A Spatial Downscaling Methodology for GRACE Total Water Storage Anomalies Using GPM IMERG Precipitation Estimates

Alexandra Gemitzi,Nikos Koutsias,Venkataraman Lakshmi

doi:10.3390/rs13245149

Abstract

A downscaling framework for coarse resolution Gravity Recovery and Climate Experiment (GRACE) Total Water Storage Anomaly (TWSA) data is described, exploiting the observations of precipitation from the Global Precipitation Measurement (GPM) mission, using the Integrated Multi-satellite Retrievals for GPM (IMERG). Considering that the major driving force for changes in TWS is precipitation, we tested our hypothesis that coarse resolution, i.e., 1°, GRACE TWSA can be effectively downscaled to 0.1° using GPM IMERG data. The algorithm for the downscaling process comprises the development of a regression equation at the coarse resolution between the GRACE and GPM IMERG data, which is then applied at the finer resolution with a subsequent residual correction procedure. An ensemble of GRACE data from three processing centers, i.e., GFZ, JPL and CSR, was used for the time period from June 2018 until March 2021. To verify our downscaling methodology, we applied it with GRACE data from 2005 to 2015, and we compared it against modeled TWSA from two independent datasets in the Thrace and Thessaly regions in Greece for the same period and found a high performance in all examined metrics. Our research indicates that the downscaled GRACE observations are comparable to the TWSA estimated with hydrological modeling, thus highlighting the potential of GRACE data to contribute to the improvement of hydrological model performance, especially in ungauged basins.

Highlights

While most previous downscaling methods of Gravity Recovery and Climate Experiment (GRACE) have relied on modeled fine-resolution information [15,38], in the present work, we evaluated the downscaling ability of a sole remotely sensed product, i.e., Global Precipitation Measurement (GPM)-Integrated Multisatellite Retrievals for GPM (IMERG), to produce a simple yet reliable downscaling framework for GRACE TWS changes
The cross-correlation analysis of the GRACE Total Water Storage Anomaly (TWSA) and was conducted at the pixel level, after resampling from its native was conducted at the pixel level, after resampling GRACE TWSA from its native 11°◦ at at 0.1°, 0.1◦, to match the resolution of Results of cross-correlation analysis at various to match the resolution of GPM IMERG
With the increasing information offered from remote sensing observations, these models can be improved, provided that remote sensing data are consistent with the spatial and temporal scales required for these hydrological predictions

Summary

Introduction

Acquiring realistic forecasts and sufficiently accurate estimates of the hydrological variables under various future climate and land-use change scenarios requires a rigorous calibration process [1,2], which in turn relies on a proper dataset of hydrological observations, either in situ or from remote sensing. Ground monitoring networks for surface waters (i.e., river discharge monitoring stations, precipitation gauges and lake levels) are present in many parts of the world like North America and Europe and provide precious hydrological information. They lack the necessary spatial density in large areas like Africa, South America and Asia, to capture the heterogeneity of hydrological variability [3]. Remote sensing has been providing unprecedented hydrological information globally over the last few decades, at spatial and temporal resolutions of practical use [3], which can be assimilated into hydrological models

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Results

Conclusion