (2014) Elevation-dependent temperature change in the Qinghai-Xizang plateau grassland during the past decade. Theor Appl Climatol 117:61–71\nTian L, Zhang YJ, Zhu JT (2014) Decreased surface albedo driven by denser vegetation on the Tibetan plateau. Environ Res Lett 9:11\nTrenberth KE, Fasullo JT, Branstator G, Phillips AS (2014) Seasonal aspects of the recent pause in surface warming. Nat Clim Chang 4:911–916\nTudoroiu M, Eccel E, Gioli B, Gianelle D, Schume H, Genesio L, Miglietta F (2016) Negative elevation-dependent warming trend in the eastern alps. Environ Res Lett 11:12\nWan ZM, Dozier J (1996) A generalized split-window algorithm for retrieving land-surface temperature from space. IEEE Trans Geosci Remote Sens 34:892–905\nWang XJ, Yang MX, Liang XW, Pang GJ, Wan GN, Chen XL, Luo XQ (2014) The dramatic climate warming in the Qaidam Basin, northeastern Tibetan plateau, during 1961-2010. Int J Climatol 34:1524–1537\nXie YK, Huang JP, Liu YZ (2017) From accelerated warming to warming hiatus in China. Int J Climatol 37:1758–1773\nXu YM, Shen Y, Wu ZY (2013) Spatial and temporal variations of land surface temperature over the Tibetan plateau based on harmonic analysis. Mt Res Dev 33:85–94\nYan LB, Liu ZY, Chen GS, Kutzbach JE, Liu XD (2016) Mechanisms of elevation-dependent warming over the Tibetan plateau in quadrupled CO2 experiments. Clim Chang 135:509–519\nYang XM, Li ZX, Feng Q, He YQ, An WL, Zhang W, Cao WH, Yu TF, Wang YM, Theakstone WH (2012) The decreasing wind speed in southwestern China during 1969-2009, and possible causes. Quat Int 263:71–84\nYang K, Wu H, Qin J, Lin CG, Tang WJ, Chen YY (2014) Recent climate changes over the Tibetan plateau and their impacts on energy and water cycle: a review. Glob Planet Chang 112:79–91\nYou QL, Fraedrich K, Ren GY, Pepin N, Kang SC (2013) Variability of temperature in the Tibetan plateau based on homogenized surface stations and reanalysis data. Int J Climatol 33:1337–1347\nYou QL, Min JZ, Kang SC (2016) Rapid warming in the Tibetan plateau from observations and CMIP5 models in recent decades. Int J Climatol 36:2660–2670\nZeng ZZ, Chen AP, Ciais P, Li Y, Li LZX, Vautard R, Zhou LM, Yang H, Huang MT, Piao SL (2015) Regional air pollution brightening reverses the greenhouse gases induced warming-elevation relationship. Geophys Res Lett 42:4563–4572\nZhang Y, Li B, Zheng D (2002) A discussion on the boundary and area of the Tibetan plateau in China. Geogr Res 21:1–8\nZhang GL, Zhang YJ, Dong JW, Xiao XM (2013) Green-up dates in the Tibetan plateau have continuously advanced from 1982 to 2011. Proc Natl Acad Sci U S A 110:4309–4314\nZhang HB, Zhang F, Ye M, Che T, Zhang GQ (2016a) Estimating daily air temperatures over the Tibetan plateau by dynamically integrating MODIS LST data. J Geophys Res-Atmos 121:11425–11441\nZhang HB, Zhang F, Zhang GQ, He XB, Tian LD (2016b) Evaluation of cloud effects on air temperature estimation using MODIS LST based on ground measurements over the Tibetan plateau. Atmos Chem Phys 16:13681–13696\nZhong L, Su ZB, Ma YM, Salama MS, Sobrino JA (2011) Accelerated changes of environmental conditions on the Tibetan plateau caused by climate change. J Clim 24:6540–6550\nZhou LM, Dickinson RE, Tian YH, Vose RS, Dai YJ (2007) Impact of vegetation removal and soil aridation on diurnal temperature range in a semiarid region: application to the Sahel. Proc Natl Acad Sci U S A 