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This work calculates the current heating and cooling degree days and also examines heating and cooling degree days in relation to three subdivisions of the twenty-first century. On the basis of these data, we were able to calculate the heating and cooling degree months and degree years. After examining both sets of data, we studied the total needs of air conditioning—also referred to in the current paper as climatization needs——for Andalusia as a whole. The results indicate an increase in air conditioning needs, and we also noted that the areas adversely affected by this increase were more numerous than those which benefited, at the end of the century. It should be noted that climate change will also necessitate the gradual replacement of heating with cooling, which will require profound changes in the energy, land planning, and housing policies of the region. The true magnitude of the challenge becomes clear when the climatization degree days are related to the population which they affect; the majority of the population is located in areas where the climatization needs will increase over the course of the century. Undoubtedly, this issue is a major protagonist in the climate change adaptation process in Andalusia.

A simple model for the determination of SO2 emission potential (the permissible emission) in basins is presented. Some Slovenian basins have been chosen to indicate the time increase of SO2 concentrations in the dependence of decay, the emission and relief conditions of basins, and also to indicate the influence of the permissible concentration level on the emission potential.

In order to quantify the impact of the use of different parameterization schemes on regional climate model outputs, hindcast experiments have been completed applying the Regional Climate Model version 4.3 (RegCM4.3) for the Carpathian region and its surroundings at 10-km horizontal resolution with three different cumulus convection schemes. Besides, the sensitivity of outputs for subgrid-scale processes is also studied by activating the subgrid Biosphere-Atmosphere Transfer Scheme (BATS) model within other RegCM experiments. Among the analyzed factors, RegCM is most sensitive to the applied convection scheme. The impact of closure assumption related to the used convective parameterization is secondary, while the use of subgridding has less influence on the outputs. RegCM4.3 results show improved performance over our previous model simulations but still have larger amplitude for annual precipitation cycle than the measurement-based reference data. Our validation results for temperature and precipitation suggest that for the selected region, the overall best performance is achieved when using the mixed Grell-Emanuel scheme together with Fritsch and Chappell closure.

Under the background of global warming, precipitation extremes are the main reasons for the cause of drought-flood disasters at local scales. Regional evaluations on the spatial and temporal variations of precipitation extremes are needed for comprehensively understanding the precipitation-related natural disasters. In this study, ten extreme precipitation indices from 17 meteorological stations in the Hanjiang River Basin, China, were computed and their spatial and temporal variations were analyzed using linear tendency method, based on daily precipitation data for the period of 1960–2015. Results indicated that consecutive dry days, number of heaviest  precipitation days, maximum 1-day precipitation, very wet day precipitation, extremely wet day precipitation, and simple precipitation intensity index exhibited non-significant increasing trends. Consecutive wet days, number of heavy  precipitation days, maximum 5-day precipitation, and total wet day precipitation exhibited non-significant decreasing trends. Using Mann-Kendall test, cumulative anomaly method, and moving t test for cross-validation, an abrupt increase was detected in 1978 for both very wet day precipitation and extremely wet day precipitation and for both these two indices, there were two significant periodic variation cycles, i.e., 1–2 years and 4 years, and in addition, extremely wet day precipitation had a change cycle of 8 years. The cross-wavelet transform method suggested that Pacific Decadal Oscillations and Sea Surface Temperature might be the two driving factors of extreme precipitation variation. The changing trends of precipitation extremes showed regional differences, but the stations with significant trends were not clustered. All the indices were highly correlated with each other, except for the number of consecutive dry days and consecutive wet days. The contribution of extreme precipitation to total precipitation revealed a non-significant increase in the study area. There were negative correlations between most of the indices and elevation with high level of significance. Changes of large-scale atmospheric circulation showed an increasing geopotential height and a weakened summer monsoon and had an impact on the variations of extreme precipitation.

An algorithm for estimating rainfall (based upon scattering of upwelling radiation at 85 GHz) using the Special Sensor Microwave Imager (SSM/I) 85 GHz sensor data has recently been developed at the National Oceanographic and Atmospheric Administration's Office of Research and Applications (NOAA ORA). Spatial and temporal variability in the differences between simple areal-averaged rainfall estimates from a raingage and satellite-derived estimates are examined. These initial comparisons provide insight into the nature of the differences; however, due to substantial amounts of spatial sampling error in the raingage spatial averages, this approach is ineffective at identifying statistically significant differences. Thus, rainfall estimates for this algorithm are examined over the tropical Pacific using a statistical technique, called the “noncontiguous raingage method” (NCR), which minimizes spatial sampling error so that the statistical significance of relationships may be determined. The results indicate that, adjusted with calibration coefficients, the ORA algorithm could produce unbiased estimates of areal rainfall for the tropical Pacific region examined in this study.

When modelling mesoscale effects in the coastal climate we have to account for the significant influence of humidity and for the land-sea contrast which is represented by the roughness lengthz 0 =z 0(x, y) and the heat capacityC 0 =C 0 (x, y). This brings about strong horizontal inhomogenities which affect the meteorological situation significantly. The effects of these inhomogenities on the structure and variation of the boundary layer in the coastal region are studied by use of a three-dimensional numerical model; the formation process of advective fog in connection with different geostrophic winds is also investigated. As main results we present 1) the modifications of wind velocity and wind direction as a function of the roughness distribution and different thermal stratifications and 2) two simulations of advective fog formation assuming different geostrophic wind values in each example.

The urban heat island (UHI) of the city of Bucharest (Romania) is analyzed in terms of its extension, geometry, and magnitude using the surface thermal data provided by the moderate resolution imaging spectroradiometer (MODIS) sensors. An objective method is developed that allows to delineate the UHI. The study focuses on the months of July from the 2000–2006 time interval. The average surface temperatures obtained for each pixel (1 km resolution) were analyzed on cross-profiles that helped us to determine the outline of the UHI. The shifting points identified by the Rodionov test in the temperature series of each profile were considered as possible limits of the UHI. Seemingly, the land cover has a major influence on the extension and the geometry of the Bucharest UHI in July. The magnitude of the heat island was calculated by comparing the average temperature inside its limits and the average temperature of the 5 km (a) and of the 10 km (b) buffers around it. The thermal difference between the UHI and the surrounding area of Bucharest is higher and more variable during the daytime, and is noticeably related to the land cover.

The present paper aims to compute climatological zones apt for the cultivation of pitaya based on trends in the occurrence of climate change events from the IPCC (Intergovernmental Panels on Climate Change) in Brazil. We used temperature and precipitation data from 4942 cities collected on the NASA/POWER platform (National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources) from 1990 to 2020 to elaborate on the current scenario. The climate change scenarios were obtained using the CHELSA platform (Climatologies at high resolution for the earth’s land surface areas) and corresponded to the periods 2041–2060 and 2061–2080 associated with four IPCC climate change scenarios. The spatialization of the data occurred according to the bioclimatic classes designed to meet the thermal and water needs of the crop. In the current scenario, class B5 has a predominance of 37.07% of the country, characterizing the Midwest, Southeast, and Northeast regions, as well as the state of Paraná, as suitable for the cultivation of pitaya. Projections of temperature increase and reduction of accumulated rainfall were found throughout Brazil, but with greater impact in the North and Northeast regions, which had the greatest reduction of areas suitable for the cultivation of pitaya with a greater predominance of classes B8 and B9. In the South and Southeast regions, class B5 makes up a large part of the areas that remained suitable for the production of this fruit until 2080. The results suggest that climate change does not benefit the cultivation of pitaya in some regions of Brazil because the dimensions of the areas suitable for economic production are restricted.