Spatial interpolation of monthly climate data for Finland: comparing the performance of kriging and generalized additive models

Springer Science and Business Media LLC - Tập 112 Số 1-2 - Trang 99-111 - 2013
Juha Aalto1, Pentti Pirinen1, Juha Heikkinen2, Ari Venäläinen1
1Finnish Meteorological Institute, Helsinki, Finland
2Finnish Forest Research Institute – Metla, Vantaa, Finland

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Adam J, Clark E, Lettenmaier D, Wood E (2006) Correction of global precipitation products for orographic effects. J Climate 19:15–38

Araújo M, Luoto M (2007) The importance of biotic interactions for modeling species distribution under climate change. Glob Ecol Biogeogr 16:743–753

Barnett T, Zwiers F, Hegerl G, Allen M, Crowley T, Gillett N, Hasselmann K, Jones P, Santer B, Schcnur P, Stott K, Taylor K, Tett S (2005) Detecting and attributing external influences on the climate system: a review of recent advances. J Climate 27:1291–1314

Bivand R, Pebesma E, Còmez-Rubio V (2008) Applied spatial data analysis with R. Springer, New York

Brown D, Goovaerts P, Burnicki A, Li MY (2002) Stochastic simulation of land-cover change using geostatistics and generalized additive models. Photogramm Eng Remote Sensing 68(10):1051–1061

Brus D, Heuvelink G (2007) Optimization of sample patterns for universal kriging of environmental variables. Geoderma 138:86–95

Chorley R, Haggett P (1965) Trend-surface mapping in geographical research. Trans Inst Br Geogr 37:47–67

Clifton P, Neuman S (1982) Effects of kriging and inverse modeling on conditional simulation of the Avra Valley aquifer in souther Arizona. Water Resour Res 18(4):1215–1234

Cressie N (1990) The origins of kriging. Math Geol 22(3):239–252

Daly C (2006) Guidelines for assessing the suitability of spatial climate data sets. Int J Climatol 26:707–721

Drebs A, Nordlund A, Karlsson P, Helminen J, Rissanen P (2002) Climatological statistics of Finland 1971–2000. Climatological Statistics of Finland 2001. Finnish Meteorological Institute, Helsinki

Fronzek S, Luoto M, Carter T (2006) Potential effect of climate change on the distribution of palsa mires in subarctic Fennoscandia. Clim Res 32:1–12

Ginsbourger D, Dupuy D, Badea A, Carraro L, Roustant O (2009) A note on the choice and the estimation of kriging models for the analysis of deterministic computer experiments. Appl Stoch Models Bus Ind 25(2):115–131

Goovaerts P (1997) Geostatistics for natural resources evaluation. Applied Geostatistics Series, Oxford University Press

Goovaerts P (1998) Ordinary cokriging revisited. Math Geol 30(1):21–42

Goovaerts P (1999) Geostatistics in soil science: state-of-the-art and perspectives. Geoderma 89:1–45

Goovaerts P (2000) Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. J Hydrol 228:113–129

Guisan A, Edwards T, Hastie T (2002) Generalized linear and generalized additive models in studies of species distributions: setting the scene. Ecol Model 157:89–100

Hastie T, Tibshirani R (1984) Generalized additive models. Technical report lcm02, Dept. of Statistics

Hastie T, Tibshirani R (1990) Generalized additive models, monographs on statistics and applied probability, vol 43. Chapman and Hall, New York

Hengl T, Heuvelink G, Stein A (2003) Comparison of kriging with external drift and regression-kriging. Technical note, ITC

Hengl T, Heuvelink G, Stein A (2004) A generic framework for spatial prediction of soil variables based on regression-kriging. Geoderma 120:75–93

Hengl T, Heuvelink G, Tadić M, Pebesma E (2012) Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images. Theor Appl Climatol 107:265–277

Hjort J, Luoto M (2010) Novel theoretical insights into geomorphic process-environment relationships using simulated response curves. Earth Surf Processes Landf 36(3):363–371

Hofstra N, Haylock M, New M, Jones P, Frei C (2008) Comparison of six methods for the interpolation of daily, European climate data. J Geophys Res 113:D21,110

Holdaway M (1996) Spatial modelling and interpolation of monthly temperature using kriging. Clim Res 6:215–225

Hong Y, Nix H, Hutchinson M, Booth T (2005) Spatial interpolation of monthly mean climate data for China. Int J Climatol 25:1369–1379

Høst G (1999) Kriging by local polynomials. Comput Stat Data Anal 29:295–312

Hutchinson M (1998) Interpolation of rainfall data with thin plate smoothing. J Geogr Inf Decis Anal 2(2):139–151