104:17937–17942",{"VOID":1961},"10.1007\u002Fs00704-018-2435-3","2024-06-25T09:41:31.352+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs00704-018-2435-3",[1965,1990,2019,2032,2052,2072,2092,2105],{"id":1966,"sortIndex":21,"researcher":20,"roles":1967,"affiliations":1968,"properties":1985,"displayName":1987,"givenName":20,"familyName":20},"35d7b3ef-52d5-42fa-ad56-86700a2e948c",[283],[1969,1977],{"id":1970,"sortIndex":21,"affiliation":1971,"properties":20},"d0c7417f-9b54-4e37-acae-b0f56b3a3dfd",{"id":1970,"createTime":20,"updateTime":20,"relativeEntities":1972,"slug":20,"properties":1973,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1976,"statistic":20},[],{"title":1974},{"VI":1975},"Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China",[],{"id":1978,"sortIndex":149,"affiliation":1979,"properties":20},"e5bf0683-9fbd-4a9a-817f-154ff9eaadb5",{"id":1978,"createTime":20,"updateTime":20,"relativeEntities":1980,"slug":20,"properties":1981,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1984,"statistic":20},[],{"title":1982},{"VI":1983},"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China",[],{"title":1986,"gsAuthor":1988},{"VI":1987},"Yaojie Liu",{"VOID":1989},"[\"2y8KcCsAAAAJ\"]",{"id":1991,"sortIndex":149,"researcher":20,"roles":1992,"affiliations":1993,"properties":2014,"displayName":2016,"givenName":20,"familyName":20},"0bf91585-b72a-46b0-8679-f1e7cf7b5408",[283],[1994,2000,2006],{"id":1970,"sortIndex":21,"affiliation":1995,"properties":20},{"id":1970,"createTime":20,"updateTime":20,"relativeEntities":1996,"slug":20,"properties":1997,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1999,"statistic":20},[],{"title":1998},{"VI":1975},[],{"id":1978,"sortIndex":149,"affiliation":2001,"properties":20},{"id":1978,"createTime":20,"updateTime":20,"relativeEntities":2002,"slug":20,"properties":2003,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2005,"statistic":20},[],{"title":2004},{"VI":1983},[],{"id":2007,"sortIndex":153,"affiliation":2008,"properties":20},"9d7e4762-5f9b-4d17-9f41-45055ee74151",{"id":2007,"createTime":20,"updateTime":20,"relativeEntities":2009,"slug":20,"properties":2010,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2013,"statistic":20},[],{"title":2011},{"VI":2012},"Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing, China",[],{"title":2015,"gsAuthor":2017},{"VI":2016},"Yangjian Zhang",{"VOID":2018},"[\"Y7SMxNoAAAAJ\"]",{"id":2020,"sortIndex":153,"researcher":20,"roles":2021,"affiliations":2022,"properties":2029,"displayName":2031,"givenName":20,"familyName":20},"fb2a5754-0a4f-44ec-a3a9-a4af4c3c27ba",[283],[2023],{"id":1970,"sortIndex":21,"affiliation":2024,"properties":20},{"id":1970,"createTime":20,"updateTime":20,"relativeEntities":2025,"slug":20,"properties":2026,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2028,"statistic":20},[],{"title":2027},{"VI":1975},[],{"title":2030},{"VI":2031},"Juntao Zhu",{"id":2033,"sortIndex":643,"researcher":20,"roles":2034,"affiliations":2035,"properties":2049,"displayName":2051,"givenName":20,"familyName":20},"129941be-1403-42be-bca3-06ba258144a6",[283],[2036,2042],{"id":1970,"sortIndex":21,"affiliation":2037,"properties":20},{"id":1970,"createTime":20,"updateTime":20,"relativeEntities":2038,"slug":20,"properties":2039,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2041,"statistic":20},[],{"title":2040},{"VI":1975},[],{"id":1978,"sortIndex":149,"affiliation":2043,"properties":2048},{"id":1978,"createTime":20,"updateTime":20,"relativeEntities":2044,"slug":20,"properties":2045,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2047,"statistic":20},[],{"title":2046},{"VI":1983},[],{},{"title":2050},{"VI":2051},"Ke