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Climate Outlook
AFRICA December 2007 - May 2008

Issued: November 2007

The IRI has prepared this experimental Climate Outlook for Africa for December 2007 - May 2008. Of relevance in the preparation of this outlook is a likelihood that the tropical Pacific SSTs will assume La Nina conditions through the four forecast periods, and particularly the first two periods. Such tropical Pacific conditions are indicated in the SST predictions on which these climate forecasts are based. See the IRI's ENSO update for a discussion on the ENSO outlook (see IRI Probabilistic ENSO forecast). Warmer than average SSTs are now observed in the western tropical Pacific, while below normal SSTs are found in most of the eastern two-thirds. Below normal SST is observed in the west-central and western portions of Indonesia, that is atypical for a La Nina pattern. Much of the equatorial Indian Ocean continues to have slightly above normal SSTs. The tropical Atlantic Ocean shows a mixed anomaly pattern, with weakly above average SSTs north of the equator in the vicinity of the Gulf of Guinea, and weakly below average SSTs south of the equator in the western side. (SSTs). The SST anomalies in both the Indian and Atlantic oceans are predicted to weaken over the course of the forecast periods. (December-February&2008, January-March 2008, February-April 2008, March-May 2008).

METHODS -

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 December 2007 - May 2008 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.

OUTLOOK -

This Outlook covers four seasons: December-February&2008 January-March 2008 February-April 2008 and March-May 2008 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 most of Kenya in December-February&2008 (Map A), there is a 40% 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 25% 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.

December-February&2008 through March-May 2008

The following tables summarize the precipitation and temperature probability forecasts:



Summary of PRECIPITATION forecast for Africa
Leads 1, 2, 3, and 4 refer, respectively, to the upcoming seasons: Dec-Jan-Feb Jan-Feb-Mar Feb-Mar-Apr Mar-Apr-May
A non-enhanced probability for above or below normal is 33%. (There is a near-normal category whose non-enhanced probability is also 33%.)
The following countries or regions out of the 49 in Africa have at least half of their area under a PRECIPITATION forecast for:
At least At least Substantially slightly slightly Substantially enhanced enhanced enhanced enhanced probability probability probability probability (>48%) for (>38%) for (>38%) for (>48%) for below normal below normal above normal above normal
ANGOLA leads 3 and 4
BOTSWANA leads 2,3 and 4
BURUNDI lead 1
CAMEROON lead 3
CENTR AFRR REPUB leads 2,3 and 4
CONGO lead 2 COTE D*IVOIRE lead 4 GHANA lead 2
KENYA lead 1 KENYA leads 3 and 4 LESOTHO leads 3 and 4 LIBERIA leads 3 and 4 MALAWI leads 3 and 4
MOROCCO lead 3
MOZAMBIQUE leads 3 and 4
NAMIBIA leads 2,3 and 4
RWANDA lead 1 RWANDA lead 4
SIERRA LEONE lead 4
SOMALIA leads 3 and 4 SOUTH AFRICA leads 3 and 4
SWAZILAND leads 3 and 4
TANZANIA lead 1
TOGO lead 2
UGANDA lead 1
ZAMBIA leads 2,3 and 4
ZIMBABWE leads 2,3 and 4

Summary of TEMPERATURE forecast for Africa
Leads 1, 2, 3, and 4 refer, respectively, to the upcoming seasons: Dec-Jan-Feb Jan-Feb-Mar Feb-Mar-Apr Mar-Apr-May
A non-enhanced probability for above or below normal is 33%. (There is a near-normal category whose non-enhanced probability is also 33%.)
The following countries or regions out of the 49 in Africa have at least half of their area under a TEMPERATURE forecast for:
At least At least Substantially slightly slightly Substantially enhanced enhanced enhanced enhanced probability probability probability probability (>48%) for (>38%) for (>38%) for (>48%) for below normal below normal above normal above normal

ALGERIA leads 1 and 2 ANGOLA leads 2,3 and 4 BENIN leads 1 and 2 BENIN lead 4 BOTSWANA lead 1 BOTSWANA lead 4 BURKINA FASO leads 1 and 2 BURUNDI leads 1,2,3 and 4 BURUNDI lead 2 CAMEROON leads 3 and 4
CENTR AFRR REPUB leads 3 and 4 CHAD leads 1 and 2 CONGO leads 1,2,3 and 4
COTE D*IVOIRE leads 3 and 4 DJIBOUTI lead 1 DJIBOUTI leads 2,3 and 4 EGYPT leads 1,2,3 and 4 EGYPT leads 1 and 2 EQ GUINEA leads 2,3 and 4 ERITREA lead 1 ETHIOPIA leads 2,3 and 4
GABON leads 2,3 and 4 GAMBIA leads 1 and 2 GAMBIA lead 4
GHANA lead 4 GUINEA lead 1 GUINEA leads 3 and 4 GUINEABISSAU lead 1 GUINEABISSAU leads 3 and 4
KENYA leads 1,2 and 3 LESOTHO lead 1 LESOTHO lead 4
LIBERIA leads 2,3 and 4 LIBYA leads 1 and 2
MALAWI lead 1 MALAWI leads 2,3 and 4 MALI leads 1 and 2 MALI lead 4 MAURITANIA lead 1
MOROCCO leads 1,2,3 and 4
MOZAMBIQUE lead 1 MOZAMBIQUE leads 2,3 and 4
NAMIBIA leads 2 and 4 NIGER leads 1 and 2 NIGER lead 1 NIGERIA leads 1 and 2 NIGERIA lead 4
RWANDA leads 1,2,3 and 4 RWANDA lead 2 SENEGAL leads 1 and 2 SENEGAL lead 4
SIERRA LEONE leads 2,3 and 4
SOMALIA leads 2,3 and 4 SOUTH AFRICA lead 1 SOUTH AFRICA lead 4 SUDAN lead 1 SUDAN lead 4 SWAZILAND lead 1 SWAZILAND lead 4
TANZANIA leads 1,2,3 and 4 TOGO lead 1 TOGO leads 3 and 4 TUNISIA leads 1,2 and 3 UGANDA leads 1,2,3 and 4 WESTERN SAHARA leads 1,2,3 and 4 ZAIRE leads 1,2,3 and 4
ZAMBIA leads 2,3 and 4 ZIMBABWE lead 1 ZIMBABWE leads 3 and 4


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

CLIMATOLOGICAL AVERAGE:

TERCILE THRESHOLDS (33%-ile & 67%-ile):

EXTREME THRESHOLDS (15%-ile & 85 %-ile):

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