Seasonal forecasts provide valuable insights into upcoming conditions, offering forecast horizons of up to seven months. However, uncorrected seasonal forecasts often exhibit substantial biases and drifts, when compared to reference data like, e.g., ERA5. This makes post-processing essential for their use in analysis and downstream modelling. This dataset provides bias-corrected and downscaled seasonal forecasts from the ECMWF SEAS5 system for precipitation and 2-meter temperature, covering the global land surface at 0.25° resolution. Using the Bias Correction and Spatial Disaggregation (BCSD) method, forecasts are corrected for biases and temporal drifts and include all SEAS5 ensemble members over the full hindcast period (1981–2016) and until 2024. The dataset supports lead times up to seven months and is suitable for a wide range of applications in water, energy, and agricultural sectors. Forecast quality has been evaluated using Brier Skill Scores and CRPSS, showing strong skill for temperature across most regions and for precipitation in tropical and humid areas.

This dataset group contains the regionalised seasonal forecasts for the SaWaM study domain D04 (Catamayo-Chira Basin, Ecuador and Peru). The data is based on the latest seasonal forecast product SEAS5 from the European Centre for Medium Range Weather Forecast (ECMWF), which has been Bias-Corrected and Spatially Disaggregated (BCSD) towards the ERA5-Land high-resolution replay of the land component of ECMWF's ERA5 climate reanalysis. It hence provides a temporally and spatially consistent set of land surface variables for driving e.g. hydrological models or assessing the regional forecast skill of seasonal forecasts. Currently, the dataset group contains daily and monthly ensemble (re)forecasts during the period 1981 to 2019. In particular, each forecast with 25 (before 2017) and 51 (since 2017) ensemble members contains daily and monthly forecasts for precipitation, maximum, minimum, and average temperature as well as radiation from the issue date for the next 215 days.

This dataset group contains the regionalised seasonal forecasts for the SaWaM study domain D02 (Rio São Francisco, Brazil). The data is based on the latest seasonal forecast product SEAS5 from the European Centre for Medium Range Weather Forecast (ECMWF), which has been Bias-Corrected and Spatially Disaggregated (BCSD) towards the ERA5-Land high-resolution replay of the land component of ECMWF's ERA5 climate reanalysis. It hence provides a temporally and spatially consistent set of land surface variables for driving e.g. hydrological models or assessing the regional forecast skill of seasonal forecasts. Currently, the dataset group contains daily and monthly ensemble (re)forecasts during the period 1981 to 2019. In particular, each forecast with 25 (before 2017) and 51 (since 2017) ensemble members contains daily and monthly forecasts for precipitation, maximum, minimum, and average temperature as well as radiation from the issue date for the next 215 days.

This dataset group contains the regionalised seasonal forecasts for the SaWaM study domain D03 (Tekeze-Atbara and Blue Nile Basins, Sudan and Ethiopia). The data is based on the latest seasonal forecast product SEAS5 from the European Centre for Medium Range Weather Forecast (ECMWF), which has been Bias-Corrected and Spatially Disaggregated (BCSD) towards the ERA5-Land high-resolution replay of the land component of ECMWF's ERA5 climate reanalysis. It hence provides a temporally and spatially consistent set of land surface variables for driving e.g. hydrological models or assessing the regional forecast skill of seasonal forecasts. Currently, the dataset group contains daily and monthly ensemble (re)forecasts during the period 1981 to 2019. In particular, each forecast with 25 (before 2017) and 51 (since 2017) ensemble members contains daily and monthly forecasts for precipitation, maximum, minimum, and average temperature as well as radiation from the issue date for the next 215 days.

