Sub-seasonal to seasonal (S2S) information holds significant socio-economic value for decision-makers relying on climate variability. While significant advancements have been made in S2S meteorological forecasting, skill variability among prediction systems persists due to differences in physical process representation and technical characteristics of the predictive systems. Traditionally, sub-seasonal systems are considered more informative than seasonal systems within their time horizons, leading to seamless communication approaches that combine systems at fixed horizons, overlooking tailored solutions to optimize forecast skill. This study investigates S2S streamflow forecasting skill across Europe’s diverse hydrological regimes, identifying optimal combination horizons for skill-informed seamless communication. Using bias-adjusted forecasts from ECMWF’s sub-seasonal (ENS-ER) and seasonal (SEAS5) systems, we evaluate streamflow forecasts to uncover spatiotemporal complementarities between the two systems. The results reveal that most European basins benefit from sub-seasonal forecasts up to 3–6 weeks ahead, while steep, snow-dominated mountain ranges, high-precipitation basins, and elevated Mediterranean areas exhibit shorter horizons of 2–4 weeks. Gains in meteorological forecast skill at short lead times (1–3 weeks) are amplified when translated into hydrological processes, extending predictability up to 6 weeks. ENS-ER-based forecasts demonstrate greater spatial homogeneity in skill during shorter lead times, while SEAS5-based forecasts excel at extended horizons. These findings highlight the potential for tailored seamless products to enhance S2S forecast utility. By integrating complementary S2S prediction systems with this diagnostic, region-dependent strategy tailored to diverse hydrological regimes, hydro-climate services can seamlessly deliver accurate, actionable, and operationally relevant information to water- and climate-dependent sectors.

Read original article

Read original article