Analysis of Seasonal Climate and Streamflow Forecast Performance for Mainland Southeast Asia

Abstract Seasonal forecast can be part of an early warning system that contributes to anticipatory management in climate-impacted sectors by providing spatiotemporal information of climate-related anomalies in the near future. This study first examined the European Centre for Medium-Range Weather Forecasts (ECMWF) Seasonal Forecasting System, version 5 (SEAS5), seasonal forecast skill over mainland Southeast Asia (MSEA). We evaluated the SEAS5 skill of temperature and precipitation for 30 years (1985–2014) against two reference model datasets, WATCH Forcing Data ERA5 (WFDE5) and Asian Precipitation–Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), using probabilistic forecast verification skill metrics at grid cells for each month. Subsequently, SEAS5 was used to force the Variable Infiltration Capacity (VIC) hydrological model to predict streamflow. These hydrological results were compared against the WFDE5-driven streamflow reanalysis and observed station data, using the same probabilistic skill statistics. The results show a prediction potential for temperature beyond 2 months in advance. The skills of precipitation and streamflow forecasting are limited to the first month, with a strong seasonal and regional dependence. The model chain exhibits strong forecast skill during the premonsoon (April–May) and postmonsoon (October–November), which are arguably the greatest practical utility period. Conversely, low skill is observed during the monsoon season (June–August). In eastern and southern MSEA, i.e., in eastern Thailand, Cambodia, Vietnam, and Malaysia, considerable skill levels are found. Year-to-year precipitation tercile plots demonstrate skill in predicting anomalous seasonal conditions associated with El Niño–Southern Oscillation (ENSO). Overall, SEAS5 and derived hydrological forecasts show useful skill that can potentially be used for hydrological and agricultural anticipatory management. Significant Statement This study aims to evaluate the ensemble seasonal forecasting [European Centre for Medium-Range Weather Forecasts (ECMWF) Seasonal Forecasting System, version 5 (SEAS5)] performance in mainland Southeast Asia. We analyzed monthly precipitation and temperature forecasts and assessed how their skill integrates into hydrological anomalies, as simulated by the Variable Infiltration Capacity (VIC) model. Our findings present that SEAS5 forecasting performance is regionally and temporally dependent. SEAS5 has the potential to apply temperature forecasting for more than 2-month lead time for anticipatory strategic planning. Skillful 1-month lead time of precipitation and hydrology during key months offers valuable guidance for short-term operational planning. Additionally, the analysis presents a good skill for detecting anomalous precipitation during El Niño–Southern Oscillation (ENSO) periods. The study highlights the potential of VIC-SEAS5 for the development of operational early warning systems.