Journel A, Rossi M (1989) When do we need a trend model in kriging? Math Geol 21(7):715–739

Jylha K, Tuomenvirta H, Ruosteenoja K (2004) Climate change projections for Finland during the 21st century. Boreal Environ Res (9):127–152

Kammann E, Wand M (2003) Geoadditive models. JR Stat Soc 52(1):1–18

Kneib T, Hothorn T, Tutz G (2009) Variable selection and model choice in geoadditive regression models. Biometrics 65(2):626–634

Kullmann L (2010) A richer, Greener and Smaller Alpine world: review and projection of warming-induced plant cover change in the Swedish Scandes. Ambio 39:159–169

Laslett G (1994) Kriging and splines: an empirical comparison of their predictive performance in some applications. J Am Stat Assoc 89(426):391–400

Leathwick J, Elith J, Hastie T (2006) Comparative performance of generalized additive models and multivariate adaptive regression splines for statistical modeling of species distributions. Ecol Model 199:188–196

Legendre P (1993) Spatial autocorrelation: trouble or new paradigm? Ecology 74:1659–1673

Lin G, Chen L (2004) A spatial interpolation method based on radial basis function networks incorporating a semivariogram model. J Hydrol 288:288–298

Liu TL, Juang KW, Lee DY (2006) Interpolating soil properties using kriging combined with categorical information of soil maps. Soil Sci Soc Am J 70(4):1200–1209

Lu G, Wong D (2008) An adaptive inverse-distance weighting spatial interpolation technique. Comput Geosci 34(9):1044–1055

Matheron G (1963) Principles of geostatistics. Econ Geol 58:1246–1266

McCullagh P, Nelder J (1989) Generalized linear models, monographs on statistics and applied probability, vol 37, 2nd edn. Chapman and Hall, New York

Miller J, Franklin J (2002) Modeling the distribution of four vegetation alliances using generalized linear models and classification trees with spatial dependence. Ecol Model 157:227–247

National Land Survey of Finland (2011) Terrain database. http://www.usc.fi/tutkimus/alat/geotieteet/paikkatieto/paituli

Pebesma E (2004) Multivariable geostatistics in S: the gstat package. Comput Geosci 30:683–691

Perry M, Hollis D (2005) The generation of monthly gridded datasets for a range of climatic variables over the UK. Int J Climatol 25:1041–1054

Price D, McKenney D, Nalder I, Hutchinson, Kesteven J (2000) A comparison of two statistical methods for spatial interpolation of Canadian monthly mean climate data. Agric For Meteorol 101:81–94

R Development Core Team (2011) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org , ISBN 3-900051-07-0

Rizzo D, Dougherty D (1994) Characterization of aquifer properties using artificial neural networks: neural kriging. Water Resour Res 30(2):483–497

Robertson G (1987) Geostatistics in ecology: interpolating with known variance. Ecology 68(3):744–748

Rolland C (2002) Spatial and seasonal variations of air temperature lapse rates in Alpine regions. J Climate 16:1032–1046

Solantie R (1976) The influences of lakes on meso-scale analysis of temperature in Finland. Ilmatieteen laitoksen tiedonantoja 30, p 130 (in Finnish)

Tikkanen M (2005) Climate. In: Seppälä M (ed) The physical geography of Fennoscandia. Oxford University Press

Vajda A, Venäläinen A (2003) The influence of natural conditions on the spatial variation of climate in Lapland, northern Finland. Int J Climatol 23:1011–1022

Vicente-Serrano S, Saz-Sánchez M, Cuadrat J (2003) Comparative analysis of interpolation methods on the middle Ebro Valley (Spain): application to annual precipitation and temperature. Clim Res 24:161–180

Voltz M, Webster R (1990) A comparison of kriging, cubic splines and classification for predicting soil properties from sample information. J Soil Sci 41(3):473–490

Walter C, McBratney A, Douaoui A, Minasny B (2001) Spatial prediction of topsoil salinity in the Chelif Valley, Algeria, using local ordinary kriging with local variograms versus whole-area variogram. Aust J Soil Res 39(2):259–272

Wilmott C (1982) Some comments on the evaluation of model permormance. Bull Am Meteorol Soc 63(11):1309–1313

Wood S (2004) Stable and efficient multiple smoothing parameter estimation for generalized additive models. J Am Stat Assoc 99:673–686

Wood S (2006) Generalized additive models: an introduction with R. Chapman & Hall, London

Wood S (2011) Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J R Stat Soc 73(1):3–36

Wood S, Augustin N (2002) GAMs with integrated model selection using penalized regression splines and applications to environmental modeling. Ecol Model 157:157–177

Yee T, Mitchell N (1991) Generalized additive models in plant ecology. J Veg Sci 2:587–602