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Influence of horizontal resolution and ensemble size on model performance

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dc.contributor.author Dalton, A
dc.contributor.author Landman, WA
dc.date.accessioned 2015-03-12T10:01:29Z
dc.date.available 2015-03-12T10:01:29Z
dc.date.issued 2014-10
dc.identifier.citation Dalton, A and Landman, WA. 2014. Influence of horizontal resolution and ensemble size on model performance. In: 30th Annual Conference of South African Society for Atmospheric Sciences (SASAS), Potchefstroom, 1-2 October 2014 en_US
dc.identifier.isbn 978-0-620-62777-1
dc.identifier.uri http://atmres.ukzn.ac.za/SASAS%202014%20peer%20review%20conference%20proceeding.pdf
dc.identifier.uri http://hdl.handle.net/10204/7929
dc.description 30th Annual Conference of South African Society for Atmospheric Sciences (SASAS), Potchefstroom, 1-2 October 2014. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website. en_US
dc.description.abstract Computing costs increase with an increase in global model resolution and ensemble size. This paper strives to determine the extent to which resolution and ensemble size affect seasonal forecast skill when simulating mid-summer rainfall totals over southern Africa. Furthermore a comparison is made between forecast skill of the 850 hPa geopotential heights and raw model rainfall outputs. The determination of skill was done by way of empirical post-processing procedures in order to project ensemble mean model forecast fields onto observed gridded mid-summer rainfall over South Africa. Spearman rank correlations are initially used to compare the performance of models with varying horizontal resolution as well as ensemble size. Further verification is also done on a set of probabilistic hindcasts through ROC scores and reliability diagrams. Skill increases with an increase in ensemble size and an increase in model resolution when 850 hPa geopotential heights are used to downscale to gridded rainfall, but when raw model rainfall is used for the downscaling similar improvement in skill is not observed. Finally, even with the best configuration (increased resolution and ensemble size) forecasts tend to be over-confident for both wet and for dry conditions notwithstanding their ability to discriminate. en_US
dc.language.iso en en_US
dc.publisher SASAS en_US
dc.relation.ispartofseries Workflow;14344
dc.subject Canonical correlation analysis en_US
dc.subject ECHAM5 en_US
dc.subject Geopotential height en_US
dc.subject Model performance en_US
dc.subject Spearman correlation en_US
dc.subject Southern Africa en_US
dc.title Influence of horizontal resolution and ensemble size on model performance en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Dalton, A., & Landman, W. (2014). Influence of horizontal resolution and ensemble size on model performance. SASAS. http://hdl.handle.net/10204/7929 en_ZA
dc.identifier.chicagocitation Dalton, A, and WA Landman. "Influence of horizontal resolution and ensemble size on model performance." (2014): http://hdl.handle.net/10204/7929 en_ZA
dc.identifier.vancouvercitation Dalton A, Landman W, Influence of horizontal resolution and ensemble size on model performance; SASAS; 2014. http://hdl.handle.net/10204/7929 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Dalton, A AU - Landman, WA AB - Computing costs increase with an increase in global model resolution and ensemble size. This paper strives to determine the extent to which resolution and ensemble size affect seasonal forecast skill when simulating mid-summer rainfall totals over southern Africa. Furthermore a comparison is made between forecast skill of the 850 hPa geopotential heights and raw model rainfall outputs. The determination of skill was done by way of empirical post-processing procedures in order to project ensemble mean model forecast fields onto observed gridded mid-summer rainfall over South Africa. Spearman rank correlations are initially used to compare the performance of models with varying horizontal resolution as well as ensemble size. Further verification is also done on a set of probabilistic hindcasts through ROC scores and reliability diagrams. Skill increases with an increase in ensemble size and an increase in model resolution when 850 hPa geopotential heights are used to downscale to gridded rainfall, but when raw model rainfall is used for the downscaling similar improvement in skill is not observed. Finally, even with the best configuration (increased resolution and ensemble size) forecasts tend to be over-confident for both wet and for dry conditions notwithstanding their ability to discriminate. DA - 2014-10 DB - ResearchSpace DP - CSIR KW - Canonical correlation analysis KW - ECHAM5 KW - Geopotential height KW - Model performance KW - Spearman correlation KW - Southern Africa LK - https://researchspace.csir.co.za PY - 2014 SM - 978-0-620-62777-1 T1 - Influence of horizontal resolution and ensemble size on model performance TI - Influence of horizontal resolution and ensemble size on model performance UR - http://hdl.handle.net/10204/7929 ER - en_ZA


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