A Space-Time Statistical Model for Post-Processing of Daily Precipitation Forecasts

This dataset provides gridded daily observed precipitation and raw forecast precipitation for the monsoon season (June–September), which were used to implement a Hierarchical Bayesian Post-Processing (HBPP) framework for bias correction and spatial downscaling of precipitation forecasts over the Brahmaputra River Basin (BRB; JJAS, 2020-2022) and Narmada River Basin (NRB; JA, 2000-2014), India. The dataset includes: (i) gridded daily observed precipitation sourced from the India Meteorological Department (IMD) at each basin grid cell for five clusters in the BRB (West, Dhubri, Guwahati, Neamatighat, and Dibrugarh) and four clusters in the NRB (Mandleshwar, Handia, Hoshangabad, and Sandiya); (ii) raw gridded forecast precipitation at 1-day, 2-day, and 3-day lead times for both basins; and (iii) grid cell latitude–longitude coordinate files for both basins. These data were processed to generate the gridded precipitation inputs and forecast fields used in the post-processing framework presented in this study.