Sources of skill in lake temperature, discharge and ice-off seasonal forecasting tools
نویسندگان
چکیده
Abstract. Despite high potential benefits, the development of seasonal forecasting tools in water sector has been slower than other sectors. Here we assess skill for lakes and reservoirs set up at four sites Australia Europe. These consist coupled hydrological catchment lake models forced with meteorological forecast ensembles to provide probabilistic predictions anomalies discharge, temperature ice-off. Successful implementation requires a rigorous assessment tools' predictive an apportionment predictability between legacy effects input forcing data. To this end, were two datasets from European Centre Medium-Range Weather Forecasts (ECMWF), system, SEAS5, 3-month lead times ERA5 reanalysis. Historical was assessed by comparing both model outputs, i.e. hindcasts (forced SEAS5), pseudo-observations ERA5). The generally low although higher reference hindcasts, pseudo-observations, some certain combinations season variable. SEAS5 showed less hindcasts. In fact, skilful identified selected seasons variables not always synchronous raising questions on source predictability. A sensitivity analyses that most originates effects, during winter spring Norway coming over target season. When skilful, additional interaction skill. We conclude forecasts ensemble boundary conditions resampled historical meteorology are currently likely yield higher-quality cases.
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ژورنال
عنوان ژورنال: Hydrology and Earth System Sciences
سال: 2023
ISSN: ['1607-7938', '1027-5606']
DOI: https://doi.org/10.5194/hess-27-1361-2023