The Efficiency of Data Assimilation

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dc.contributor.authorNearing, Grey
dc.contributor.authorYatheendradas, Soni
dc.contributor.authorCrow, Wade
dc.contributor.authorZhan, Xiwu
dc.contributor.authorLiu, Jicheng
dc.contributor.authorChen, Fan
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.contributor.otherNational Aeronautics & Space Administration (NASA)
dc.contributor.otherNASA Goddard Space Flight Center
dc.contributor.otherUniversity of Maryland College Park
dc.contributor.otherUnited States Department of Agriculture (USDA)
dc.contributor.otherNational Oceanic Atmospheric Admin (NOAA) - USA
dc.date.accessioned2023-09-28T19:35:40Z
dc.date.available2023-09-28T19:35:40Z
dc.date.issued2018
dc.description.abstractData assimilation is the application of Bayes' theorem to condition the states of a dynamical systems model on observations. Any real-world application of Bayes' theorem is approximate, and therefore, we cannot expect that data assimilation will preserve all of the information available from models and observations. We outline a framework for measuring information in models, observations, and evaluation data in a way that allows us to quantify information loss during (necessarily imperfect) data assimilation. This facilitates quantitative analysis of trade-offs between improving (usually expensive) remote sensing observing systems versus improving data assimilation design and implementation. We demonstrate this methodology on a previously published application of the ensemble Kalman filter used to assimilate remote sensing soil moisture retrievals from Advanced Microwave Scattering Radiometer for Earth (AMSR-E) into the Noah land surface model.en_US
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.citationNearing, G., Yatheendradas, S., Crow, W., Zhan, X., Liu, J., & Chen, F. (2018). The Efficiency of Data Assimilation. In Water Resources Research (Vol. 54, Issue 9, pp. 6374–6392). American Geophysical Union (AGU). https://doi.org/10.1029/2017wr020991
dc.identifier.doi10.1029/2017WR020991
dc.identifier.orcidhttps://orcid.org/0000-0001-6178-7976
dc.identifier.urihttps://ir.ua.edu/handle/123456789/11506
dc.languageEnglish
dc.language.isoen_US
dc.publisherAmerican Geophysical Union
dc.subjectdata assimilation
dc.subjectinformation theory
dc.subjectBayesian efficiency
dc.subjectsoil moisture
dc.subjectATMOSPHERE TRANSFER SCHEME
dc.subjectLAND-SURFACE SCHEME
dc.subjectSOIL-MOISTURE
dc.subjectRUNOFF
dc.subjectPARAMETERIZATION
dc.subjectINFORMATION
dc.subjectRETRIEVALS
dc.subjectMODEL
dc.subjectEnvironmental Sciences
dc.subjectLimnology
dc.subjectWater Resources
dc.titleThe Efficiency of Data Assimilationen_US
dc.typeArticle
dc.typetext
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