Statistical downscaling of general circulation model output: A comparison of methods

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dc.contributor.authorWilby, R L
dc.contributor.authorWigley, T M L
dc.contributor.authorConway, D
dc.contributor.authorJones, P D
dc.contributor.authorHewitson, B C
dc.contributor.authorMain, J
dc.contributor.authorWilks, D S
dc.date.accessioned2021-10-08T07:22:55Z
dc.date.available2021-10-08T07:22:55Z
dc.date.issued1998
dc.description.abstractA range of different statistical downscaling models was calibrated using both observed and general circulation model (GCM) generated daily precipitation time series and intercompared. The GCM used was the U.K. Meteorological Office, Hadley Centre's coupled ocean/atmosphere model (HadCM2) forced by combined CO2 and sulfate aerosol changes. Climate model results for 1980-1999 (present) and 2080-2099 (future) were used, for six regions across the United States. The downscaling methods compared were different weather generator techniques (the standard 'WGEN' method, and a method based on spell-length durations), two different methods using grid point vorticity data as an atmospheric predictor variable (B-Circ and C-Circ), and two variations of an artificial neural network (ANN) transfer function technique using circulation data and circulation plus temperature data as predictor variables. Comparisons of results were facilitated by using standard sets of observed and GCM-derived predictor variables and by using a standard suite of diagnostic statistics. Significant differences in the level of skill were found among the downscaling methods. The weather generation techniques, which are able to fit a number of daily precipitation statistics exactly, yielded the smallest differences between observed and simulated daily precipitation. The ANN methods performed poorly because of a failure to simulate wet-day occurrence statistics adequately. Changes in precipitation between the present and future scenarios produced by the statistical downscaling methods were generally smaller than those produced directly by the GCM. Changes in daily precipitation produced by the GCM between 1980-1999 and 2080-2099 were therefore judged not to be due primarily to changes in atmospheric circulation. In the light of these results and detailed model comparisons, suggestions for future research and model refinements are presented.
dc.identifier.apacitationWilby, R. L., Wigley, T. M. L., Conway, D., Jones, P. D., Hewitson, B. C., Main, J., & Wilks, D. S. (1998). Statistical downscaling of general circulation model output: A comparison of methods. <i>Water Resources Research</i>, 34(11), 2995 - 3008. http://hdl.handle.net/11427/35030en_ZA
dc.identifier.chicagocitationWilby, R L, T M L Wigley, D Conway, P D Jones, B C Hewitson, J Main, and D S Wilks "Statistical downscaling of general circulation model output: A comparison of methods." <i>Water Resources Research</i> 34, 11. (1998): 2995 - 3008. http://hdl.handle.net/11427/35030en_ZA
dc.identifier.citationWilby, R.L., Wigley, T.M.L., Conway, D., Jones, P.D., Hewitson, B.C., Main, J. & Wilks, D.S. 1998. Statistical downscaling of general circulation model output: A comparison of methods. <i>Water Resources Research.</i> 34(11):2995 - 3008. http://hdl.handle.net/11427/35030en_ZA
dc.identifier.issn0043-1397
dc.identifier.issn1944-7973
dc.identifier.ris TY - Journal Article AU - Wilby, R L AU - Wigley, T M L AU - Conway, D AU - Jones, P D AU - Hewitson, B C AU - Main, J AU - Wilks, D S AB - A range of different statistical downscaling models was calibrated using both observed and general circulation model (GCM) generated daily precipitation time series and intercompared. The GCM used was the U.K. Meteorological Office, Hadley Centre's coupled ocean/atmosphere model (HadCM2) forced by combined CO2 and sulfate aerosol changes. Climate model results for 1980-1999 (present) and 2080-2099 (future) were used, for six regions across the United States. The downscaling methods compared were different weather generator techniques (the standard 'WGEN' method, and a method based on spell-length durations), two different methods using grid point vorticity data as an atmospheric predictor variable (B-Circ and C-Circ), and two variations of an artificial neural network (ANN) transfer function technique using circulation data and circulation plus temperature data as predictor variables. Comparisons of results were facilitated by using standard sets of observed and GCM-derived predictor variables and by using a standard suite of diagnostic statistics. Significant differences in the level of skill were found among the downscaling methods. The weather generation techniques, which are able to fit a number of daily precipitation statistics exactly, yielded the smallest differences between observed and simulated daily precipitation. The ANN methods performed poorly because of a failure to simulate wet-day occurrence statistics adequately. Changes in precipitation between the present and future scenarios produced by the statistical downscaling methods were generally smaller than those produced directly by the GCM. Changes in daily precipitation produced by the GCM between 1980-1999 and 2080-2099 were therefore judged not to be due primarily to changes in atmospheric circulation. In the light of these results and detailed model comparisons, suggestions for future research and model refinements are presented. DA - 1998 DB - OpenUCT DP - University of Cape Town IS - 11 J1 - Water Resources Research LK - https://open.uct.ac.za PY - 1998 SM - 0043-1397 SM - 1944-7973 T1 - Statistical downscaling of general circulation model output: A comparison of methods TI - Statistical downscaling of general circulation model output: A comparison of methods UR - http://hdl.handle.net/11427/35030 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/35030
dc.identifier.vancouvercitationWilby RL, Wigley TML, Conway D, Jones PD, Hewitson BC, Main J, et al. Statistical downscaling of general circulation model output: A comparison of methods. Water Resources Research. 1998;34(11):2995 - 3008. http://hdl.handle.net/11427/35030.en_ZA
dc.language.isoeng
dc.publisher.departmentDepartment of Environmental and Geographical Science
dc.publisher.facultyFaculty of Science
dc.sourceWater Resources Research
dc.source.journalissue11
dc.source.journalvolume34
dc.source.pagination2995 - 3008
dc.source.urihttps://dx.doi.org/10.1029/98WR02577
dc.subject.otherBurns
dc.subject.otherDisaster Planning
dc.subject.otherHumans
dc.subject.otherMass Casualty Incidents
dc.subject.otherNational Health Programs
dc.subject.otherPractice Guidelines as Topic
dc.subject.otherSocieties, Medical
dc.subject.otherSouth Africa
dc.titleStatistical downscaling of general circulation model output: A comparison of methods
dc.typeJournal Article
uct.type.publicationResearch
uct.type.resourceJournal Article
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