Huang",{"id":2053,"sortIndex":159,"researcher":20,"roles":2054,"affiliations":2055,"properties":2069,"displayName":2071,"givenName":20,"familyName":20},"e23c8906-e993-40f8-9d2c-d87bb837d9b0",[283],[2056,2062],{"id":1970,"sortIndex":21,"affiliation":2057,"properties":20},{"id":1970,"createTime":20,"updateTime":20,"relativeEntities":2058,"slug":20,"properties":2059,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2061,"statistic":20},[],{"title":2060},{"VI":1975},[],{"id":1978,"sortIndex":149,"affiliation":2063,"properties":2068},{"id":1978,"createTime":20,"updateTime":20,"relativeEntities":2064,"slug":20,"properties":2065,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2067,"statistic":20},[],{"title":2066},{"VI":1983},[],{},{"title":2070},{"VI":2071},"Jiaxing Zu",{"id":2073,"sortIndex":97,"researcher":20,"roles":2074,"affiliations":2075,"properties":2089,"displayName":2091,"givenName":20,"familyName":20},"e65943d4-d481-4620-8319-7e7efe38c457",[283],[2076,2082],{"id":1970,"sortIndex":21,"affiliation":2077,"properties":20},{"id":1970,"createTime":20,"updateTime":20,"relativeEntities":2078,"slug":20,"properties":2079,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2081,"statistic":20},[],{"title":2080},{"VI":1975},[],{"id":1978,"sortIndex":149,"affiliation":2083,"properties":2088},{"id":1978,"createTime":20,"updateTime":20,"relativeEntities":2084,"slug":20,"properties":2085,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2087,"statistic":20},[],{"title":2086},{"VI":1983},[],{},{"title":2090},{"VI":2091},"Ning Chen",{"id":2093,"sortIndex":151,"researcher":20,"roles":2094,"affiliations":2095,"properties":2102,"displayName":2104,"givenName":20,"familyName":20},"712da9c5-fec5-4a67-92e7-0e38adc2be4d",[283],[2096],{"id":1970,"sortIndex":21,"affiliation":2097,"properties":20},{"id":1970,"createTime":20,"updateTime":20,"relativeEntities":2098,"slug":20,"properties":2099,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2101,"statistic":20},[],{"title":2100},{"VI":1975},[],{"title":2103},{"VI":2104},"Nan Cong",{"id":2106,"sortIndex":156,"researcher":20,"roles":2107,"affiliations":2108,"properties":2117,"displayName":2119,"givenName":20,"familyName":20},"5e29bd7b-facb-4ffe-b1a5-4d092566fbd6",[283],[2109],{"id":2110,"sortIndex":21,"affiliation":2111,"properties":20},"3fc75e53-5808-4b63-a113-fe82db63c60f",{"id":2110,"createTime":20,"updateTime":20,"relativeEntities":2112,"slug":20,"properties":2113,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2116,"statistic":20},[],{"title":2114},{"VI":2115},"Shenzhen Key Laboratory of Circular Economy, School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen, China",[],{"title":2118},{"VI":2119},"Annemiek Irene Stegehuis",{"url":1963,"publisher":2121,"properties":2163},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":2122,"slug":10,"properties":2123,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":2127,"manageAffiliations":2132,"indexDatabases":2143,"url":20,"thumbnailPath":20,"statistic":2158,"gsStatistic":20,"type":20,"analyzePriority":20},[],{"issn":2124,"title":2125,"eissn":2126},{"VOID":13},{"EN":15},{"VOID":17},[2128],{"id":24,"createTime":20,"updateTime":20,"relativeEntities":2129,"label":2130,"description":2131,"parentId":20,"standard":20,"scholarHubFieldId":20},[],{"EN":27},{},[2133,2138],{"id":31,"createTime":20,"updateTime":20,"relativeEntities":2134,"slug":20,"properties":2135,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2137,"statistic":20},[],{"title":2136},{"EN":35},[37],{"id":39,"createTime":20,"updateTime":20,"relativeEntities":2139,"slug":20,"properties":2140,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":2142,"statistic":20},[],{"title":2141},{"EN":43},[37],[2144,2151],{"id":47,"indexDatabase":2145,"