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

1
Impact of Sea Surface Temperature and Soil
Moistureon Seasonal Rainfall Prediction over the
SahelWassila M. Thiaw and Kingtse C. MoClimate
Prediction Center/NCEP/NOAAWashington, DC
Discussions Precipitation forecasts over the
Sahel from the NCEP coupled forecast system (CFS)
model were compared to the gauge rainfall
analysis. The CFS ensemble forecasts for JAS from
initial conditions in June show a southward shift
in the West African rain band (Fig. 2). This
leaves the Sahel very dry. The southward shift of
the rain band is accompanied by the southward
shift of the AEJ. The CFS forecasts also do not
capture the interannual variability in the Sahel
rainfall quite adequately (Fig. 1). The
suppressed interannual variability in P suggests
the existence of persistent erroneous forcing.
The model simulations and CFS (corrected) have
better representation of the position of the AEJ
and the spatial distribution of rainfall across
West Africa (Fig. 3 and 4). They also show more
realistic interannual rainfall variability. Part
of the P errors comes from the SST systematic
errors (Fig.5, 6). For the forecasts on the
seasonal time scales, SSTs have dominant
influence on rainfall over the Sahel. The
systematic error pattern is similar to the
decadal SST mode. It shows positive SSTs over the
North Pacific and the North Atlantic and negative
errors in the tropical Pacific and the southern
oceans (Fig. 7, 8). During the CFS forecasts,
the systematic errors are not corrected so they
serve as additional forcing. The persistence of
the errors in the SST pattern may cause the
errors in rainfall magnitudes and the suppressed
variability. The CFS model does not have
realistic ice model as a subcomponent. The ice
information is supplied through the mean monthly
climatology and the ocean coupling is limited to
the south of 65N. These model deficiencies may
contribute to the warming over the North Pacific
and the North Atlantic. In addition to the SST
errors, the soil moisture feedback mechanism may
also contribute to the southward shift of the AEJ
and rainfall. This is demonstrated by the
comparison between the AMIP run and the
simulations (Fig. 9, 11). Both experiments are
forced with the observed SSTs. The main
differences are in soil moisture and surface
fluxes. The SIMs are initialized from the R2 in
June and has realistic information on soil
moisture and surface fluxes. The AMIP, which is
a continuous run, does not have such information.
The AMIP run shows the southward shift of the
AEJ, while the SIMs provide a better
representation of the jet location and rainfall
spatial pattern. As expected, the AMIP has less
soil moisture over the Sahel and less E. E
contributes to P directly, but the largest
influence is indirect through the temperature
gradients. The radiation differences are smaller
so E is balanced by sensible heat. Less E implies
more sensible heat and indeed the AMIP is warmer
over the Sahel than the SIMs. This implies that
the largest temperature gradients over West
Africa in the AMIP are located further south than
in the SIMs. The temperature gradients reach the
middle troposphere (Fig. 10). This serves as a
forcing to move the AEJ southward. In response,
The African wave disturbances, which account for
much of the rains in the Sahel shift southward
resulting in dryness over the Sahel. As it is
well known, the most important contribution to
rainfall variability over the Sahel is the
decadal mode. The AMIP forced with the observed
SSTs does not capture the decadal changes in
rainfall. The model does not have interactive
vegetation fraction and does not use the
information of the leaf area index (LAI). The
vegetation fraction is supplied to the model
through the monthly mean vegetation fraction
climatology. Therefore, it is not able to
simulate the changes of albedo and surface fluxes
due to the greenness of vegetation. Vegetation
dynamics is a significant process in simulating
rainfall over the Sahel and it has been found
that the decadal variability which is the
essential part of the rainfall variability over
the Sahel is better produced when the interactive
vegetation is added to the model. Therefore, a
land-surface interaction model coupled with the
CFS will improve precipitation forecasts over the
Sahel. Thiaw, W. M., and K. C. Mo, 2005 J.
Climate, In press. Wassila.thiaw_at_noaa.gov
kingtse.mo_at_noaa.gov