Nonstationary models for exploring and mapping monthly precipitation in the United kingdom

International Journal of Climatology

Volumn 30, Issue 3, 2010, Pages 390-405

  Lloyd, C D ^a  

^a QUEEN'S UNIVERSITY BELFAST   (United Kingdom)

Author keywords

Geographically weighted regression; Kriging; Moving window regression; Nonstationarity; Precipitation

Indexed keywords

ACCURATE PREDICTION; CROSS VALIDATION; ELEVATION DATA; ENVIRONMENTAL VARIABLES; GENERALIZED LEAST SQUARE; GEOGRAPHICALLY WEIGHTED REGRESSION; INVERSE DISTANCE WEIGHTING; KEY ISSUES; KRIGING WITH AN EXTERNAL DRIFT; LOCAL MEAN; LOCAL VARIATIONS; MOVING WINDOW; MOVING WINDOW REGRESSIONS; NON-STATIONARITIES; NON-STATIONARY MODEL; ORDINARY KRIGING; ORDINARY LEAST SQUARES; PREDICTION ERRORS; PREDICTION PROCESS; REGION OF INTEREST; RESEARCH EFFORTS; SIMPLE KRIGING; SMALL REDUCTION; SPATIAL INTERPOLATION; SPATIAL PREDICTION; SPATIAL STRUCTURE; SPATIAL VARIATIONS; STATIONARITY; STATISTICAL ALGORITHM; UNITED KINGDOM; UNIVARIATE; VARIOGRAM MODELS; VARIOGRAMS;

ERRORS; MAPPING; PASSENGER CARS; WINDOWS;

REGRESSION ANALYSIS;

ALGORITHM; INTERPOLATION; KRIGING; MAPPING METHOD; MODELING; PRECIPITATION ASSESSMENT; PREDICTION; REGRESSION ANALYSIS; SPATIAL VARIATION; VARIOGRAM;

UNITED KINGDOM;

EID: 76849091165     PISSN: 08998418     EISSN: 10970088     Source Type: Journal    
DOI: 10.1002/joc.1892     Document Type: Article

References (50)

