EXPERIMENTAL FORECAST OF EAST AFRICAN RAINFALL FOR OCTOBER-DECEMBER 1999

INTRODUCTION

The Met Office is conducting research into the effects of sea surface temperatures and other climatic variables on tropical rainfall. As part of this research, experimental seasonal rainfall forecasts have been made for the Sahel and adjacent regions in tropical NW Africa since 1986, and for the Nordeste region of Brazil since 1987. Using similar statistical methods, forecasts for tropical East Africa October-December rainfall (the 'short rains') have been issued since 1994 and appear in previous September issues of this bulletin .

A long-lead forecast for East African rainfall using observed data up to mid August has already been produced and was contributed to the Greater Horn of Africa Climate Outlook Forum (GHACOF10 ). This forecast uses observed data up to the end of August.

The region covered by the East Africa prediction is between 5N and 15S and between 30E and the Indian Ocean coast. These forecasts for E Africa were produced using statistical methods and by using the Met Office's Atmospheric General Circulation Model (AGCM). In addition to forecasts for the entire region, forecasts for 2.5^o latitude x 3.75^o longitude rectangular sub-regions corresponding to model grid boxes are provided. Skill is not so high at this higher resolution but these forecasts give an indication of rainfall distribution.

The statistical forecast is made by using linear regression and discriminant analysis techniques, with three indices of global sea surface temperature (SST) anomaly patterns (Appendix, figures A1-A3 respectively). The forecast model is derived from historical rainfall and SST information.

The AGCM forecast was extracted from two nine-member ensembles of AGCM predictions using sea temperatures and atmospheric conditions observed just prior to when the forecasts were run (September 6^th and 13th).

Forecasts are expressed as probabilities for 5 equi-probable categories (quints) for the whole region and as probabilities of 3 equi-probable categories (terciles) for the sub-regions. The categories are equi-probable over the 1961-1990 climatology period.

The category boundaries (as percentages of mean rainfall) are:

FORECAST SKILL

PERFORMANCE OF TRIAL FORECASTS FOR 50 PAST YEARS

The statistical and dynamical forecasts were tested using trial forecasts over the period 1948 to 1997. The assessment measure used is correlation.

Statistical linear regression forecasts were assessed using a method where a trial forecast is made for each year using a regression equation calculated using data for the remaining years. This assessment provides a good measure of forecast skill from minimal data.

To provide an indication of AGCM skill, the performance of a long term AGCM run forced with observed SST in simulating rainfall is measured.

Statistical forecast skill correlation=0.50
AGCM simulation skill correlation=0.65

These correlations are statistically significant at the 5% level.

PERFORMANCE OF REAL TIME EMPIRICAL FORECASTS

Forecasts have been made for this region since 1994. The forecasts for 1994 and 1995 were strongly influenced by above and below average SST in the NW Pacific respectively and the forecasts for 1997 and 1998 where influenced by the 1997 El Nino and the 1998 La Nina events. The observed rainfalls for 2000 and 2001 were quite close to the dry-average and very dry-dry boundaries respectively so the forecasts for these seasons were as accurate as they could be.

Year	1994	1995	1996	1997	1998	1999	2000	2001
Forecast Category	Very Wet	Dry	Average	Wet	Dry or Average	Dry	Dry or Average	Dry or VeryDry
Observed Category	Wet	Dry	Very Dry	Very Wet	Very Dry	Average	Dry	Very Dry

Note: The categories used for the 1994-1998 forecasts are based on a 1951-1980 climatology. For the 1999 and later forecasts, categories based on the 1961-1990 climatology are used as 1961-1990 is the accepted WMO standard climatology period and is used by most forecasters. The 1961-1990 rainfall average is 104% of the 1951-1980 average.

FORECASTS FOR THE 2002 SEASON

STATISTICAL FORECAST

Below average SST in the NW Pacific and in the tropical SW Atlantic are favouring below average rainfall in E Africa this year. The regression forecast is 96% of the 1961-1990 average and is in the AVERAGE category

The discriminant analysis technique gives the following probabilities for the 5 (1961-1990 based) categories:

Very Dry	Dry	Average	Wet	Very Wet
0.23	0.28	0.39	0.04	0.05

Very Dry	Dry	Average	Wet	Very Wet
0.42	0.24	0.15	0.08	0.10

OVERALL BEST ESTIMATE: This year, the AGCM is favouring the VERY DRY category whilst the empirical forecasts favour the AVERAGE category with probabilities skewed towards the drier categories. Our best estimate is a consensus forecast for the DRY category.

SUB- REGION GRID BOX FORECASTS

The grid box forecasts are expressed as probabilities of terciles which are climatologically equi-probable over 1961-1990. This is in order to make the forecasts compatible with GHACOF forecasts which are expressed in the same way. Figure 1 shows the skill of the empirical forecasts. The empirical and dynamical forecasts are shown in figures 2 and 3 respectively.

Two forecast maps are shown for each category, one includes all grid boxes for which there is data, the second (skill mask) version includes only gridboxes where independent test correlation skill is significant. To be included on the skill mask map, hindcasts for the box must pass at least 1 of these 2 tests:

· Correlation between independent hindcasts and observations over 1949-1998 are significant at the 5% level (shown in figure 1)

· Correlation between independent hindcasts of this years forecast tercile and observations during 1949-1998 are significant at the 5% level

OVERALL BEST ESTIMATE: Below average rainfall is predicted for most of Tanzania and Southern Kenya by both the AGCM and empirical forecasts. Elsewhere, probabilities are mostly close to climatology levels. In the far north-east (Central Sudan) the forecasts of below average rainfall mostly indicate zero rainfall in a region where the climatology is zero rainfall .

REFERENCE:

Mutai, C.C., Ward, M.N and Colman, A.W. Prediction of East Africa seasonal "short rainfall" rooted in evidence for widespread SST-forced variability during October-December. J.Climatol., 18, 975-997 (1998).

ACKNOWLEDGEMENTS:

Thanks to David Rowell for providing output from the HADAM3 model. Thanks to Pete Mclean and Richard Graham for supplying dynamical forecast output.

APPENDIX : Predictor patterns used for empirical Forecast

The pattern shown in figure 3 is the most important predictor contributing to over 50% of the forecast variance.

FIGURE 1: CORRELATION SKILL OF EMPIRICAL REGRESSION FORECASTS

FIGURE 2: PROBABILITY FORECASTS BY EMPIRICAL METHOD

FIGURE 3: PROBABILITY FORECASTS FROM AGCM DYNAMICAL FORECAST

Figure A1:

Figure A2:

Figure A3:

VeryDry/Dry	Dry/Average	Average/Wet	Wet /Very Wet
74%	86%	102%	124%

Seasonal Forecasting Group, Ocean Applications, Met Office, Bracknell, UK