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.