2011
DOI: 10.1175/2010jcli3557.1
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Predictability of Seasonal Sahel Rainfall Using GCMs and Lead-Time Improvements Through the Use of a Coupled Model

Abstract: The ability of several atmosphere-only and coupled ocean-atmosphere general circulation models (AGCMs and CGCMs, respectively) is explored for the prediction of seasonal July-September (JAS) Sahel rainfall. The AGCMs driven with observed sea surface temperature (SST) over the period 1968-2001 confirm the poor ability of such models to represent interannual Sahel rainfall variability. However, using a model output statistics (MOS) approach with the predicted low-level wind field over the tropical Atlantic and w… Show more

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Cited by 42 publications
(29 citation statements)
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“…They found that the multimodel ensemble improved the spread-to-skill ratio and average skill score over the use of a single model by as much as 10% when measured as potential economic value. Philippon et al (2010) and Ndiaye et al (2011) found that skill can be enhanced by predicting modes of variability using model output statistics (MOS) instead of using direct model output and therefore such enhancements are used to produce forecasts.…”
Section: Seasonal Forecasting Of Drought In Africamentioning
confidence: 99%
“…They found that the multimodel ensemble improved the spread-to-skill ratio and average skill score over the use of a single model by as much as 10% when measured as potential economic value. Philippon et al (2010) and Ndiaye et al (2011) found that skill can be enhanced by predicting modes of variability using model output statistics (MOS) instead of using direct model output and therefore such enhancements are used to produce forecasts.…”
Section: Seasonal Forecasting Of Drought In Africamentioning
confidence: 99%
“…MOS uses predictor values from the CGCM in both the development and forecast stages, subsequently reducing model errors. This notion of statistical post-processing has already been tested and successfully employed in studies of AGCM versus coupled model performance Ndiaye et al, 2011). In addition, the post-processing will also have as a result model forecast data directly applicable over an area of interest, such as the 0.5° x 0.5° grid of the CRU data across the Lake Kariba catchment (e.g., Landman and Goddard, 2002;Shongwe et al, 2006).…”
Section: Statistical Downscalingmentioning
confidence: 99%
“…Such empirical remapping of GCM fields to regional rainfall has already been successfully employed (e.g., Landman and Goddard 2002;Shongwe et al 2006). Model output statistics (MOS) equations are developed here because they can compensate for systematic deficiencies in the global models directly in the regression equations (Wilks 2006) and have already been successfully employed in a study of AGCM versus coupled model performance (Ndiaye et al 2011). Since MOS uses predictor values from the global models in both the development and forecast stages, these model errors are subsequently reduced.…”
Section: Model Output Statisticsmentioning
confidence: 99%