CCA Prediction for Eastern Africa Rainfall in Oct-Nov-Dec 1999 at one Month Lead

contributed by Wassila Thiaw and Anthony Barnston

Climate Prediction Center/NCEP/NWS/NOAA, Washington DC, 20233

1. Methodology

CCA is a multivariate regression model that relates patterns in the predictor fields to patterns in the predictand field. The prediction scheme is designed such that four consecutive 3-month predictor periods are followed by a lead time and then a single 3-month predictand, or target period. The predictor SST data were derived from a combination of the COADS data and more recent OI data. The predictand Eastern Africa rainfall data come from the gridded global rainfall data set developed by M. Hulme at 2.5 by 3.75 resolution, resulting in 32 points in the Eastern Africa region. For the Oct-Nov-Dec 1998 East Africa rainfall prediction discussed above, the predictor data are the global SST anomaly field over the four 3-month periods of Sep-Oct-Nov 1998, Dec-Jan-Feb 1998-99, Mar-Apr-May, and Jun-Jul-Aug 1999. Using data from 1955-96, relationships between the prior year's SST anomaly evolution and the target year's Oct-Nov-Dec East Africa rainfall anomaly patterns are linearly modeled by the CCA. The predictor SST data for the current forecast are then projected onto the preferred relationships derived from the past years, and a forecast for Oct-Nov-Dec 1999 developed. Here the lead time is 1 month, because the latest predictor data used are those of August 1999, preceding the beginning of the target period by 1 month. The diagnostic data produced by CCA indicate that expected skill is low to modest in predicting Oct-Nov-Dec East Africa rainfall. Correlations between observed and predicted rainfall ranged between 0.1 and 0.4. A cross validation design is used in obtaining these skill estimates, where each year of the time series is held out of the developmental data set in turn, and then used as the forecast target.

2. Outlook

Eastern Africa is defined here as the region between 10°N and 10°S; 25-50°E. In this forecast, quasi-global SSTs between 40°S and 60°N at a resolution of 10° by 10° lat-lon are used to predict East African rainfall. The predictions (Figure 1) are expressed in terms of departures from climatological probabilities of 3 equi-probable categories of below, near, and above normal rainfall. The climatological probability of each category is 0.333. Positive (negative) departures from the climatological probability indicates a shift toward wet (dry) extremes. For instance a departure of 0.05 from the climatological probability indicates probabilities of 0.38 and 0.28 for above and below normal rainfall, respectively. For the sake of simplicity, the probability for the near normal category remains at 0.33. When skill is low, climatology (denoted with "0") is suggested. The diagnostic data produced by CCA indicate that the current cold episode of ENSO has a weak influence on Oct-Nov-Dec East African rainfall. In fact, during the past few months, the Indian Ocean, which usually drives the East African rainfall response to ENSO, has been warmer than normal, particularly over the eastern and central parts. Higher than normal SSTs over the Indian Ocean tend to be associated with above normal rainfall over East Africa. However, cold SSTs over the equatorial central Pacific are often conducive to near to below normal rainfall over parts of East Africa, especially in the east.

The prediction for Oct-Nov-Dec 1999 calls for slightly higher than climatological probabilities for below normal rainfall over southern Sudan eastward into southern Ethiopia, northern Kenya, and Somalia. Climatology is indicated across Uganda and much of the southern part of the region, including Tanzania.