ClimateWNA-high-resolution spatial climate data for western North America

Journal of Applied Meteorology and Climatology

Volumn 51, Issue 1, 2012, Pages 16-29

  Wang, Tongli ^a   Hamann, Andreas ^b   Spittlehouse, David L ^c   Murdock, Trevor Q ^d  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b UNIVERSITY OF ALBERTA   (Canada)

^c RESEARCH BRANCH   (Canada)

^d UNIVERSITY OF VICTORIA   (Canada)

Author keywords

Climate models; Interpolation schemes; Model evaluation performance; Model output statistics; Nonlinear models; Optimization

Indexed keywords

BASELINE DATA; CLIMATE CHANGE PROJECTIONS; CLIMATE DATA; CLIMATE PROJECTION; CLIMATE VARIABLES; DOWN-SCALING; ELEVATION GRADIENT; EXTREME TEMPERATURES; FUTURE CLIMATE; INTERPOLATION SCHEMES; MODEL EVALUATION/PERFORMANCE; MODEL OUTPUT STATISTICS; MULTI-MODEL; NON-LINEAR MODEL; PARTIAL DERIVATIVES; PRECIPITATION ANOMALIES; QUERY POINTS; RESOURCE MANAGERS; SOFTWARE USE; STATISTICAL ACCURACY; TEMPERATURE CHANGES; TEMPERATURE VARIABLES; WEATHER STATIONS;

ALGORITHMS; CLIMATE MODELS; OPTIMIZATION; SOFTWARE PACKAGES; TIME SERIES;

CLIMATE CHANGE;

AIR TEMPERATURE; ALGORITHM; CLIMATE CHANGE; CLIMATE MODELING; CLIMATE VARIATION; DATABASE; DOWNSCALING; INTERPOLATION; NONLINEARITY; NUMERICAL MODEL; OPTIMIZATION; PRECIPITATION (CLIMATOLOGY); STATISTICAL ANALYSIS; TIME SERIES ANALYSIS;

NORTH AMERICA;

EID: 84862907547     PISSN: 15588424     EISSN: None     Source Type: Journal    
DOI: 10.1175/JAMC-D-11-043.1     Document Type: Article

References (42)

