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
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CLIMATOLOGICAL AVERAGE:
TERCILE THRESHOLDS (33%-ile & 67%-ile):
EXTREME THRESHOLDS (15%-ile & 85 %-ile):
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