Abstract

Surface soil moisture (SSM) is crucial for understanding the hydrological process of our earth surface. Passive microwave (PM) technique has long been the primary tool for estimating global SSM from the view of satellite, while the coarse resolution (usually >~10 km) of PM observations hampers its applications at finer scales. Although quantitative studies have been proposed for downscaling satellite PM-based SSM, very few products have been available to public that meet the qualification of 1-km resolution and daily revisit cycles under all-weather conditions. In this study, we developed one such SSM product in China with all these characteristics. The product was generated through downscaling the AMSR-E/AMSR-2 based SSM at 36-km, covering all on-orbit time of the two radiometers during 2003–2019. MODIS optical reflectance data and daily thermal infrared land surface temperature (LST) that had been gap-filled for cloudy conditions were the primary data inputs of the downscaling model, so that the “all-weather” quality was achieved for the 1-km SSM. Daily images from this developed SSM product have quasi-complete coverage over the country during April–September. For other months, the national coverage percentage of the developed product is also greatly improved against the original daily PM observations, through a specifically developed sub-model for filling the gap between seams of neighboring PM swaths during the downscaling procedure. The product is well compared against in situ soil moisture measurements from 2000+ meteorological stations, indicated by station averages of the unbiased RMSD ranging from 0.052 vol/vol to 0.059 vol/vol. Moreover, the evaluation results also show that the developed product outperforms the SMAP-Sentinel (Active-Passive microwave) combined SSM product at 1-km, with a correlation coefficient of 0.55 achieved against that of 0.40 for the latter product. This indicates the new product has great potential to be used for hydrological community, agricultural industry, water resource and environment management.

Highlights

  • Surface soil moisture (SSM) is one of the most important variables that dominate the mass and energy cycles of earth surface system

  • All above influential factors have seriously impeded the use of Active microwave (AM) radar techniques or combination of passive/active microwave datasets for producing high spatial resolution SSM products with a frequent revisit

  • Since negative effects might be brought to this validation campaign by the potentially existing heterogeneity of the validated 1-km thermal-infrared remote sensing pixels, we firstly analyzed correlations between estimated and benchmark datasets at each station, only based on satellite remote sensing observations obtained under clear sky

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Summary

Introduction

Surface soil moisture (SSM) is one of the most important variables that dominate the mass and energy cycles of earth surface system. Radiometer-2 (AMSR-2), can obtain SSM observations at a revisit interval of 1-3 days, with relatively poor native spatial resolutions of tens of kilometers. Active microwave (AM) such as radar can achieve kilometer-level and even finer resolution of observations targeting at the earth surface. This usually sacrifices the swath width of radar configuration, because of which, most satellite-based synthetic aperture radars (SAR) have an obviously longer global revisit cycle (usually longer than 5 days, e.g. Sentinel-1 SAR data) than the typical radiometers. All above influential factors have seriously impeded the use of AM radar techniques or combination of passive/active microwave datasets for producing high spatial resolution SSM products with a frequent revisit

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