Spatial downscaling analysis of GPM IMERG precipitation dataset based on multiscale geographically weighted regression model: a case study of the Inner Mongolia Reach of the Yellow River basin

Abstract

The Inner Mongolia Reach of the Yellow River Basin is characterized by a relative scarcity of meteorological stations. While satellite precipitation products can complement observations from meteorological stations, their limited spatial resolution restricts their efficacy in regional studies. This study utilizes the GPM IMERG precipitation dataset, considering various factors that influence the spatial distribution of precipitation, such as the Normalized Difference Vegetation Index (NDVI), elevation, slope, aspect, and topographical relief, to construct a multiscale geographically weighted regression (MGWR) model. A spatial downscaling method for the GPM IMERG precipitation dataset is proposed, and its reliability is validated through an accuracy assessment. Moreover, the scale differences in the impact of different factors on the spatial pattern of precipitation in the Inner Mongolia Reach of the Yellow River Basin are scrutinized. The results indicate that: 1) The downscaled GPM IMERG precipitation data (1 km × 1 km) exhibit enhanced accuracy compared to the pre-downscaled data (approximately 11 km × 11 km). The correlation coefficient, Bias, and RMSE of the annual precipitation data after downscaling of GPM IMERG are 0.865, 6.05%, and 68.50 mm/year, respectively. For the monthly downscaled precipitation data, the correlation coefficient, Bias, and RMSE are 0.895, 6.09%, and 16.25 mm/month, respectively. The downscaled GPM IMERG precipitation dataset exhibit high accuracy on both annual and monthly temporal scales. 2) Different factors demonstrate localized effects on precipitation in both dry and wet years. Elevation is the dominant factor influencing the spatial heterogeneity of annual precipitation. The findings from this study can provide technical support for hydrological modeling, drought monitoring, and water resource management in data-scarce areas of the Inner Mongolia Reach of the Yellow River Basin.

Evaluation of GPM IMERG Satellite Precipitation Products in Event-Based Flood Modeling over the Sunshui River Basin in Southwestern China

“…Recent research on the GPM IMERG product focuses on evaluating the performance of the rainfall product at either daily or monthly scales [19][20][21][22] and spatially downscaling the rainfall product [23][24][25]. For example, Ji (2022) assessed the performance of five satellite precipitation products, namely TRMM3B42, PERSIANN-CDR, GPM-IMERG, CMORPH, and GSMaP, in the Yarlung Zangbo River Basin, finding that GPM excelled in daily streamflow simulation, followed by CMORPH, TRMM, GSMaP, and PERSIANN [19].…”