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Global soil moisture bimodality in satellite observations and climate models
Author(s) -
Vilasa L.,
Miralles D. G.,
Jeu R. A. M.,
Dolman A. J.
Publication year - 2017
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2016jd026099
Subject(s) - bimodality , environmental science , satellite , latitude , water content , climate model , radiometer , climatology , estimator , earth system science , coupled model intercomparison project , probability density function , meteorology , atmospheric sciences , climate change , remote sensing , mathematics , geology , geography , statistics , geodesy , physics , geotechnical engineering , quantum mechanics , galaxy , engineering , aerospace engineering , oceanography
A new diagnostic metric based on soil moisture bimodality is developed in order to examine and compare soil moisture from satellite observations and Earth System Models. The methodology to derive this diagnostic is based on maximum likelihood estimator encoded into an iterative algorithm, which is applied to the soil moisture probability density function. This metric is applied to satellite data from the Advanced Microwave Scanning Radiometer for the Earth Observing System and global climate models data from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Results show high soil moisture bimodality in transitional climate areas and high latitudes, potentially associated with land‐atmosphere feedback processes. When comparing satellite versus climate models, a clear difference in their soil moisture bimodality is observed, with systematically higher values in the case of CMIP5 models. These differences appear related to areas where land‐atmospheric feedback may be overestimated in current climate models.