Can spatio-temporal geostatistical methods improve high resolution regionalisation of meteorological variables?

Agricultural and Forest Meteorology

Volumn 149, Issue 6-7, 2009, Pages 1105-1117

  Spadavecchia, L ^a   Williams, M ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

Error analysis; Kriging; Meteorological upscaling; Precipitation; Product sum covariance model; Space time geostatistics

Indexed keywords

ERROR ANALYSIS; GEOSTATISTICS; KRIGING; PRECIPITATION (CLIMATOLOGY); REGIONALIZATION; TEMPERATURE EFFECT; TIME SERIES;

NORTH AMERICA; OREGON; UNITED STATES;

EID: 62849105579     PISSN: 01681923     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.agrformet.2009.01.008     Document Type: Article

References (56)

1. Armstrong M., and Matheron G. Disjunctive Kriging revisited 1. Mathematical Geology 18 8 (1986) 711-728
2. Armstrong M., and Matheron G. Disjunctive Kriging revisited 2. Mathematical Geology 18 8 (1986) 729-742
3. Ashraf M., Loftis J.C., and Hubbard K.G. Application of geostatistics to evaluate partial weather station networks. Agricultural and Forest Meteorology 84 3-4 (1997) 255-271
4. Bertino L., Evensen G., and Wackernagel H. Combining geostatistics and Kalman filtering for data assimilation in an estuarine system. Inverse Problems 18 1 (2002) 1-23
5. Bristow K.L., and Campbell G.S. On the relationship between incoming solar-radiation and daily maximum and minimum temperature. Agricultural and Forest Meteorology 31 2 (1984) 159-166
6. Bruno, F., Guttorp, P., Sampson, P.D., Cocci, D., 2008. A simple non-separable, non-stationary spatiotemporal model for ozone. Environmental and Ecological Statistics, doi:10.1007/s10651-008-0094-8.
7. Cressie N. The origins of kriging. Mathematical Geology 22 3 (1990) 239-252
8. Cressie N.A.C. Statistics for Spatial Data. Wiley series in probability and mathematical statistics. Applied probability and statistics (1991), Wiley, New York/Chichester 900 pp.
9. Daly C., Neilson R.P., and Phillips D.L. A statistical topographic model for mapping climatological precipitation over mountainous terrain. Journal of Applied Meteorology 33 2 (1994) 140-158
10. De Cesare L., Myers D.E., and Posa D. Estimating and modeling space-time correlation structures. Statistics & Probability Letters 51 1 (2001) 9-14
11. De Iaco S., Myers D.E., and Posa D. Space-time analysis using a general product-sum model. Statistics & Probability Letters 52 1 (2001) 21-28
12. Deutsch C.V. Correcting for negative weights in ordinary kriging. Computers & Geosciences 22 7 (1996) 765-773
13. Deutsch C.V., and Journel A.G. Gslib: Geostatistical software library and user's guide (1998), Oxford University Press, New York
14. Diggle P.J., Ribero P.J., and Cristensen O.F. An introduction to model based geostatistics. In: Møller J. (Ed). Spatial Statistics and Computational Methods. Lecture Notes in Statistics (2002), Springer-Verlag, New York
15. Fawcett T. An introduction to ROC analysis. Pattern Recognition Letters 27 (2006) 861-874
16. Fuentes M., Chen L., and Davis J.M. A class of nonseparable and nonstationary spatial temporal covariance functions. Environmetrics 19 5 (2007) 487-507
17. Glassy J.M., and Running S.W. Validating diurnal climatology logic of the mt-clim model across a climatic gradient in Oregon. Ecological Applications 4 2 (1994) 248-257
18. Goovaerts P. Geostatistics for Natural Resources Evaluation. Applied geostatistics series vol. xiv (1997), Oxford University Press, New York/Oxford 483 pp.
19. Goovaerts P. Geostatistics in soil science: state-of-the-art and perspectives. Geoderma 89 1-2 (1999) 1-45
20. Goovaerts P. Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology 228 1-2 (2000) 113-129
21. Goward S.N., Waring R.H., Dye D.G., and Yang J.L. Ecological remote-sensing at otter-satellite macroscale observations. Ecological Applications 4 2 (1994) 322-343
22. Hudson G., and Wackernagel H. Mapping temperature using kriging with external drift-theory and an example from Scotland. International Journal of Climatology 14 1 (1994) 77-91
23. Hungerford, R.D., Nemani, R.R., Running, S.W., Coughlan, J.C., 1989. MTCLIM: a mountain microclimate simulation model. US Forum Service Research Paper INT-414.
24. Hutchinson M.F. Interpolating mean rainfall using thin-plate smoothing splines. International Journal of Geographical Information Systems 9 4 (1995) 385-403
25. Isaaks E.H., and Srivastava R.M. Applied Geostatistics vol. xix (1989), Oxford University Press, New York/Oxford 561 pp.
26. Jones R.G., Noguer M., Hassell D.C., Hudson D., Wilson S.S., Jenkins G.J., and Mitchell J.F.B. Generating High Resolution Climate Change Scenarios Using PRECIS (2004), Met Office Hadley Centre, Exeter, UK 40 pp.
27. Karrasch H. Microclimatic studies in the Alps. Arctic and Alpine Research 5 3 (1973) A55-A63
