Statistical downscaling using localized constructed analogs (LOCA)

Journal of Hydrometeorology

Volumn 15, Issue 6, 2014, Pages 2558-2585

  Pierce, David W ^a   Cayan, Daniel R ^a,b   Thrasher, Bridget L ^c  

^a San Diego   (United States)

^b U S GEOLOGICAL SURVEY   (United States)

^c Climate Analytics Group   (United States)

Author keywords

Atmosphere land interaction; Climate models; Hydrologic models; Hydrometeorology; Land surface model; Regional effects

Indexed keywords

CLIMATE MODELING; CORRELATION; DOWNSCALING; HYDROMETEOROLOGY; LAND SURFACE; PRECIPITATION (CLIMATOLOGY);

UNITED STATES;

EID: 84915749409     PISSN: 1525755X     EISSN: 15257541     Source Type: Journal    
DOI: 10.1175/JHM-D-14-0082.1     Document Type: Article

References (28)

1. Abatzoglou, J. T., and T. J. Brown, 2012: A comparison of statistical downscaling methods suited for wildfire applications. Int. J. Climatol., 32, 772-780, doi:10.1002/joc.2312.
2. Chen, J., F. P. Brissette, and R. Leconte, 2014: Assessing regression-based statistical approaches for downscaling precipitation over North America. Hydrol. Processes, 28, 3482- 3504, doi:10.1002/hyp.9889.
3. Das, T., E. P. Maurer, D. W. Pierce, M. D. Dettinger, and D. R. Cayan, 2013: Increases in flood magnitudes in California under warming climates. J. Hydrol., 501, 101-110, doi:10.1016/ j.jhydrol.2013.07.042.
4. Fowler, H. J., S. Blenkinsop, and C. Tebaldi, 2007: Linking climate change modeling to impacts studies: Recent advances in downscaling techniques for hydrological modelling. Int. J. Climatol., 27, 1547-1578, doi:10.1002/joc.1556.
5. Goodess, C. M., and J. P. Palutikof, 1998: Development of daily rainfall scenarios for southeast Spain using a circulationtype approach to downscaling. Int. J. Climatol., 18, 1051-1083, doi:10.1002/(SICI)1097-0088(199808)18:10,1051:: AID-JOC304.3.0.CO;2-1.
6. Gutmann, E. D., T. Pruitt, M. P. Clark, L. Brekke, J. R. Arnold, D. A. Raff, and R. M. Rasmussen, 2014: An intercomparison of statistical downscaling methods used for water resource assessments in the United States. Water Resour. Res., 50, 7167-7186, doi:10.1002/2014WR015559.
7. Hidalgo, H. G., M. D. Dettinger, and D. R. Cayan, 2008: Downscaling with constructed analogues: Daily precipitation and temperature fields over the United States. CEC PIER Project Rep. CEC-500-2007-123, 48 pp. [Available online at www.energy.ca.gov/2007publications/CEC-500-2007-123/CEC-500-2007-123.PDF.]
8. Hwang, S., and W. D. Graham, 2014: Assessment of alternative methods for statistically downscaling dailyGCMprecipitation outputs to simulate regional streamflow. J. Amer. Water Resour. Assoc., 50, 1010-1032, doi:10.1111/jawr.12154.
9. Livneh, B., E. A. Rosenberg, C. Lin, B. Nijssen, V. Mishra, K. Andreadis, E. P. Maurer, and D. P. Lettenmaier, 2013:Alongterm hydrologically based dataset of land surface fluxes and states for the conterminous United States: Updates and extensions. J. Climate, 26, 9384-9392, doi:10.1175/JCLI-D-12-00508.1.
10. Lobell, D. B., A. Torney, and C. B. Field, 2009: Climate extremes in California agriculture.CaliforniaEnergyCommissionRep. CEC- 500-2009-040-F, 8 pp. [Available online at www.energy.ca.gov/2009publications/CEC-500-2009-040/CEC-500-2009-040-F.PDF.]
11. Maraun, D., 2013: Bias correction, quantile mapping, and downscaling: Revisiting the inflation issue. J. Climate, 26, 2137- 2143, doi:10.1175/JCLI-D-12-00821.1.
