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 data sets as initial conditions: the Global Precipitation Climatology Centre (GPCC) and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis (ERAI); and two seasonal forecasts of precipitation, the most recent ECMWF seasonal forecast system and climatologically based ensemble forecasts. The forecast evaluation focuses on the periods where precipitation deficits are likely to have higher drought impacts, and the results were summarized over different regions in the world. The verification of the forecasts with lead time indicated that generally for all regions the least reduction on skill was found for (i) long lead times using ERAI or GPCC for monitoring and (ii) short lead times using ECMWF or climatological seasonal forecasts. The memory effect of initial conditions was found to be 1 month of lead time for the SPI-3, 4 months for the SPI-6 and 6 (or more) months for the SPI-12. Results show that dynamical forecasts of precipitation provide added value with skills at least equal to and often above that of climatological forecasts. Furthermore, it is very difficult to improve on the use of climatological forecasts for long lead times. Our results also support recent questions of 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.

Impacts of climate change on drought: changes to drier conditions at the beginning of the crop growing season in southern Brazil

“…The SPI calculation starts by fitting a parametric distribution to the precipitation data (P) that can be accumulated over a wide range of time scales (Dutra et al 2014). This first step is also known as calibration process (Dubrovsky et al 2008).…”

Global Meteorological Drought: A Synthesis of Current Understanding with a Focus on SST Drivers of Precipitation Deficits

“…Nonetheless, these relationships do not seem to be associated with the high interannual predictability of meteorological drought in central and northern Europe (Dutra et al 2014). Overall SST anomalies, which may be associated with largescale modes of variability, explain only a small fraction of the annual mean variability in precipitation (less than 10%) and temperature (less than 20%) over Europe (see Fig.…”

Hydrological drought forecasting and skill assessment for the Limpopo River basin, southern Africa

“…A hindcast set is provided for calibration and verification purposes, covering a period of 30 years with the same configuration as the operational forecasts but with only 15 ensemble members. Molteni et al (2011) presents an overview of S4 model biases and forecasts performance, and Dutra et al ( , 2014 present an evaluation of S4 in seasonal forecasts of meteorological droughts. They found that S4-derived meteorological drought forecasts over southern Africa were skilful with up to 4-months lead time for SPI-6 in April.…”