28. Kyriakidis P.C., and Journel A.G. Geostatistical space-time models: a review. Mathematical Geology 31 6 (1999) 651-684
29. Law B.E., Sun O.J., Campbell J., Van Tuyl S., and Thornton P.E. Changes in carbon storage and fluxes in a chronosequence of ponderosa pine. Global Change Biology 9 4 (2003) 510-524
30. Law B.E., Thornton P.E., Irvine J., Anthoni P.M., and Van Tuyl S. Carbon storage and fluxes in ponderosa pine forests at different developmental stages. Global Change Biology 7 7 (2001) 755-777
31. Law B.E., Turner D., Campbell J., Sun O.J., Van Tuyl S., Ritts W.D., and Cohen W.B. Disturbance and climate effects on carbon stocks and fluxes across Western Oregon USA. Global Change Biology 10 9 (2004) 1429-1444
32. Law B.E., and Waring R.H. Combining remote-sensing and climatic data to estimate net primary production across Oregon. Ecological Applications 4 4 (1994) 717-728
33. Mcbratney A.B., and Webster R. Choosing functions for semi-variograms of soil properties and fitting them to sampling estimates. Journal of Soil Science 37 4 (1986) 617-639
34. Murray F.W. On the computation of saturation vapor pressure. Journal of Applied Meteorology 6 (1967) 203-204
35. Nott D.J., and Dunsmuir W.T.M. Estimation of nonstationary spatial covariance structure. Biometrika 89 4 (2002) 819-829
36. O'Sullivan D., and Unwin D. Geographic Information Analysis (2003), John Wiley and Sons Inc., Hoboken, NJ
37. Paciorek C.J., and Schervish M.J. Spatial modelling using a new class of nonstationary covariance functions. Environmetrics 17 (2005) 483-506
38. Pinheiro J.C., and Bates D.M. Mixed-effects models in S and S-PLUS. Statistics and Computing vol. xvi (2000), Springer, New York 528 pp.
39. Porcu E., Mateu J., and Saura F. New classes of covariance and spectral density functions for spatio-temporal modelling. Stochastic Environmental Research and Risk Assessment 22 1 (2008) 65-79
40. Prihodko L., and Goward S.N. Estimation of air temperature from remotely sensed surface observations. Remote Sensing of Environment 60 3 (1997) 335-346
41. Rabus B., Eineder M., Roth A., and Bamler R. The shuttle radar topography mission-a new class of digital elevation models acquired by spaceborne radar. Isprs Journal of Photogrammetry and Remote Sensing 57 4 (2003) 241-262
42. Running S.W. Testing forest-bgc ecosystem process simulations across a climatic gradient in Oregon. Ecological Applications 4 2 (1994) 238-247
43. Running S.W., Nemani R.R., and Hungerford R.D. Extrapolation of synoptic meteorological data in mountainous terrain and its use for simulating forest evapotranspiration and photosynthesis. Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere 17 6 (1987) 472-483
44. Taylor G.H., and Hannan C. The Climate of Oregon: From Rainforest to Desert (1999), Oregon State University Press, Corvallis
45. Thiessen A.H. Precipitation averages for large areas. Monthly Weather Review 39 7 (1911) 1082-1089
46. Thornton P.E., and Running S.W. An improved algorithm for estimating incident daily solar radiation from measurements of temperature, humidity, and precipitation. Agricultural and Forest Meteorology 93 4 (1999) 211-228
47. Thornton P.E., Running S.W., and White M.A. Generating surfaces of daily meteorological variables over large regions of complex terrain. Journal of Hydrology 190 3-4 (1997) 214-251
48. Tobler W.R. A computer movie simulating urban growth in the Detroit region. Economic Geography 46 (1970) 234-240
49. Van Meirvenne M., and Goovaerts P. Evaluating the probability of exceeding a site-specific soil cadmium contamination threshold. Geoderma 102 1-2 (2001) 75-100
50. Van Tuyl S., Law B.E., Turner D.P., and Gitelman A.I. Variability in net primary production and carbon storage in biomass across Oregon forests-an assessment integrating data from forest inventories, intensive sites, and remote sensing. Forest Ecology and Management 209 3 (2005) 273-291
51. Wackernagel H. Multivariate Geostatistics: An Introduction With Applications vol. xiv (1998), Springer, Berlin/London 291 pp.
52. Waring R.H., and Peterson D.L. Oregon transect ecosystem research (otter) project. Ecological Applications 4 2 (1994) 210-210
53. Williams M., Law B.E., Anthoni P.M., and Unsworth M.H. Use of a simulation model and ecosystem flux data to examine carbon-water interactions in ponderosa pine. Tree Physiology 21 5 (2001) 287-298
54. Williams M., Rastetter E.B., Shaver G.R., Hobbie J.E., Carpino E., and Kwiatkowski B.L. Primary production in an arctic watershed: an uncertainty analysis. Ecological applications 11 (2001) 1800-1816
55. Williams M., Schwarz P.A., Law B.E., Irvine J., and Kurpius M.R. An improved analysis of forest carbon dynamics using data assimilation. Global Change Biology 11 1 (2005) 89-105
56. Zaleny M. Multiple Criteria Decision Making (1982), McGraw-Hill, New York