Gridded Hydroclimatic Datasets over the United States (2006–2021)

This study focuses on generating gridded hydroclimatic datasets from station-based ob-servations using spatial interpolation techniques and evaluating their performance againstERA5 reanalysis data. Five variables—air temperature, precipitation, relative humidity,soil temperature, and soil moisture—were analyzed over the United States for the period2006–2021. Interpolation methods including Inverse Distance Weighting (IDW) and mul-tiple Kriging variants were implemented. Model performance was assessed using RMSE,correlation, and statistical distribution metrics. Seasonal analysis was also conducted tounderstand temporal variability. Results indicate that IDW provides the most consistentperformance across variables.