Global soil moisture bimodality in satellite observations and climate models

L. Vilasa, D. G. Miralles, R. A.M. De Jeu, A. J. Dolman

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)4299-4311
Number of pages13
JournalJournal of Geophysical Research
Volume122
Issue number8
DOIs
Publication statusPublished - 2017

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Climate models
soil moisture
climate models
satellite observation
Soil moisture
climate modeling
soil water
Satellites
Earth Observing System
Earth (planet)
Feedback
radiometers
EOS
Radiometers
probability density function
probability density functions
estimators
radiometer
polar regions
Probability density function

Cite this

Vilasa, L. ; Miralles, D. G. ; De Jeu, R. A.M. ; Dolman, A. J. / Global soil moisture bimodality in satellite observations and climate models. In: Journal of Geophysical Research. 2017 ; Vol. 122, No. 8. pp. 4299-4311.
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Global soil moisture bimodality in satellite observations and climate models. / Vilasa, L.; Miralles, D. G.; De Jeu, R. A.M.; Dolman, A. J.

In: Journal of Geophysical Research, Vol. 122, No. 8, 2017, p. 4299-4311.

Research output: Contribution to JournalArticleAcademicpeer-review

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AB - 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.

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