Global meteorological drought – Part 2: Seasonal forecasts

Abstract

Abstract. Global seasonal forecasts of meteorological drought using the standardized precipitation index (SPI) are produced using two datasets as initial conditions: the Global Precipitation Climatology Center (GPCC) and the ECMWF ERA-Interim reanalysis (ERAI); and two seasonal forecasts of precipitation: the most current ECMWF seasonal forecast system and climatologically based ensemble forecasts. The forecast skill is concentrated on verification months where precipitation deficits are likely to have higher drought impacts and grouped over different regions in the world. Verification of the forecasts as a function of lead time revealed a reduced impact on skill for: (i) long lead times using different initial conditions, and (ii) short lead times using different precipitation forecasts. The memory effect of initial conditions was found to be 1 month lead time for the SPI-3, 3 to 4 months for the SPI-6 and 5 months for the SPI-12. Results show that dynamical forecasts of precipitation provide added value, a skill similar or better than climatological forecasts. In some cases, particularly for long SPI time scales, it is very difficult to improve on the use of climatological forecasts. Our results also support recent questions whether seasonal forecasting of global drought onset was essentially a stochastic forecasting problem. Results are presented regionally and globally, and our results point to several regions in the world where drought onset forecasting is feasible and skilful.