Keywords: Atmospheric sciences 、 Pearson product-moment correlation coefficient 、 Water content 、 Irrigation scheduling 、 Environmental science 、 Brightness temperature 、 Data assimilation 、 Precipitation 、 Calibration (statistics) 、 Satellite
Description: Information about the spatiotemporal variability of soil moisture is critical for many purposes, including monitoring of hydrologic extremes, irrigation scheduling, and prediction of agricultural yields. We evaluated the temporal dynamics of 18 state-of-the-art (quasi-) global near-surface soil moisture products, including six based on satellite retrievals, six based on models without satellite data assimilation (referred to hereafter as “open-loop” models), and six based on models that assimilate satellite soil moisture or brightness temperature data …
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Howard Zebker, Chris Ruf, Charles Elachi, Fawwaz T. Ulaby, Jakob Van Zyl, Kamal Sarabandi, David G. Long, William J. Blackwell, Adrian K. Fung, Microwave Radar and Radiometric Remote Sensing ,(2013)