1. Armstrong M. 1998. Basic Linear Geostatistics. Springer: Berlin.
2. Barrow E, Hulme M. 1997. Describing the surface climate of the British Isles. In Climates of the British Isles: Present, Past and Future, Hume M, Barrow E (eds). Longman: London; 33-62
3. Bastin G, Lorent B, Duque C, Gevers M. 1984. Optimal estimation of the average rainfall and optimal selection of raingauge locations. Water Resources Research 20: 463-470.
4. Brunsdon C, McClatchey J, Unwin DJ. 2001. Spatial variations in the average rainfall-altitude relationship in Great Britain: an approach using geographically weighted regression. International Journal of Climatology 21: 455-466.
5. Burrough PA, McDonnell RA. 1998. Principles of Geographical Information Systems. Oxford University Press: Oxford.
6. Chilès J-P, Delfiner P. 1999. Geostatistics: Modeling Uncertainty. Wiley: New York.
7. Cressie NAC. 1993. Statistics for Spatial Data, Revised edition. Wiley: New York.
8. Creutin JD, Delrieu G, Lebel T. 1988. Rain measurement by raingageradar combination: a geostatistical approach. Journal of Atmospheric and Oceanic Technology 5: 102-115.
9. Daly C, Neilson RP, Phillips DL. 1994. A statistical-topographic model for mapping climatological precipitation over mountainous terrain. Journal of Applied Meteorology 33: 140-158
10. Deraisme J, Humbert J, Drogue G, Freslon N. 2001. Geostatistical interpolation of rainfall in mountainous areas. In GeoENV III: Geostatistics for Environmental Applications, Monestiez P Allard D, Froidevaux R (eds). Kluwer Academic Publishers: Dordrecht; 57-66.
11. Deutsch CV, Journel AG. 1998. GSLIB: Geostatistical Software and User's Guide, 2nd edn. Oxford University Press: New York
12. Fotheringham AS, Brunsdon C, Charlton M. 2002. Geographically Weighted Regression: The Analysis of Spatially Varying Relation- ships. Wiley: Chichester.
13. Gòmez-Hernàndez J, Cassiraga E, Guardiola-Albert C, Álvarez Rodríguez J. 2001. Incorporating information from a digital elevation model for improving the areal estimation of rainfall. In GeoENV III: Geostatistics for Environmental Applications, Monestiez P Allard D, Froidevaux R (eds). Kluwer Academic Publishers: Dordrecht; 67-78.
14. Goovaerts P. 1997. Geostatistics for Natural Resources Evaluation. Oxford University Press: New York.
15. Goovaerts P. 2000. Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology 228: 113-129.
16. Haas TC. 1990. Lognormal and moving window methods of estimating acid deposition. Journal of the American Statistical Association 85: 950-963.
17. Hancock PA, Hutchinson MF. 2006. Spatial interpolation of large climate data sets using bivariate thin plate smoothing splines. Environmental Modelling and Software 21: 1684-1694.
18. Hay L, Viger R, McCabe G. 1998. Precipitation interpolation in mountainous regions using multiple linear regression. In Hydrology, Water Resources and Ecology in Headwaters. Proceedings of the Headwater 1998 Conference, April 1998, Mean/Merano; Italy,
19. Kovar K, Tappeiner U, Peters NE, Craig RG (eds). International Association of Hydrological Sciences Publication 248: Wallingford, UK.
20. Hengl T. 2007. A Practical Guide to Geostatistical Mapping of Environmental Variables. Office for Official Publications of the European Communities: Luxembourg.
21. Hengl T, Heuvelink GBM, Rossiter DG. 2007. About regression-kriging: From equations to case studies. Computers and Geosciences 33: 1301-1315.
22. Hevesi JA, Istok JD, Flint AL. 1992a. Precipitation estimation in mountainous terrain using multivariate geostatistics. Part I: structural analysis. Journal of Applied Meteorology 31: 661-676
23. Hevesi JA, Flint AL, Istok JD. 1992b. Precipitation estimation in mountainous terrain using multivariate geostatistics. Part II: isohyetal maps. Journal of Applied Meteorology 31: 677-688
24. Hofierka J, Parajka J, Mitasova M, Mitas L. 2002. Multivariate interpolation of precipitation using regularized spline with tension. Transactions in GIS 6: 135-150.
25. Hutchinson MF. 1995. Interpolating mean rainfall using thin-plate smoothing splines. International Journal of Geographical Information Systems 9: 385-403.
26. Hutchinson MF. 1998a. Interpolation of rainfall data with thin plate smoothing splines - Part I: Two dimensional smoothing of data with short range correlation. Journal of Geographic Information and Decision Analysis 2: 139-151 http://www.geodec.org/gida4.htm
27. Hutchinson MF. 1998b. Interpolation of rainfall data with thin plate smoothing splines - Part II: Analysis of topographic dependence. Journal of Geographic Information and Decision Analysis 2: 152-167. http://www.geodec.org/gida.4.htm.
28. Isaaks EH, Srivastava RM. 1989. An Introduction to Applied Geostatistics. Oxford University Press: New York.
29. Jian X, Olea RA, Yu Y-S. 1996. Semivariogram modeling by weighted least squares. Computers and Geosciences 22: 387-397
30. Journel AG, Huijbregts CJ. 1978. Mining Geostatistics. Academic Press: London.
31. Kitanidis PK. 1997. Introduction to Geostatistics: Applications in Hydrogeology. Cambridge University Press: Cambridge.
32. Lloyd CD. 2002. Increasing the accuracy of predictions of monthly precipitation in Great Britain using kriging with an external drift. In Uncertainty in Remote Sensing and GIS, Foody GM, Atkinson PM (eds). Wiley: Chichester; 243-267.
33. Lloyd CD. 2005. Assessing the effect of integrating elevation data into the estimation of monthly precipitation in Great Britain. Journal of Hydrology 308: 128-150.
34. Lloyd CD. 2006. Local Models for Spatial Analysis. CRC Press: Boca Raton.
35. Lloyd CD. 2009. Multivariate interpolation of monthly precipitation amount in the United Kingdom. In Geostatistics for Environmental Applications: Proceedings of the Seventh European Conference on Geostatistics for Environmental Applications, Atkinson PM, Lloyd CD (eds). Springer: Berlin. (in press).
36. Lloyd CD, Atkinson PM. 2002. Deriving DSMs from LiDAR data with kriging. International Journal of Remote Sensing 23: 2519-2524
37. McBratney AB, Webster R. 1986. Choosing functions for semi-variograms of soil properties and fitting them to sampling estimates. Journal of Soil Science 37: 617-639.
38. Nicolau R, Ribeiro L, Rodrigues RR, Pereira HG, Câmara AS. 2002. Mapping the spatial distribution of rainfall in Portugal. In Geostatistics 2000 Cape Town, Kleingeld WJ, Krige DG (eds). Geostatistical Association of Southern Africa: Johannesburg; 548-558.
39. Pardo-Igúzquiza E. 1997. MLREML: a computer program for the inference of spatial covariance parameters by maximum likelihood and restricted maximum likelihood. Computers and Geosciences 23: 153-162.
40. Pardo-Igúzquiza E. 1998. Comparison of geostatistical methods for estimating the areal average climatological rainfall mean using data on precipitation and topography. International Journal of Climatology 18: 1031-1047.
41. Pardo-Igúzquiza E. 1999. VARFIT: a Fortran-77 program for fitting variogram models by weighted least squares. Computers and Geosciences 25: 251-261.
42. Pardo-Igúzquiza E, Dowd PA, Grimes DIF. 2005. An automatic moving window approach for mapping meteorological data. International Journal of Climatology 25: 665-678.
43. Pebesma EJ. 2004. Multivariable geostatistics in S: the Gstat package. Computers and Geosciences 30: 683-691.
44. Pebesma EJ, Wesseling CG. 1998. Gstat, a program for geostatistical modelling, prediction and simulation. Computers and Geosciences 24: 17-31.
45. Prudhomme C, Reed DW. 1999. Mapping extreme rainfall in a mountainous region using geostatistical techniques: a case study in Scotland. International Journal of Climatology 19: 1337-1356.
46. Sampson PD, Damien D, Guttorp P. 2001. Advances in modeling and inference for environmental processes with non-stationary spatial covariance. In GeoENV III: Geostatistics for Environmental Applications, Monestiez P Allard D, Froidevaux R (eds). Kluwer Academic Publishers: Dordrecht; 17-32.
47. Schabenberger O, Gotway CA. 2005. Statistical Methods for Spatial Data Analysis. Chapman & Hall, CRC Press: Boca Raton.
48. Tabios GQ, Salas JD. 1985. A comparative analysis of techniques for spatial interpolation of precipitation. Water Resources Bulletin 21: 365-380.
49. Webster R, Oliver MA. 2007. Geostatistics for Environmental Scientists, 2nd edn. John Wiley & Sons: Chichester.
50. Wackernagel H. 2003. Multivariate Geostatistics. An Introduction with Applications, 3rd edn. Springer: Berlin.