12. Maraun, D., and Coauthors, 2010: Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user. Rev. Geophys., 48, RG3003, doi:10.1029/2009RG000314.
13. Maurer, E. P., H. G. Hidalgo, T. Das, M. D. Dettinger, and D. R. Cayan, 2010: The utility of daily large-scale climate data in the assessment of climate change impacts on daily streamflow in California. Hydrol. Earth Syst. Sci., 14, 1125-1138, doi:10.5194/hess-14-1125-2010.
14. Parry, M. L., O. F. Canziani, J. P. Palutikof, P. J. van der Linden, and C. E. Hanson, Eds., 2007: Climate Change 2007: Impacts, Adaptation, and Vulnerability. CambridgeUniversity Press, 976 pp.
15. Piani, C., J. Haerter, and E. Coppola, 2010: Statistical bias correction for daily precipitation in regional climate models over Europe. Theor. Appl. Climatol., 99, 187-192, doi:10.1007/s00704-009-0134-9.
16. Pierce, D. W., and D. R. Cayan, 2013: The uneven response of different snow measures to human-induced climate warming. J. Climate, 26, 4148-4167, doi:10.1175/JCLI-D-12-00534.1.
17. Pierce, D. W., and Coauthors, 2013: The key role of heavy precipitation events in climate model disagreements of future annual precipitation changes in California. J. Climate, 26, 5879-5896, doi:10.1175/JCLI-D-12-00766.1.
18. Schoof, J. T., and S. C. Pryor, 2001: Downscaling temperature and precipitation: A comparison of regression-based methods and artificial neural networks. Int. J. Climatol., 21, 773-790, doi:10.1002/joc.655.
19. Thrasher, B., E. P. Maurer, C. McKellar, and P. B. Duffy, 2012: Technical note: Bias correcting climate model simulated daily temperature extremes with quantile mapping. Hydrol. Earth Syst. Sci., 16, 3309-3314, doi:10.5194/hess-16-3309-2012.
20. Trewin, B. C., 2007: The role of climatological normals in a changing climate. WCDMP-61/WMO-TD-1377, 45 pp. [Available online at www.wmo.int/datastat/documents/WCDMPNo61_1.pdf.]
21. van den Dool, H. M., 1994: Searching for analogues, how long must we wait? Tellus, 46A, 314-324, doi:10.1034/j.1600-0870.1994.t01-2-00006.x.
22. von Storch, H., 1999: On the use of ''inflation'' in statistical downscaling. J. Climate, 12, 3505-3506, doi:10.1175/ 1520-0442(1999)012,3505:OTUOII.2.0.CO;2.
23. von Storch, H., E. Zorita, and U. Cubasch, 1993: Downscaling of global climate change estimates to regional scales: An application to Iberian rainfall in wintertime. J. Climate, 6, 1161-1171, doi:10.1175/1520-0442(1993)006,1161:DOGCCE.2.0.CO;2.
24. Wilby, R. L., T. M. L. Wigley, D. Conway, P. D. Jones, B. C. Hewiston, J.Main, andD. S.Wilks, 1998: Statistical downscaling of general circulation model output: A comparison of methods. Water Resour. Res., 34, 2995-3008, doi:10.1029/98WR02577.
25. Wilby, R. L., S. P. Charles, E. Zorita, B. Timbal, P. Whetton, and L.O.Mearns, 2004: Guidelines for use of climate scenarios developed from statistical downscalingmethods. IPCCDoc., 27 pp. [Available online at www.ipcc-data.org/guidelines/dgm_no2_v1_09_2004.pdf.]
26. Wilks, D. S., 2012: Stochastic weather generators for climatechange downscaling, part II: Multivariable and spatially coherent multisite downscaling. Wiley Interdiscip. Rev.: Climate Change, 3, 267-278, doi:10.1002/wcc.167.
27. Wood, A.W., L. R. Leung, V. Sridhar, and D. P. Lettenmaier, 2004: Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Climatic Change, 62, 189-216, doi:10.1023/B:CLIM.0000013685.99609.9e.
28. Zhang, F., and A. P. Georgakakos, 2012: Joint variable spatial downscaling. Climatic Change, 111, 945-972, doi:10.1007/s10584-011-0167-9.