The IRI has prepared this experimental Climate Outlook for Africa for January - June 2003. Of relevance in the preparation of this outlook is the prediction of moderate El Niño conditions in the central and eastern equatorial Pacific through the end of 2002 and lasting at least into the first two to four months of 2003. The sea surface temperatures (SSTs) across much of the central equatorial Pacific are more than 1 degree C above their long-term average(SSTs), and have been so for the last several months. In the last month, SST anomalies in some parts of the central and eastern equatorial Pacific have exceeded 2 degrees C. Warm SST anomalies for the central equatorial Pacific are predicted by the coupled model throughout the forecast period January-March 2003, February-April 2003, March-May 2003, April-June 2003. However, the coupled model forecast has not captured the strength of the currently observed warm conditions, and it is believed that the SST anomalies observed in the next 2-3 months may be warmer than indicated in the coupled model SST forecast. Warmer than average SSTs continue to dominate much of the central and western Indian Ocean. These are expected to decrease slowly through the forecast period. There are currently no substantial SST anomalies in the tropical Atlantic Ocean, but this may change near the end of the forecast period as the northern tropical Atlantic frequently develops warm SST anomalies in the February-May season in response to El Niño conditions in the Pacific.

This Outlook was prepared using the following procedures and information:

A) Coupled ocean-atmosphere model predictions of tropical Pacific SST covering the forecast period. Particularly heavy weighting has been given to predictions from the coupled model operated by the NOAA National Centers for Environmental Prediction, Climate Modeling Branch. This model suggests a continuation of near-average conditions during the first forecast season. The forecast for near-neutral conditions is consistent with some, but not all, numerical and statistical forecasts of central and eastern Pacific SSTs.

B) Forecasts of the tropical Indian ocean using a statistical model developed by the IRI.

C) Global atmospheric general circulation model (GCM) predictions of the atmospheric response to the present and predicted sea-surface temperature patterns.

D) Other sources of information include NASA's Seasonal to Interannual Prediction Project (GSFC-NASA) and also seasonal prediction research at COLA.

The procedures, models, and data used to derive this Climate Outlook may be somewhat different from those used by the national meteorological services in the region. Thus, this product may differ from the official forecasts issued in those areas. The Climate Outlook for January - June 2003 is dependent on the accuracy of the SST predictions. For the tropical Pacific, these predictions can be expected to provide useful information, but there is some uncertainty concerning the evolution of SSTs. Spread (variation) in global SST predictions is a source of uncertainty in the Outlook provided here. In particular, the forecasts for the tropical Indian and Atlantic oceans have been an important influence on the forecasts over Africa. Note that even if perfectly accurate SST forecasts were possible, there would still be uncertainty in the climate forecast due to chaotic internal variability of the atmosphere. These uncertainties are reflected in the probabilities given in the forecast.

It is stressed that the current status of seasonal-to-interannual climate forecasting allows prediction of spatial and temporal averages, and does not fully account for all factors that influence regional and national climate variability. This Outlook is relevant only to seasonal time scales and relatively large areas; local variations should be expected, and variations within the 3-month period should also be expected. For further information concerning this and other guidance products, users are strongly advised to contact their National Meteorological Services.

This Outlook covers four seasons: January-March 2003, February-April 2003, March-May 2003 and April-June 2003. Maps are given showing tercile probabilities of precipitation and temperature. The maps for precipitation indicate the probabilities that the seasonal precipitation will fall into the wettest third of the years (top number), the middle third of the years (middle number), or the driest third of the years (bottom number). The color shading indicates the probability of the most dominant tercile -- that is, the tercile having the highest forecast probability. The color bar alongside the map defines these dominant tercile probability levels. The upper side of the color bar shows the colors used for increasingly strong probabilities when the dominant tercile is the above-normal tercile, while the lower side shows likewise for the below-normal tercile. The gray color indicates an enhanced probability for the near-normal tercile (nearly always limited to 40%). As before, numbers and their associated histograms show the probabilities of the three terciles. In areas with lots of spatial detail, there may not be sufficient room on the map, to allow histograms for each region. In those cases, some idea of the probabilities may be gained from the color alone. A qualitative outlook of climatology ("C") indicates that there is no basis for favoring any particular category. Areas that are marked by "D" represent regions for which less than 3cm of precipitation typically occurs over the season. Otherwise, for example, in the case of Botswana in January-March 2003 (Map A), there is a 25% probability that the precipitation will be in the wettest third of the years, a 35% chance it will be in the near-normal third of the years, and a 40% chance that the precipitation will be in the driest third of the years.

Maps of temperature show expected probabilities that the seasonal temperatures will fall into the warmest third of the years, the middle third of the years, or the coldest third of the years (Map A). The numbers for each region on the temperature maps indicate the probabilities of temperatures to fall in each of the three categories, above-, near-, and below-normal.

An additional precipitation map is provided for the first season indicating probabilities for extreme precipitation anomalies. Extremes are defined as anomalies that fall within the top and bottom 15th percentile of the observed records. A priori, there is a 15% probability of being within the extremely wet category, and a 15% probability of being within the extremely dry category, leaving a 70% probability that the precipitation will not be extreme. The maps indicate areas of increased risk of extreme precipitation totals. Three levels of increased risk are defined: slightly enhanced risk, enhanced risk, and greatly enhanced risk. For slightly enhanced risk, there is a 25-40% probability that precipitation will be within the indicated extreme, i.e. wet or dry. This represents an approximate doubling of the climatological risk. For enhanced risk, there is a 40-50% probability that precipitation will be within the indicated extreme. This represents an approximate tripling of the climatological risk. For greatly enhanced risk, the probability that precipitation will be within the indicated extreme exceeds 50%, i.e. the indicated extreme is the most likely outcome. A similar map is provided in the first season indicating probabilities of extreme temperature anomalies.

Boundaries between sub-regions should be considered as transition zones, and their location considered to be only qualitatively correct.

January-March 2003 through April-June 2003:

The following discussion briefly describes the probability anomaly forecasts:

Enhanced probabilities for below normal precipitation are forecast for large portions of southern Africa for the first three forecast periods. Enhanced probabilities for above normal precipitation are forecast for equatorial eastern Africa, central, and/or western Africa during all four forecast periods, particularly equatorial eastern Africa for the first two periods.

OBSERVED CLIMATOLOGY DATA for Jan-Feb-Mar, Feb-Mar-Apr, Mar-Apr-May and Apr-May-Jun