Wassila M. Thiaw

Predictability of Seasonal Sahel Rainfall Using GCMs and Lead-Time Improvements Through the Use of a Coupled Model

AbstractThe 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...

Impact of Sea Surface Temperature Anomalies on the Atlantic Tropical Storm Activity and West African Rainfall

Abstract The association between rainfall over the Sahel and Sudan region and tropical storm activity in the Atlantic is examined using the NCEP–NCAR reanalysis and sea surface temperature anomalies (SSTAs) from 1949 to 1998. Evidence indicates that both are influenced by global SSTAs. The SSTA modes generating favorable atmospheric conditions for tropical storms to develop are also in favor of a wet rainfall season in the Sahel and Sudan region. The easterly waves over West Africa become tropical storms only if the atmospheric conditions over the Atlantic are favorable. These conditions are responses to SSTAs. In addition to ENSO, a multidecadal trend mode also plays a role. The positive phase of the trend mode features positive loadings in the North Pacific and the North Atlantic, and negative loadings over the three southern oceans. The positive (negative) phases of both modes are associated with increased (reduced) Atlantic tropical storm activity, and with wet (dry) West African monsoon seasons. The ...

Predictions of African rainfall on the seasonal timescale

Real-time predictions of the rainfall in July-September 1997 and January-March 1998, respectively, for the Sahel and southern Africa at 1 month lead are presented. The forecast technique is based on canonical correlation analysis (CCA), a multivariate linear statistical model that relates patterns in the predictand field to patterns in the predictor field. In this CCA design, four consecutive 3 month predictor periods are followed by a lead time and a single 3 month predictand period. Cross validation is used to estimate the skill in the forecasts. The forecasts are expressed in terms of departures from climatological probabilities of three equiprobable categories for above-, near-, and below-normal rainfall. Expressing the forecasts in terms of probability anomalies communicates the level of confidence in the forecasts. Forecast verifications have been performed using the Heidke skill (S) score. For the Sahel the July-September 1997 rainfall prediction at 1 month lead showed reasonable skill. Furthermore, it is shown that the Sahel rainfall in July-September is influenced at least partly by El Nino-Southern Oscillation (ENSO). In addition, Sahel rainfall is affected by the sea surface temperature pattern in the Atlantic Ocean and perhaps the Indian Ocean. For southern Africa, the S score was +30, suggesting a moderately good forecast for the region as a whole. The results also indicate that ENSO plays an important role in modulating rainfall variations in southern Africa.

Cholera outbreak in Senegal in 2005: was climate a factor?

Cholera is an acute diarrheal illness caused by Vibrio cholerae and occurs as widespread epidemics in Africa. In 2005, there were 31,719 cholera cases, with 458 deaths in the Republic of Senegal. We retrospectively investigated the climate origin of the devastating floods in mid-August 2005, in the Dakar Region of Senegal and the subsequent outbreak of cholera along with the pattern of cholera outbreaks in three other regions of that country. We compared rainfall patterns between 2002 and 2005 and the relationship between the sea surface temperature (SST) gradient in the tropical Atlantic Ocean and precipitation over Senegal for 2005. Results showed a specific pattern of rainfall throughout the Dakar region during August, 2005, and the associated rainfall anomaly coincided with an exacerbation of the cholera epidemic. Comparison of rainfall and epidemiological patterns revealed that the temporal dynamics of precipitation, which was abrupt and heavy, was presumably the determining factor. Analysis of the SST gradient showed that the Atlantic Ocean SST variability in 2005 differed from that of 2002 to 2004, a result of a prominent Atlantic meridional mode. The influence of this intense precipitation on cholera transmission over a densely populated and crowded region was detectable for both Dakar and Thiès, Senegal. Thus, high resolution rainfall forecasts at subseasonal time scales should provide a way forward for an early warning system in Africa for cholera and, thereby, trigger epidemic preparedness. Clearly, attention must be paid to both natural and human induced environmental factors to devise appropriate action to prevent cholera and other waterborne disease epidemics in the region.

Impact of Sea Surface Temperature and Soil Moisture on Seasonal Rainfall Prediction over the Sahel

Abstract The ensemble rainfall forecasts over the Sahel for July–September (JAS) from the NCEP Coupled Forecast System (CFS) were evaluated for the period 1981–2002. The comparison with the gauge-based precipitation analysis indicates that the predicted Sahel rainfall is light and exhibits little interannual variability. The rain belt is shifted about 4° southward. One major source of rainfall errors comes from the erroneous sea surface temperature (SST) forecasts. The systematic SST error pattern has positive errors in the North Pacific and the North Atlantic and negative errors in the tropical Pacific and the southern oceans. It resembles the decadal SST mode, which has a significant influence on rainfall over the Sahel. Because the systematic SST errors were not corrected during the forecasts, persistent errors serve as an additional forcing to the atmosphere. The second source of error is from the soil moisture feedback, which contributes to the southward shift of rainfall and dryness over West Africa...

Regional model simulations of African wave disturbances

A regional climate simulation model is run at 50 km horizontal resolution over West Africa to study synoptic systems, such as African wave disturbances (AWDs). The study examines the results of 18 simulations, the longest of them covering the period August 8-15, 1988. Simulations were initialized with European Center for Medium-Range Weather Forecasts (ECMWF) gridded analysis data which also supply the lateral boundary conditions. Daily means of 700 mbar circulation and other model diagnostics are compared with ECMWF and National Centers for Environmental Prediction analyses to assess the skill of the model in simulating the evolution of synoptic systems. Trajectories of AWDs are tracked on time-longitude cross sections of 700 mbar vorticity, lower tropospheric divergence and precipitation rates. Cloud clusters on satellite imagery relate rather well to synoptic features on observational analyses as well as to spatial patterns of rain gage measurements but not consistently to simulated precipitation. Movement of major AWDs and the generation of new waves are handled realistically by the model. Model dynamics and physics appear to be more important than lateral boundary conditions in determining the course of simulations.

NOAA’s African Desk: Twenty Years of Developing Capacity in Weather and Climate Forecasting in Africa

AbstractDrought is one of the leading causes of death in Africa because of its impact on access to sanitary water and food. This challenge has mobilized the international community to develop famine early warning systems (FEWS) to bring safe food and water to populations in need. Over the past several decades, much attention has focused on advance risk planning in agriculture and water and, more recently, on health. These initiatives require updates of weather and climate outlooks. This paper describes the active role of NOAA’s African Desk in FEWS and in enhancing the capacity of African institutions to improve forecasts. The African Desk was established in 1994 to provide services to U.S. agencies and African institutions. Emphasis is on the operational products across all time scales from weather to climate forecasts in support of humanitarian relief programs. Tools to provide access to real-time weather and climate information to the public are described. These include the downscaling of the U.S. Nati...

Effects of tropical convection on the predictability of the Sahel summer rainfall interannual variability

Tropical convection as inferred from OLR, and global SST, are used as predictor fields in separate canonical correlation analysis (CCA) experiments. The experiments are based on 43-year (1955-98) observed SST data and 20-year (1979-98) OLR record. The aim is to study the role of tropical convection in improving the predictions of the interannual variability of the Sahel summer rainfall. Forecast skills for OLR and SST predictor fields are estimated using a cross-validation scheme. Average region-wide correlation skill for OLR is 0.368, which is slightly higher than skill for SST based on a 43-year record (0.308). However, much of the skill in the latter is associated with long term trends. Skill for OLR outperforms significantly that of SST based on a 20-year historical record. Hindcasts for the Jul-Sep Sahel rainfall in 1997 and 1999 show an improvement over SST in the predictions of the interannual variability where OLR is used as predictor field.