A Two-Step Approach to Blending GSMaP Satellite Rainfall Estimates with Gauge Observations over Australia

An approach to developing a blended satellite-rainfall dataset over Australia that could be suitable for operational use is presented. In this study, Global Satellite Mapping of Precipitation (GSMaP) satellite precipitation estimates were with station-based rain gauge data Australia, using station has not been harnessed by other products. A two-step method was utilized. First, GSMaP adjusted through multiplicative ratios gridded ordinary kriging. This step resulted in reducing dry biases, especially topography. The then the Australian Gridded Climate Dataset (AGCD) rainfall analysis, an dataset, inverse error variance weighting further remove biases. validation performed 20-year range (2001 2020) showed proposed successful; resulting displayed superior performance compared non-gauge-based datasets respect stations as well displaying more realistic patterns than AGCD areas no gauges. average mean absolute (MAE) against reduced from 0.89 0.31. greatest bias reductions obtained extreme totals and mountainous regions, provided sufficient availability. newly produced supported identification general positive north-west interior Australia.