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Climate Outlook
AFRICA October 2006 - March 2007

Issued: September 2006

The IRI has prepared this experimental Climate Outlook for Africa for October 2006 - March 2007. Of relevance in the preparation of this outlook is a moderately strong likelihood that the present somewhat above average tropical Pacific SSTs will continue. Such weak El Nino 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). Somewhat warmer than average SSTs are now observed in the west-central, central, and eastern tropical Pacific, while slightly below normal SSTs are found in the far western tropical Pacific. Much of the equatorial Indian Ocean, and much of the tropical Atlantic Ocean (particularly north of the equator), show above-average SSTs (SSTs). The tropical Atlantic SSTs are predicted to slowly weaken over the course of the forecast periods. (October-December 2006, November-January 2007, December-February 2007, January-March 2007).

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 October 2006 - March 2007 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: October-December 2006 November-January 2006 December-February 2006 and January-March 2006 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 October-December 2006 (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.

October-December 2006 through January-March 2006

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: Oct-Nov-Dec Nov-Dec-Jan Dec-Jan-Feb Jan-Feb-Mar
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
BENIN lead 1
BURUNDI leads 2 and 4
CAMEROON lead 1
CENTR AFRR REPUB lead 1
COTE D*IVOIRE leads 1,2 and 3
EQ GUINEA leads 1,2 and 3
GABON leads 1,2 and 3
GAMBIA lead 1 GAMBIA lead 1 GHANA leads 1 and 2
GUINEA leads 1 and 2
GUINEABISSAU lead 1 GUINEABISSAU lead 1 KENYA leads 1,2,3 and 4
LIBERIA leads 1,2 and 3 MALAWI lead 1
MOZAMBIQUE lead 1 NIGERIA lead 1
RWANDA leads 2,3 and 4
SENEGAL lead 1 SENEGAL lead 1 SIERRA LEONE leads 1,2,3 and 4
SOMALIA lead 2
TOGO lead 1
UGANDA leads 1,2,3 and 4 ZAMBIA lead 1

Summary of TEMPERATURE forecast for Africa
Leads 1, 2, 3, and 4 refer, respectively, to the upcoming seasons: Oct-Nov-Dec Nov-Dec-Jan Dec-Jan-Feb Jan-Feb-Mar
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 1,2,3 and 4
ANGOLA leads 1,2,3 and 4 ANGOLA leads 1,2,3 and 4 BENIN leads 1,2,3 and 4 BENIN lead 4 BOTSWANA leads 1,2,3 and 4
BURKINA FASO leads 1,2,3 and 4
BURUNDI leads 1,2,3 and 4 BURUNDI leads 1,2,3 and 4 CAMEROON leads 1,2,3 and 4 CAMEROON leads 1,2,3 and 4 CENTR AFRR REPUB leads 1,2,3 and 4 CENTR AFRR REPUB leads 1,2 and 3 CHAD leads 1,2,3 and 4 CHAD lead 1 CONGO leads 1,2,3 and 4 CONGO leads 1,2,3 and 4 COTE D*IVOIRE leads 1,2,3 and 4
DJIBOUTI leads 1,2,3 and 4 DJIBOUTI lead 4 EGYPT leads 1,2,3 and 4 EGYPT leads 1,2,3 and 4 EQ GUINEA leads 1,2,3 and 4 EQ GUINEA leads 1,2,3 and 4 ERITREA leads 1,2,3 and 4 ERITREA lead 1 ETHIOPIA leads 1,2,3 and 4
GABON leads 1,2,3 and 4 GABON leads 1,2,3 and 4 GAMBIA leads 1,2,3 and 4 GAMBIA leads 1,2,3 and 4 GHANA leads 1,2,3 and 4
GUINEA leads 1,2,3 and 4
GUINEABISSAU leads 1,2,3 and 4 GUINEABISSAU leads 2 and 3 KENYA leads 1,2,3 and 4
LESOTHO leads 3 and 4
LIBERIA leads 1,2,3 and 4 LIBERIA lead 1 LIBYA leads 1,2,3 and 4 LIBYA leads 1,2 and 3 MADAGASCAR leads 1,2,3 and 4 MADAGASCAR leads 1 and 4 MALAWI leads 1,2,3 and 4 MALAWI leads 3 and 4 MALI leads 1,2,3 and 4
MAURITANIA leads 1,2,3 and 4
MOROCCO leads 1,2,3 and 4
MOZAMBIQUE leads 1,2,3 and 4
NAMIBIA leads 1,2,3 and 4
NIGER leads 1,2,3 and 4
NIGERIA leads 1,2,3 and 4 NIGERIA lead 4 RWANDA leads 1,2,3 and 4 RWANDA leads 1,2,3 and 4 SENEGAL leads 1,2,3 and 4 SENEGAL leads 1,2,3 and 4 SIERRA LEONE leads 1,2,3 and 4
SOMALIA leads 1,2,3 and 4
SOUTH AFRICA leads 1,3 and 4
SUDAN leads 1,2,3 and 4 SUDAN lead 1 SWAZILAND leads 1,3 and 4
TANZANIA leads 1,2,3 and 4 TANZANIA lead 4 TOGO leads 1,2,3 and 4
TUNISIA leads 1,2,3 and 4
UGANDA leads 1,2,3 and 4 UGANDA lead 1 WESTERN SAHARA leads 1,2,3 and 4 WESTERN SAHARA leads 1,2,3 and 4 ZAIRE leads 1,2,3 and 4 ZAIRE leads 1,2,3 and 4 ZAMBIA leads 1,2,3 and 4 ZAMBIA leads 1,2,3 and 4 ZIMBABWE leads 1,2,3 and 4 ZIMBABWE lead 1


OBSERVED CLIMATOLOGY DATA for Oct-Nov-Dec, Nov-Dec-Jan, Dec-Jan-Feb and Jan-Feb-Mar

CLIMATOLOGICAL AVERAGE:

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

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

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