Forecasting water temperature in lakes and reservoirs using seasonal climate prediction

Seasonal climate forecasts produce probabilistic predictions of meteorological variables for subsequent months. This provides a potential resource to predict the influence seasonal anomalies on surface water balance in catchments and hydro-thermodynamics related bodies (e.g., lakes or reservoirs). Obtaining impact discharge temperature) requires link between models simulating hydrology lake hydrodynamics thermal regimes. However, this remains challenging stakeholders scientific community, mainly due nature these predictions. In paper, we introduce feasible, robust, open-source workflow integrating with hydrologic generate temperature profiles. The has been designed be applicable any catchment associated reservoir, is optimized study four catchment-lake systems help their proactive management. We assessed performance resulting by comparing them (pseudo)observations (reanalysis). Precisely, analysed historical using data sample past reanalysis obtain information about skill (performance quality) forecast system particular events. used current (SEAS5) (ERA5) European Centre Medium Range Weather Forecasts (ECMWF). found that limited predictability at time-scales over locations case studies (Europe South Australia), exhibited none low (skill) atmospheric considered. Nevertheless, present some all but one study. Moreover, had higher natural than reservoirs, which means human control relevant factor affecting predictability, increases depth studies. Further investigation into skillful should aim identify extent consequence inertia (i.e., lead-in conditions).