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Vincent Moron, Andrew W. Robertson, M. Neil Ward, and Ousmane Ndiaye

Abstract

A k-means cluster analysis is used to summarize unfiltered daily atmospheric variability at regional scale over the western Sahel and eastern tropical North Atlantic during the boreal summer season [July–September (JAS)] 1961–98. The analysis employs zonal and meridional regional wind fields at 925, 700, and 200 hPa from the European Centre for Medium-Range Weather Forecasts reanalyses. An eight-cluster solution is shown to yield an integrated view of the complex regional circulation variability, without the need for explicit time filtering. Five of the weather types identified characterize mostly typical phases of westward-moving wave disturbances, such as African easterly waves (AEWs), and persistent monsoon surges, while the three others describe mostly different stages of the seasonal cycle. Their temporal sequencing describes a systematic monsoonal evolution, together with considerable variability at subseasonal and interannual time scales.

Daily rainfall occurrence at 13 gauge stations in Senegal is found to be moderately well conditioned by the eight weather types, with positive rainfall anomalies usually associated with southerly wind anomalies at 925 hPa. Interannual variability of daily rainfall frequency is shown to depend substantially on the frequency of occurrence of weather types specific to the beginning and end of the JAS season, together with the number of persistent monsoon surges over the western Sahel. In contrast, year-to-year changes in the frequency of the weather types mostly associated with westward-moving waves such as AEWs are not found to influence seasonal frequency of occurrence of daily rainfall substantially.

The fraction of seasonal rainfall variability related to weather-type frequency is found to have a strong relationship with tropical Pacific sea surface temperatures (SSTs): an El Niño (La Niña) event tends to be associated with a higher (lower) frequency of dry weather types during early and late JAS season with enhanced trade winds over the western Sahel, together with lower (higher) prevalence of persistent monsoon surges. The component of seasonal rainfall variability not related to weather-type frequency is characterized by changes in rainfall probability within each weather type, especially those occurring in the core of the JAS season; it exhibits a larger decadal component that is associated with an SST pattern previously identified with recent observed trends in Sahel rainfall.

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Vincent Moron, Andrew W. Robertson, M. Neil Ward, and Ousmane Ndiaye

Abstract

Four methods of downscaling daily rainfall sequences from general circulation model (GCM) simulations are intercompared over Senegal, using a 13-station network of daily observations during July–September 1961–98. The local scaling method calibrates raw GCM daily rainfall at the closest grid point to a given station so that the climatological distribution of rainfall matches the observed one. The k-nearest neighbor and weather classification schemes resample historical station rainfall observations according to the similarity between the daily wind fields from an ensemble of GCM simulations and a historical library of reanalysis [from 40-yr ECMWF Re-Analysis (ERA-40)] daily wind fields. The nonhomogenous hidden Markov model uses a small set of hidden states to describe the relationship between daily station rainfall observations and low-pass-filtered simulated winds to simulate stochastic sequences of daily rainfall. The four methods are assessed in terms of seasonal statistics of daily rainfall, including seasonal amount, rainfall frequency, and the mean length of wet and dry spells. Verification measures used are mean bias error, interannual anomaly correlation, root-mean-square error, and ranked probability skill score.

The k-nearest neighbor and weather-type classification are shown to perform similarly well in reproducing the mean seasonal cycle, interannual variability of seasonal amount, daily rainfall frequency, as well as the mean length of dry and wet spells, and generally slightly better than the nonhomogeneous hidden Markov model. All three methods are shown to outperform the simple local scaling method. This is due to (i) the ability of the GCM to reproduce remarkably well the mean seasonal cycle and the transitions between weather types defined from reanalysis and (ii) the GCM’s moderate-to-strong skill in reproducing the interannual variability of the frequency occurrence of the weather types that strongly influence the interannual variability of rainfall in Senegal. In contrast, the local scaling exaggerates the length of wet and dry spells and reproduces less accurately the interannual variability of the seasonal-averaged amounts, occurrences, and dry/wet spells. This failure is attributed primarily to systematic errors in the GCM’s precipitation simulation.

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Ousmane Ndiaye, M. Neil Ward, and Wassila M. Thiaw

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 western part of West Africa yields good Sahel rainfall skill for all models. Skill is mostly captured in the leading empirical orthogonal function (EOF1), representing large-scale fluctuation in the regional circulation system over the tropical Atlantic. This finding has operational significance for the utility of AGCMs for short lead-time prediction based on persistence of June SST information; however, studies have shown that for longer lead-time forecasts, there is substantial loss of skill, relative to that achieved using the observed JAS SST.

The potential of CGCMs is therefore explored for extending the lead time of Sahel rainfall predictions. Some of the models studied, when initialized using April information, show potential to at least match the levels of skill achievable from assuming persistence of April SST. One model [NCEP Climate Forecasting System (CFS)] was found to be particularly promising. Diagnosis of the hindcasts available for the CFS (from lead times up to six months for 1981–2008) suggests that, especially by applying the same MOS approach, skill is achieved through capturing interannual variations in Sahel rainfall (primarily related to El Niño–Southern Oscillation in the period of study), as well as the upward trend in Sahel rainfall that is observed over 1981–2008, which has been accompanied by a relative warming in the North Atlantic compared to the South Atlantic. At lead times up to six months (initialized forecasts in December), skill levels are maintained with the correlation between predicted and observed Sahel rainfall at approximately r = 0.6. While such skill levels at these long lead times are notably higher than previously achieved, further experiments, such as over the same period and with comparable AGCMs, are required for definitive attribution of the advance to the use of a coupled ocean–atmosphere modeling approach. Nonetheless, the detrended skill achieved here by the January–March initializations (r = 0.33) must require an approach that captures the evolution of the key ocean–atmosphere anomalies from boreal winter to boreal summer, and approaches that draw on persistence in ocean conditions have not previously been successful.

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Chris Hewitt, Erica Allis, Simon Mason, Meredith Muth, Roger Pulwarty, Joy Shumake-Guillemot, Ana E. Bucher, Manola Brunet, Andreas M. Fischer, Angela M. Hama, Rupa Kumar Kolli, Filipe Lucio, Ousmane Ndiaye, and Barbara Tapia
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