Seasonal drought forecasting for Latin America using the ECMWF S4 forecast system

Meaningful seasonal prediction of drought conditions is key information for end-users and water managers, particularly in Latin America where crop and livestock production are key for many regional economies. However, there still not many studies of the feasibility of such a forecasts at continental level in the region. In this study, precipitation predictions from the European Centre for Medium Range Weather (ECMWF) seasonal forecast system S4 are combined with observed precipitation data to generate forecasts of the standardized precipitation index (SPI) for Latin America, and their skill is evaluated over the hindcast period 1981–2010. The value-added utility in using the ensemble S4 forecast to predict the SPI is identified by comparing the skill of its forecasts with a baseline skill based solely on their climatological characteristics. As expected, skill of the S4-generated SPI forecasts depends on the season, location, and the specific aggregation period considered (the 3- and 6-month SPI were evaluated). Added skill from the S4 for lead times equaling the SPI accumulation periods is primarily in regions with high intra-annual precipitation variability, and is found mostly for the months at the end of the dry seasons for 3-month SPI, and half yearly periods for 6-month SPI. The ECMWF forecast system behaves better than the climatology for clustered grid points at the North of South America, Northeast of Argentina, Uruguay, southern Brazil and Mexico. The skillful regions are similar for the SPI3 and -6, but become reduced in extent for severest SPI categories. Forecasting different magnitudes of meteorological drought intensity on seasonal time scale still remains a challenge. However, the ECMWF S4 forecasting system does captures reasonably well the occurrence of drought events for some regions and months. In the near term, the largest advances in the prediction of meteorological drought for Latin America are obtainable from improvements in near-real-time precipitation observations for the region. In the longer term, improvements in precipitation forecast skill from dynamical models will be essential in this effort.

CARRAO Hugo;  NAUMANN Gustavo;  DUTRA Emmanuel;  LAVAYSSE Christophe;  MARINHO FERREIRA BARBOSA Paulo; 

2018-06-20

MDPI

JRC110968

2225-1154,   

http://www.mdpi.com/2225-1154/6/2/48,    https://publications.jrc.ec.europa.eu/repository/handle/JRC110968,   

10.3390/cli6020048,