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.

Forecasting droughts in East Africa

“…Similar approaches have been also described by Mo et al (2012) and Yuan and Wood (2013). The results display the ensemble mean of the SPI forecasts; the ensemble mean variance was rescaled for each lead time to conserve a standard deviation of 1 (see Dutra et al, 2014, for further details). While each ensemble member of the SPI forecasts follows the SPI characteristics of mean zero and standard deviation of 1, the ensemble mean only conserves the zero mean and tends to have standard deviations lower than 1.…”

“…For example, Dutra et al (2013b) proposed a methodology to forecast 3-month SPI for the prediction of meteorological drought over four basins in Africa based on the SYS-4 forecasts of precipitation: the Blue Nile, Limpopo, Upper Niger, and Upper Zambezi. The detailed methodology used to calculate the SPI from the ECMWF seasonal forecasts is presented in Dutra et al (2014). This followed the methodology initially described by Dutra et al (2013b) and was applied on a basin scale.…”

Exploring drought vulnerability in Africa: an indicator based analysis to be used in early warning systems

“…A detailed analysis on the weighting scheme adopted as well as a comparison with the impacts of previous drought disasters may help in the stakeholders' acceptance of the indicator. Advances in seasonal forecast skill (Dutra et al, 2013(Dutra et al, , 2014 open the possibility for improved drought early warning systems. However, the implementation of such systems also requires an understanding of the social capacity to use the forecast.…”

Evaluating skill and robustness of seasonal meteorological and hydrological drought forecasts at the catchment scale – Case Catalonia (Spain)

“…For the next step, the reforecasted precipitation data (available for the period 2002-2010, Section 2.2.4) had to be organized. In the calculation of SPI3, SPI6, and SPI12, SFO precipitation data had to be added to the reforecast data, to be able to get SPIi values in all reforecast months (Yuan et al, 2013a(Yuan et al, , 2013bDutra et al, 2014). This means that, for instance in the SPI6 reforecasted dataset, the SPI6 for a lead time of one month (LT = 1) consists of five months of SFO precipitation data and one month of reforecasted precipitation data.…”

“…In Europe, seasonal meteorological drought forecasts currently range up to seven months (e.g. Hwang and Carbone, 2009;Dutra et al, 2014;Mo and Lyon, 2015), and are usually based on the Standardized Precipitation Index (SPI, McKee et al, 1993) or the Palmer Drought Severity Index (PDSI, Palmer, 1965). Pre-operational seasonal hydrometeorological drought forecasts have recently also been made available for Europe and on a regional scale for Catalonia under the EUfunded project ANYWHERE (www.anywhere-h2020.eu) (Sutanto and Van Lanen, in preparation).…”