url":58,"indexYears":59,"academicFieldIds":2150,"indexDatabaseRanking":62},{"id":49,"createTime":20,"updateTime":20,"relativeEntities":2146,"label":2147,"description":2148,"key":55,"publicationTags":2149,"standard":20},[],{"EN":52,"VI":52},{"EN":52,"VI":54},[57],[61],{"id":64,"indexDatabase":2152,"url":77,"indexYears":20,"academicFieldIds":2157,"indexDatabaseRanking":20},{"id":66,"createTime":20,"updateTime":20,"relativeEntities":2153,"label":2154,"description":2155,"key":73,"publicationTags":2156,"standard":20},[],{"EN":69,"VI":69},{"EN":71,"VI":72},[75,76],[79],{"impactFactor":21,"impactFactorByYear":2159,"i10Index":93,"i10IndexLast5Year":94,"totalPublication":95,"totalPublicationByYear":2160,"totalCitation":147,"totalCitationByYear":2161,"totalCitationPerPublication":192,"totalCitationPerPublicationByYear":2162,"hindexLast5Year":130,"hindex":130},{"2012":82,"2013":83,"2014":84,"2015":85,"2016":86,"2017":87,"2018":84,"2019":88,"2020":89,"2021":90,"2022":91,"2023":92},{"1948":97,"1949":98,"1950":99,"1951":100,"1952":101,"1953":102,"1954":103,"1955":104,"1956":105,"1957":106,"1958":107,"1959":108,"1960":109,"1961":110,"1962":111,"1963":105,"1964":108,"1965":112,"1966":97,"1967":111,"1968":102,"1969":112,"1970":109,"1971":104,"1972":109,"1973":113,"1974":105,"1975":107,"1976":113,"1977":113,"1978":114,"1979":113,"1980":115,"1981":111,"1982":116,"1983":114,"1984":115,"1985":99,"1986":104,"1987":102,"1988":110,"1989":117,"1990":118,"1991":116,"1992":119,"1993":120,"1994":121,"1995":122,"1996":123,"1997":124,"1998":125,"1999":126,"2000":119,"2001":119,"2002":127,"2003":125,"2004":128,"2005":129,"2006":130,"2007":128,"2008":131,"2009":94,"2010":132,"2011":133,"2012":134,"2013":135,"2014":136,"2015":137,"2016":138,"2017":139,"2018":140,"2019":141,"2020":142,"2021":143,"2022":144,"2023":145,"2024":146},{"1948":149,"1949":149,"1951":114,"1952":108,"1953":107,"1954":150,"1955":105,"1956":101,"1957":113,"1958":97,"1959":99,"1960":151,"1961":101,"1962":152,"1964":153,"1965":111,"1967":125,"1968":100,"1969":127,"1970":119,"1971":104,"1972":107,"1973":125,"1974":154,"1975":102,"1976":155,"1977":156,"1978":157,"1979":158,"1980":151,"1986":120,"1987":151,"1988":159,"1989":119,"1990":160,"1991":98,"1992":161,"1993":162,"1994":163,"1995":164,"1996":165,"1997":166,"1998":167,"1999":94,"2000":168,"2001":169,"2002":170,"2003":171,"2004":172,"2005":173,"2006":174,"2007":175,"2008":176,"2009":177,"2010":178,"2011":179,"2012":180,"2013":181,"2014":182,"2015":183,"2016":184,"2017":185,"2018":186,"2019":187,"2020":188,"2021":189,"2022":190,"2023":191,"2024":108},{"1948":194,"1949":195,"1951":196,"1952":197,"1953":198,"1954":199,"1955":197,"1956":200,"1957":201,"1958":202,"1959":203,"1960":86,"1961":204,"1962":205,"1964":206,"1965":207,"1967":208,"1968":209,"1969":210,"1970":211,"1971":149,"1972":212,"1973":213,"1974":214,"1975":89,"1976":215,"1977":87,"1978":199,"1979":198,"1980":216,"1986":217,"1987":87,"1988":218,"1989":219,"1990":220,"1991":221,"1992":222,"1993":223,"1994":224,"1995":225,"1996":226,"1997":227,"1998":228,"1999":229,"2000":230,"2001":231,"2002":232,"2003":233,"2004":234,"2005":235,"2006":236,"2007":237,"2008":238,"2009":239,"2010":240,"2011":241,"2012":242,"2013":243,"2014":244,"2015":245,"2016":246,"2017":247,"2018":248,"2019":249,"2020":250,"2021":251,"2022":252,"2023":253,"2024":254},{"pages":2164,"volume":2166},{"VOID":2165},"1375-1385",{"VOID":2167},"135",{"total":150,"publishYear":2169,"statisticByYear":2170},2018,{"2019":149,"2021":643,"2022":149,"2023":149,"2025":149,"2026":153},"2018-03-10","DONE_ANALYZE_CITATION","2026-07-23T11:19:21.021+00:00",[62,75]]