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A short-range multi-model ensemble weather prediction system for South Africa

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dc.contributor.author Landman, S
dc.contributor.author Engelbrecht, FA
dc.contributor.author Engelbrecht, CJ
dc.contributor.author Landman, WA
dc.contributor.author Dyson, L
dc.date.accessioned 2012-03-27T14:45:39Z
dc.date.available 2012-03-27T14:45:39Z
dc.date.issued 2010-09
dc.identifier.citation Landman, S, Engelbrecht, FA, Engelbrecht, CJ, Landman, WA and Dyson, L. A short-range multi-model ensemble weather prediction system for South Africa. 26th Annual South African Society for Atmospheric Sciences Conference, Gariep Dam, Free State, 20-22 September 2010 en_US
dc.identifier.isbn 978-0-620-47333-0
dc.identifier.uri http://www.sasas.org.za/images/stories/SASAS_2010_Program.pdf
dc.identifier.uri http://hdl.handle.net/10204/5688
dc.description 26th Annual South African Society for Atmospheric Sciences Conference, Gariep Dam, Free State, 20-22 September 2010 en_US
dc.description.abstract The objective of this paper is to present the temporal and spatial description of precipitation forecast skill over South Africa from an ensemble of multiple model runs. Numerical forecasts from an experimental short-range multi-model ensemble prediction system (EPS) at the South African Weather Service (SAWS) are examined. The ensemble consists of different forecasts from the 12-km LAM of the UK Met Office Unified Model (UM) and the Conformal-Cubic Atmospheric Model (CCAM) covering the South African domain. The multi-model ensemble consists of six members. The ensemble is simulated over a 0.5º grid for hourly precipitation for the austral summer season of October to March. The ensemble produces skill scores that are generally higher than those of the individual models, therefore providing the evidence that such a system can improve on deterministic rainfall forecasts that currently only uses the output of a single numerical weather model. en_US
dc.language.iso en en_US
dc.publisher SASAS en_US
dc.relation.ispartofseries Workflow;8598
dc.subject Multi-models en_US
dc.subject Short-range weather forecasting en_US
dc.subject South African weather forecasts en_US
dc.subject South African Weather Service en_US
dc.subject SAWS en_US
dc.subject Weather prediction systems en_US
dc.title A short-range multi-model ensemble weather prediction system for South Africa en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Landman, S., Engelbrecht, F., Engelbrecht, C., Landman, W., & Dyson, L. (2010). A short-range multi-model ensemble weather prediction system for South Africa. SASAS. http://hdl.handle.net/10204/5688 en_ZA
dc.identifier.chicagocitation Landman, S, FA Engelbrecht, CJ Engelbrecht, WA Landman, and L Dyson. "A short-range multi-model ensemble weather prediction system for South Africa." (2010): http://hdl.handle.net/10204/5688 en_ZA
dc.identifier.vancouvercitation Landman S, Engelbrecht F, Engelbrecht C, Landman W, Dyson L, A short-range multi-model ensemble weather prediction system for South Africa; SASAS; 2010. http://hdl.handle.net/10204/5688 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Landman, S AU - Engelbrecht, FA AU - Engelbrecht, CJ AU - Landman, WA AU - Dyson, L AB - The objective of this paper is to present the temporal and spatial description of precipitation forecast skill over South Africa from an ensemble of multiple model runs. Numerical forecasts from an experimental short-range multi-model ensemble prediction system (EPS) at the South African Weather Service (SAWS) are examined. The ensemble consists of different forecasts from the 12-km LAM of the UK Met Office Unified Model (UM) and the Conformal-Cubic Atmospheric Model (CCAM) covering the South African domain. The multi-model ensemble consists of six members. The ensemble is simulated over a 0.5º grid for hourly precipitation for the austral summer season of October to March. The ensemble produces skill scores that are generally higher than those of the individual models, therefore providing the evidence that such a system can improve on deterministic rainfall forecasts that currently only uses the output of a single numerical weather model. DA - 2010-09 DB - ResearchSpace DP - CSIR KW - Multi-models KW - Short-range weather forecasting KW - South African weather forecasts KW - South African Weather Service KW - SAWS KW - Weather prediction systems LK - https://researchspace.csir.co.za PY - 2010 SM - 978-0-620-47333-0 T1 - A short-range multi-model ensemble weather prediction system for South Africa TI - A short-range multi-model ensemble weather prediction system for South Africa UR - http://hdl.handle.net/10204/5688 ER - en_ZA


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