<![CDATA[Papua, Indonesia’s easternmost island, is prone to seasonal hydrometeorological disasters, necessitating high-quality climate forecasts for effective risk management. This study evaluates the performance of the European Centre for Medium-Range Weather Forecasts (ECMWF) Seasonal Forecast System 5 (SEAS5) in predicting seasonal (3-monthly) rainfall across Papua from 1982 to 2016, using the blended Climate Hazards group InfraRed Precipitation with in-situ rainfall data (CHIRP+Pos) as the observational reference. SEAS5 forecasts at 1 to 3 month lead times were assessed across seasons which defined as July-August-September (JAS), August-September-October (ASO), September-October-November (SON), and December-January-February (DJF), and El Niño-Southern Oscillation (ENSO) phases (El Niño, La Niña, Neutral), using Pearson correlation coefficient (Corr), root mean square error (RMSE), and Kling-Gupta Efficiency (KGE) metrics. Results show stronger SEAS5 skill in JAS–SON (Corr up to 0.939) compared to DJF-JFM (Corr as low as -0.208), with a robust ENSO-rainfall relationship in JJA-SON. SEAS5 performed best during El Niño, particularly in lowlands and exhibited greater variability skill during La Niña and Neutral phases. Benchmarking against a linear regression baseline showed SEAS5’s superior Corr in 76.2% of grids but higher RMSE in 60.6%. Despite limitations in mountainous regions and at longer lead times, SEAS5 offers reliable forecasts for lowland areas during JAS-SON under El Niño, supporting operational applications like drought preparedness and agricultural planning in the regions.]]>
Copyrights © 2025
