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A Dynamical One-Month Lead Seasonal Rainfall Prediction for

July to September 1997 for North Africa from 20N to the Equator

contributed by Mike Harrison¹, Tony Evans¹, Mike Davey² and Andrew Colman²

¹NWP Division ²Ocean Applications Branch

UK Meteorological Office, Bracknell, United Kingdom

One objective of the European PROVOST experiment (PRediction Of climate Variations On Seasonal and interannual Timescales) is to estimate potential dynamical seasonal predictability given ideal surface boundary conditions on a global scale. To this end, three European models (the UKMO Unified Model at climate resolution, the ECMWF T63 model and the ARPGE model run at T42 by Météo-France and T63 by EDF) have been integrated in 9-member ensembles initialized at 24-hour intervals for four months for each season over 15 years from 1979 to 1993 (climatologies are calculated over the same period). Common initial conditions and verifying analyses obtained from the ECMWF reanalysis as well as common SST anomalies from the UKMO GISST and Reynold's OI data sets were used in all experiments. All initializations were at 0000Z finishing on the day prior to the start of the season. Useful levels of skill appear to exist in these PROVOST simulations for most of the region over Africa between the Equator and 20N, and in this paper a real-time seasonal forecast at one month lead is provided for the region based on these assessments.

Within the area of Africa bound by the Equator and the 20N line of latitude, area correlations over the 15 years between ensemble-mean rainfall anomalies and anomaly values obtained from the gridded observed land-surface rainfall data set of Hulme (1994) vary between 0.18 and 0.67, with lowest correlations for the area of northern Kenya and Uganda and highest correlations over eastern Niger, western Chad and central Sudan (Fig. 1). The observed data set is gridded to the same resolution as the model (2.5 x 3.75), but in order to reduce noise 4x4 blocks have been joined together to produce Figure 1; only blocks with adequate data were retained. Time series of ensemble mean rainfall and the Hulme data for selected regions illustrate the fact that the dynamical model, although able to capture the interannual variability reasonably well, has insufficient variability (Fig. 2). Hence a variance inflation has been calculated using both ensemble means and ensemble members for each gridded area and applied appropriately to the forecasts from both the members and the ensemble means given below. Note that observed anomalies frequently lie within the ranges of the inflated ensembles or are close outliers to those ranges; capture rates vary between 5 (Area A in Figure 1) and 15 (Area C).

Correlations have also been calculated for three standard areas of the region (Fig. 3) as used in past UKMO predictions (regions 2, 3 and 4 in Colman et al., 1996 and this volume). The regions are defined in terms of the model grid, and observed values have been generated from the Hulme data set. Correlations are lowest over the northern Sahel region (0.51), but exceed 0.6 in the central Sudan and southern Guinea Coast regions. Capture rates achieved after ensemble variance inflation (Fig. 2) vary between 10 (Guinea Coast) and 15 (Sudan; not show explicitly in Fig. 2).

Forecasts as produced for the 1997 July to September season are derived from nine-member ensemble runs, but with the difference from the PROVOST runs that persisted SST anomalies (from May), rather than observed values, are used throughout. It is thought unlikely that the use of persisted anomalies will have a significant negative impact if results obtained from experiments for twelve winter seasons, carried out with persisted anomalies, can be extrapolated to the summer. While there is some inevitable loss of predictability associated with the use of persisted anomalies, this appears to be minimal in areas of relatively high predictability such as considered here, and certainly does not eliminate predictability in terms of the levels normally associated with seasonal forecasts (see Harrison et al. 1997). Use of persisted anomalies fails, of course, during seasons in which there is a substantial readjustment of SST anomalies over ocean areas related to a given region's rainfall; experience has been gained of such failed forecasts for the Sahel in preliminary work with the model. Currently there is no solution to this problem of rapid intraseasonal SST anomaly distribution changes: the forecasts given below are conditional on the continuity of the May anomalies.

The ensemble mean provides a consistent prediction of below-average rainfall during July to September 1997 across the region except for a few isolated local areas (Fig. 4 and Table 1). A decrease in convection along the ITCZ from its model climato-logical average is suggested.

Ensemble mean, together with maximum and minimum, rainfall anomalies, all variance-inflated, for each of the gridded areas depicted in Figure 1, plus for the three standard African rainfall indices, are listed in Table 1. Ensemble and statistical model predictions of below-normal rainfall are reasonably consistent with one another (cf. Colman et al. 1997).

Table 1. July to September 1997 seasonal forecast rainfall percentages of normal for the unmodified Ensemble Mean (E Mean - with respect to the model 1979-1993 climate) and inflated Mean (I Mean - with respect to the Hulme data for 1979-1983) and for the highest and lowest (inflated) ensemble members for each of the 7 areas depicted in Figure 1. Also shown in the last three columns are equivalent predictions for the three north African rainfall regions (2 - Sahel; 3 - Sudan; 4 - Guinea coast), each inflated individually.

Forecast (%)	A	B	C	D	E	F	G	2	3	4
E Mean	91	93	82	98	95	95	95	87	92	86
I Mean	91	92	67	98	95	94	95	82	86	79
I Highest	100	116	93	108	113	102	106	103	101	101
I Lowest	78	74	62	87	72	84	74	72	63	69

Colman, A., M. Davey, M. Harrison and D. Rich-ardson, 1996: Multiple regression and discriminant analysis predictions of Jul-Aug-Sep 1996 rainfall in the Sahel and other tropical North African regions. Experimental Long-Lead Bulletin, NOAA, 5, June 1996, 26-28.

Colman, A. et al., 1997: Multiple regression and discriminant analysis predictions of Jul-Aug-Sep 1997 rainfall in the Sahel and other tropical North African regions. Experimental Long-Lead Forecast Bulletin, NOAA, 6, June 1997 (this volume, 2 articles below).

Harrison, M., T. Evans, R. Evans, M. Davey and A. Colman, 1997: A dynamical one-month lead seasonal rainfall prediction for March to May 1997 for the north-eastern area of South America. Experimental Long-Lead Forecast Bulletin, NOAA, 6, March 1997, 25-28.

Hulme, M., 1994: Validation of large-scale precipitation fields in general circulation models. Global Precipitation and Climate Change, M. Desbois and F. Desalmand, Eds., NATO ASI Series, Vol. 23, Springer-Verlag, 387-406.

Fig. 1. Correlations for simulations over July to September 1979-1993 between ensemble mean rainfall and the Hulme gridded rainfall set over 10 x 15 blocks.

Fig. 2. Time series of Ensemble Mean (EM) rainfall (as % of normal) pre- and post-inflation of ensembles created using observed SST and of the Hulme dataset for selected representative areas (see Figs 1 and 3). Bars indicate inflated range of ensembles and the median. Capture rate (CR) indicates the number of years out of 15 when the observation lies within the range of the inflated ensemble.

Fig. 3. Correlations for simulations over July to September 1979-93 between ensemble mean rainfall and the Hulme gridded rainfall set over the areas shown for Sahel (labeled 2), Sudan (labeled 3) and Guinea coast (labeled 4).

Fig. 4. Non-inflated ensemble mean precipitation forecast anomalies for July to September 1997. Negative contours dashed. Variable contour interval in mm/day.

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