AIMERG: a new Asian precipitation dataset (0.1°/half-hourly, 2000–2015) by calibrating the GPM-era IMERG at a daily scale using APHRODITE

Summary

This study presents AIMERG, an improved satellite-derived precipitation dataset for Asia developed by applying a daily-scale calibration algorithm (DSTDCA) to IMERG satellite data using the higher-resolution APHRODITE ground observation network. The authors demonstrate that daily-scale calibration substantially reduces both systematic biases and random errors in precipitation estimates compared to the existing monthly-scale approach, with particular improvements over topographically complex regions. The resulting dataset offers enhanced spatio-temporal resolution and accuracy for hydrological, water resource, and climate modelling applications across Asia.

UK applicability

This dataset and calibration methodology are geographically specific to Asia and would have limited direct applicability to UK precipitation measurement systems, which benefit from dense ground-based radar and gauge networks. However, the methodological approach of using high-resolution ground observations to calibrate satellite data at finer temporal scales could inform refinement of UK satellite precipitation products or support calibration of data for poorly gauged international regions relevant to UK climate and water security research.

Key measures

Systematic biases and random errors in precipitation estimates; spatio-temporal resolution (0.1° grid, half-hourly temporal frequency); performance metrics across mainland China and topographically complex regions

Outcomes reported

The study developed AIMERG, a calibrated satellite precipitation dataset for Asia (0.1°/half-hourly, 2000–2015) by applying a novel daily-scale calibration algorithm to IMERG data using APHRODITE ground observations. The dataset demonstrated improved accuracy in precipitation estimates across varying spatio-temporal scales compared to the original uncalibrated IMERG product.

Topic tags