Articles | Volume 12, issue 1
https://doi.org/10.5194/asr-12-31-2015
https://doi.org/10.5194/asr-12-31-2015
02 Apr 2015
 | 02 Apr 2015

The verification of seasonal precipitation forecasts for early warning in Zambia and Malawi

O. Hyvärinen, L. Mtilatila, K. Pilli-Sihvola, A. Venäläinen, and H. Gregow

Abstract. We assess the probabilistic seasonal precipitation forecasts issued by Regional Climate Outlook Forum (RCOF) for the area of two southern African countries, Malawi and Zambia from 2002 to 2013. The forecasts, issued in August, are of rainy season rainfall accumulations in three categories (above normal, normal, and below normal), for early season (October–December) and late season (January–March). As observations we used in-situ observations and interpolated precipitation products from Global Precipitation Climatology Project (GPCP), Global Precipitation Climatology Centre (GPCC), and Climate Prediction Centre (CPC) Merged Analysis of Precipitation (CMAP). Differences between results from different data products are smaller than confidence intervals calculated by bootstrap.

We focus on below normal forecasts as they were deemed to be the most important for society. The well-known decomposition of Brier score into three terms (Reliability, Resolution, and Uncertainty) shows that the forecasts are rather reliable or well-calibrated, but have a very low resolution; that is, they are not able to discriminate different events. The forecasts also lack sharpness as forecasts for one category are rarely higher than 40 % or less than 25 %. However, these results might be unnecessarily pessimistic, because seasonal forecasts have gone through much development during the period when the forecasts verified in this paper were issued, and forecasts using current methodology might have performed better.

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Short summary
We assessed the quality of the seasonal precipitation forecasts issued by Regional Climate Outlook Forum for Malawi and Zambia. The forecasts, issued in August, are of rainy season rainfall accumulations for early and late season. The forecasts are rather well-calibrated, but cannot discriminate between different events. But these results can be too pessimistic, because forecasts have gone through much development lately, and forecasts using current methodology might have performed better.