Developing an Agricultural Drought Prediction Framework for Timor-Leste

Abstract

Agricultural drought is a natural hazard which has disastrous impacts on populations, economies and the environment in drought-vulnerable countries. This study develops an agricultural drought prediction framework for Timor-Leste—a least developed country in Southeast Asia. Currently, long-range forecasting capabilities and proactive agricultural drought management practices in Timor-Leste remain limited, constraining the country’s ability to prepare for and respond to periodic drought events. This research evaluated the effectiveness of drought prediction in Timor-Leste using seasonal rainfall outlooks from a dynamical Global Climate Model (GCM): the European Centre for Medium-Range Weather Forecasts’ (ECMWF) Seasonal Forecast System 5 (SEAS5), across different drought and non-drought events. SEAS5 effectively predicted an increased probability of below-average median rainfall over Timor-Leste for the case study of the 2015–2016 El Niño-induced drought and was assessed as having higher probabilistic skill across the wider study area compared with the Australian Bureau of Meteorology’s (BoM) Australian Community Climate and Earth-System Simulator (ACCESS-S2). While some limitations exist in raw forecast skill at times of year when predictability is lower, outlooks from both GCMs could, with sound communication, be applied to predict drought’s onset, peak and end. This research serves as a foundational step toward the development of an agricultural drought early warning system in Timor-Leste.