Seasonal Drought Forecasting for Latin America Using the ECMWF S4 Forecast System

Abstract

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 are 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 present 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 in the North of South America, the Northeast of Argentina, Uruguay, southern Brazil and Mexico. The skillful regions are similar for the SPI3 and -6, but become reduced in extent for the severest SPI categories. Forecasting different magnitudes of meteorological drought intensity on a seasonal time scale still remains a challenge. However, the ECMWF S4 forecasting system does capture the occurrence of drought events for the aforementioned regions and seasons reasonably well. 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, like the fifth generation of the ECMWF seasonal forecasting system, will be essential in this effort.

Performance of State‐of‐the‐Art C3S European Seasonal Climate Forecast Models for Mean and Extreme Precipitation Over Africa

“…In East, Central, West, North and Southern Africa up to 44% (ECMWF), 46% (UK‐Met), 58% (CMCC), 47% (UK‐Met), 39% (Meteo‐France), and 38% (UK‐Met) of droughts events are forecasted by the models, respectively. Similar to our findings, in Latin America, ECMWF showed a POD of 30% for drought events with FAR less than 70% (Carrão et al., 2018). The drought forecast performance is improved when using the MMM and WMMM.…”

SEAS5 skilfully predicts late wet‐season precipitation in Central American Dry Corridor excelling in Costa Rica and Nicaragua

“…In September, the opposite occurs, and SEAS5 low-precipitation forecasts are much worse than its predictions of normal precipitation variability (Figures 2 and 4). The overall seasonal variability aligns with findings from other studies of the previous version (S4); Carrão et al (2018), for instance, demonstrated relatively lower skill in May and June relative to July and August across much of Central America when measuring S4 skill for predicting SPI at 3-month lead time.…”

“…Dynamic forecasting systems like SEAS5 require more localized evaluation in the CADC specifically, as relatively few evaluations have focused on how these systems perform across the region, and their quality may vary regionally. Some studies have addressed how the previous version of the ECMWF forecasting system (S4) performed over Central America more generally (e.g., Dutra et al ., 2014; Weisheimer and Palmer, 2014; Carrão et al ., 2018), and others have investigated SEAS5 performance in nearby regions (e.g., in South America; Gubler et al ., 2020). For instance, Weisheimer and Palmer (2014) showed S4 had a perfect reliability score in predicting precipitation variability over Central America during June through August (JJA) and December through February (DJF) using initialization periods of 2 and 4 months in both relatively warm and cool years.…”

Evaluation of a New Precipitation-Based Index for Global Seasonal Forecasting of Unusually Wet and Dry Periods

“…Finally, it is worth highlighting the improvement of the new ECMWF seasonal forecast system (SEAS5) compared with the older version (S4). Indeed, the patterns found over South America look relatively similar to those obtained in (Carrão et al 2018), but with a clear increase of significance. The same scores as those used by these authors reveal this improvement between the two versions (not shown).…”