This dataset group contains the regionalised seasonal forecasts for the SaWaM study domain D02 (Rio São Francisco, Brazil). The data is based on the latest seasonal forecast product SEAS5 from the European Centre for Medium Range Weather Forecast (ECMWF), which has been Bias-Corrected and Spatially Disaggregated (BCSD) towards the ERA5-Land high-resolution replay of the land component of ECMWF's ERA5 climate reanalysis. It hence provides a temporally and spatially consistent set of land surface variables for driving e.g. hydrological models or assessing the regional forecast skill of seasonal forecasts. Currently, the dataset group contains daily and monthly ensemble (re)forecasts during the period 1981 to 2019. In particular, each forecast with 25 (before 2017) and 51 (since 2017) ensemble members contains daily and monthly forecasts for precipitation, maximum, minimum, and average temperature as well as radiation from the issue date for the next 215 days.

This dataset group contains the regionalised seasonal forecasts for the SaWaM study domain D03 (Tekeze-Atbara and Blue Nile Basins, Sudan and Ethiopia). The data is based on the latest seasonal forecast product SEAS5 from the European Centre for Medium Range Weather Forecast (ECMWF), which has been Bias-Corrected and Spatially Disaggregated (BCSD) towards the ERA5-Land high-resolution replay of the land component of ECMWF's ERA5 climate reanalysis. It hence provides a temporally and spatially consistent set of land surface variables for driving e.g. hydrological models or assessing the regional forecast skill of seasonal forecasts. Currently, the dataset group contains daily and monthly ensemble (re)forecasts during the period 1981 to 2019. In particular, each forecast with 25 (before 2017) and 51 (since 2017) ensemble members contains daily and monthly forecasts for precipitation, maximum, minimum, and average temperature as well as radiation from the issue date for the next 215 days.

This dataset group contains the regionalised seasonal forecasts for the SaWaM study domain D04 (Catamayo-Chira Basin, Ecuador and Peru). The data is based on the latest seasonal forecast product SEAS5 from the European Centre for Medium Range Weather Forecast (ECMWF), which has been Bias-Corrected and Spatially Disaggregated (BCSD) towards the ERA5-Land high-resolution replay of the land component of ECMWF's ERA5 climate reanalysis. It hence provides a temporally and spatially consistent set of land surface variables for driving e.g. hydrological models or assessing the regional forecast skill of seasonal forecasts. Currently, the dataset group contains daily and monthly ensemble (re)forecasts during the period 1981 to 2019. In particular, each forecast with 25 (before 2017) and 51 (since 2017) ensemble members contains daily and monthly forecasts for precipitation, maximum, minimum, and average temperature as well as radiation from the issue date for the next 215 days.

This dataset group contains the regionalised seasonal forecasts for the SaWaM study domain D01 (Karun Basin, Iran). The data is based on the latest seasonal forecast product SEAS5 from the European Centre for Medium Range Weather Forecast (ECMWF), which has been Bias-Corrected and Spatially Disaggregated (BCSD) towards the ERA5-Land high-resolution replay of the land component of ECMWF's ERA5 climate reanalysis. It hence provides a temporally and spatially consistent set of land surface variables for driving e.g. hydrological models or assessing the regional forecast skill of seasonal forecasts. Currently, the dataset group contains daily and monthly ensemble (re)forecasts during the period 1981 to 2019. In particular, each forecast with 25 (before 2017) and 51 (since 2017) ensemble members contains daily and monthly forecasts for precipitation, maximum, minimum, and average temperature as well as radiation from the issue date for the next 215 days.

This dataset group contains the regionalised seasonal forecasts for the SaWaM study domain D01 (Karun Basin, Iran). The data is based on the latest seasonal forecast product SEAS5 from the European Centre for Medium Range Weather Forecast (ECMWF), which has been Bias-Corrected and Spatially Disaggregated (BCSD) towards the ERA5-Land high-resolution replay of the land component of ECMWF's ERA5 climate reanalysis. It hence provides a temporally and spatially consistent set of land surface variables for driving e.g. hydrological models or assessing the regional forecast skill of seasonal forecasts. Currently, the dataset group contains daily and monthly ensemble (re)forecasts during the period 1981 to 2019. In particular, each forecast with 25 (before 2017) and 51 (since 2017) ensemble members contains daily and monthly forecasts for precipitation, maximum, minimum, and average temperature as well as radiation from the issue date for the next 215 days.