Assessing precipitation seasonal forecasts in Central Africa using North American Multimodel Ensemble (NMME)

This study examines the seasonal forecast of North American Multi-Model Ensemble (NMME) over Central Africa (CA), which encompasses a region world where economies countries are highly dependent on agriculture and livestock breeding. Following many regional climate perspectives, we evaluated 4 seasons: December to February (DJF), March May (MAM), June August (JJA), September November (SON) between 0 5 months lead time before beginning each season. Deterministic categorical approaches focus rainfall variable were used assess NMME ensemble mean (MME). The observed predicted rainfalls have been divided into three categories: below normal, above normal. results show that for 2 time, MME reproduces well peak Atlantic coast in East Democratic Republic Congo MAM SON 9 10 mm/day. Again same interval, values correlation coefficients (R) Global Precipitation Climatology Center (GPCC) reference observation all seasons greater than 0.72. For 3 lower R observed. It follows probabilities detection (POD) 50% different normal less 45% seasons. On other hand, high false alarm (FAR) low Critical Success Index (CSI) both From our results, one can argue seems be an interesting tool during first forecasting times CA capable providing important characteristics start season, will allow proper consideration meteorological phenomena.