1. Allen, R. G., L. S. Pereira, D. Raes, and M. Smith, 1998: Crop evapotranspiration-Guidelines for computing crop water requirements. U.N. Food and Agriculture Organization Irrigation and Drainage Paper FAO56, 300 pp.
2. Bürger, G., D. Reusser, and D. Kneis, 2009: Early flood warnings from empirical (expanded) downscaling of the full ECMWF Ensemble Prediction System. Water Resour. Res., 45, W10443, doi:10.1029/2009WR007779.
3. Campbell, E. M., R. I. Alfaro, and B. Hawkes, 2007: Spatial distribution of mountain pine beetle outbreaks in relation to climate and stand characteristics:Adendroecological analysis. J. Integr. Plant Biol., 49, 168-178.
4. Christenson, M., H. Manz, and D. Gyalistras, 2006: Climate warming impact on degree-days and building energy demand in Switzerland. Energy Convers. Manage., 47, 671-686.
5. Coops, N. C., R. Gaulton, and R. H. Waring, 2011: Mapping site indices for five Pacific Northwest conifers using a physiologically based model. J. Appl. Veg. Sci., 14, 268-276.
6. Daly, C., W. P.Gibson, G.H. Taylor, G. L. Johnson, and P. Pasteris, 2002:Aknowledge-based approach to the statisticalmapping of climate. Climate Res., 22, 99-113.
7. Daly, C., M. Halbleib, J. I. Smith, W. P. Gibson, M. K. Doggett, G. H. Taylor, and J. Curtis, 2008: Physiographically sensitive mapping of temperature and precipitation across the conterminous United States. Int. J. Climatol., 28, 2031-2064.
8. DeLong, S. C., H. Griesbauer, W. Mackenzie, and V. Foord, 2010: Corroboration of biogeoclimatic ecosystem classification climate zonation by spatiallymodelled climate data.BCJ. Ecosyst. Manage., 10, 49-64.
9. Donohue, R. J., T. R. McVicar, and M. L. Roderick, 2010: Assessing the ability of potential evaporation formulations to capture the dynamics in evaporative demand within a changing climate. J. Hydrol., 386, 186-197.
10. Fowler, H. J., S. Blenkinsop, and C. Tebaldi, 2007: Linking climate change modelling to impacts studies: Recent advances in downscaling techniques for hydrological modelling. Int. J. Climatol., 27, 1547-1578.
11. Fyfe, J. C., and G. M. Flato, 1999: Enhanced climate change and its detection over the Rocky Mountains. J. Climate, 12, 230-243.
12. Girvetz, E. H., C. Zganjar, G. T. Raber, E. P. Maurer, P. Kareiva, and J. J. Lawler, 2009: Applied climate-change analysis: The Climate Wizard tool. PloS One, 4, e8320, doi:10.1371/journal.pone.0008320.
13. Goring, S., M. G. Pellatt, T. Lacourse, I. R. Walker, and R. W. Mathewes, 2009: A new methodology for reconstructing climate and vegetation from modern pollen assemblages: An example from British Columbia. J. Biogeogr., 36, 626-638.
14. Gray, L. K., T. Gylander, M. Mbogga, P. Chen, and A. Hamann, 2011: Assisted migration to address climate change: Recommendations for aspen reforestation in western Canada. Ecol. Appl., 21, 1591-1603.
15. Hamann, A., and T. L. Wang, 2005: Models of climatic normals for genecology and climate change studies in British Columbia. Agric. For. Meteor., 128, 211-221.
16. Hamann, A., and T. L. Wang, 2006: Potential effects of climate change on ecosystem and tree species distribution in British Columbia. Ecology, 87, 2773-2786.
17. Hamann, A., T. Gylander, and P. Chen, 2011: Developing seed zones and transfer guidelines with multivariate regression trees. Tree Genet. Genomes, 7, 399-408.
18. Hargreaves, G. A., and Z. A. Samni, 1982: Estimation of potential evapotranspiration. J. Irrig. Drain. Div., Proc. Amer. Soc. Civ. Eng., 108, 223-230.
19. Hijmans, R. J., S. E. Cameron, J. L. Parra, P. G. Jones, and A. Jarvis, 2005: Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol., 25, 1965-1978.
20. Hutchinson, M. F., 1989: A new objective method for spatial interpolation ofmeteorological variables fromirregular networks applied to the estimation of monthly mean solar radiation, temperature, precipitation and windrun. CSIRO Division Water Resources Tech. Memo. 89/5, 104 pp.
21. Maurer, E. P., L. Brekke, T. Pruitt, and P. B. Duffy, 2007: Fineresolution climate projections enhance regional climate change impact studies. Eos, Trans. Amer. Geophys. Union, 88, 504, doi:10.1029/2007EO470006.
22. Maurer, E. P., J. C. Adam, and A. W. Wood, 2009: Climate model based consensus on the hydrologic impacts of climate change to the Rio Lempa basin of Central America. Hydrol. Earth Syst. Sci., 13, 183-194.
23. Mbogga, M. S., A. Hamann, and T. Wang, 2009: Historical and projected climate data for natural resource management in western Canada. Agric. For. Meteor., 149, 881-890.
24. Mbogga, M. S., X. L. Wang, and A. Hamann, 2010: Bioclimate envelope model predictions for natural resource management: Dealing with uncertainty. J. Appl. Ecol., 47, 731-740.
25. McCutchan, M. H., and D. G. Fox, 1986: Effect of elevation and aspect on wind, temperature and humidity. J. Climate Appl. Meteor., 25, 1996-2013.
26. McKenney, D.W., J. H. Pedlar, P. Papadopol, and M. F. Hutchinson, 2006: The development of 1901-2000 historical monthly climate models for Canada and the United States. Agric. For. Meteor., 138, 69-81.
27. McLane, S. C., L. D. Daniels, and S. N. Aitken, 2011a: Climate impacts on lodgepole pine (Pinus contorta) radial growth in a provenance experiment. For. Ecol. Manage., 262, 115-123.
28. McLane, S. C., V. M. LeMay, and S. N. Aitken, 2011b: Modeling lodgepole pine annual growth relative to climate and genetics using universal growth-trend response functions. Ecol. Appl., 21, 776-788.
29. Messaoud, Y., and H. Y. H. Chen, 2011: The influence of recent climate change on tree height growth differs with species and spatial environment. PLoS One, 6, e14691, doi:10.1371/ journal.pone.0014691.
30. Mitchell, T. D., and P. D. Jones, 2005: An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int. J. Climatol., 25, 693-712.
31. Miyamoto, Y., H. P. Griesbauer, and D. S. Green, 2010: Growth responses of three coexisting conifer species to climate across wide geographic and climate ranges in Yukon and British Columbia. For. Ecol. Manage., 259, 514-523.
32. O'Neill, G., A. Hamann, and T. Wang, 2008: Accounting for population variation improves estimates of climate change impacts on species' growth and distribution. J. Appl.Ecol., 45, 1040-1049.
33. Roberts, D. R. andA.Hamann, 2011: Predicting potential climate change impacts with bioclimate envelope models: A palaeoecological perspective. Global Ecol. Biogeogr., doi:10.1111/ j.1466-8238.2011.00657.x, in press.
34. Rose, N.-A., and P. J. Burton, 2011: Persistent climate corridors: The identification of climate refugia in British Columbia's Central Interior for the selection of candidate areas for conservation. BC J. Ecosyst. Manage., 12, 101-117.
35. Schlenker, W., M. W. Hanemann, and A. C. Fisher, 2007: Water availability, degree days, and the potential impact of climate change on irrigated agriculture in California. Climatic Change, 81, 19-38.
36. Shuttleworth, W. J., 1993: Evaporation. Handbook of Hydrology, D. R. Maidment, Ed., McGraw-Hill, 4.1-4.53.
37. Sinha, A., 1995: Relative influence of lapse rate and water vapor on the greenhouse effect. J. Geophys. Res., 100 (D3), 5095-5103.
38. Solomon, S., D.Qin, M.Manning, Z.Chen, M.Marquis, K.B.Avery, T. M. Tignor, H. L.Miller, Eds., 2007:ClimateChange 2007: The Physical Science Basis. Cambridge University Press, 996 pp.
39. Sutherst, R. W., G. F. Maywald, and A. S. Bourne, 2007: Including species interactions in risk assessments for global change. Global Change Biol., 13, 1-17.
40. Wang, T., A. Hamann, D. L. Spittlehouse, and S. N. Aitken, 2006a: Development of scale-free climate data for western Canada for use in resource management. Int. J. Climatol., 26, 383-397.
41. Wang, T., A. Hamann, A. Yanchuk, G.A. O'Neill, and S.N.Aitken, 2006b:Use of response functions in selecting lodgepole pine populations for future climate. Global Change Biol., 12, 2404-2416.
42. Wang, T., G. O'Neill, and S. N. Aitken, 2010: Integrating environmental and genetic effects to predict responses of tree populations to climate. Ecol. Appl., 20, 153-163.