Assimilation of Remote Sensing Data into Earth System Models

In the Earth sciences, a transition is currently occurring in multiple fields towards an integrated Earth system approach, with applications including numerical weather prediction, hydrological forecasting, climate impact studies, ocean dynamics estimation and monitoring, and carbon cycle monitoring...

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Bibliographic Details
Main Author: Calvet, Jean-Christophe (auth)
Other Authors: De Rosnay, Patricia (auth), Penny, Stephen G. (auth)
Format: Book Chapter
Published: MDPI - Multidisciplinary Digital Publishing Institute 2019
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Online Access:Get Fullteks
DOAB: description of the publication
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020 |a books978-3-03921-641-3 
020 |a 9783039216406 
020 |a 9783039216413 
024 7 |a 10.3390/books978-3-03921-641-3  |c doi 
041 0 |a English 
042 |a dc 
100 1 |a Calvet, Jean-Christophe  |4 auth 
700 1 |a De Rosnay, Patricia  |4 auth 
700 1 |a Penny, Stephen G.  |4 auth 
245 1 0 |a Assimilation of Remote Sensing Data into Earth System Models 
260 |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2019 
300 |a 1 electronic resource (236 p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a In the Earth sciences, a transition is currently occurring in multiple fields towards an integrated Earth system approach, with applications including numerical weather prediction, hydrological forecasting, climate impact studies, ocean dynamics estimation and monitoring, and carbon cycle monitoring. These approaches rely on coupled modeling techniques using Earth system models that account for an increased level of complexity of the processes and interactions between atmosphere, ocean, sea ice, and terrestrial surfaces. A crucial component of Earth system approaches is the development of coupled data assimilation of satellite observations to ensure consistent initialization at the interface between the different subsystems. Going towards strongly coupled data assimilation involving all Earth system components is a subject of active research. A lot of progress is being made in the ocean-atmosphere domain, but also over land. As atmospheric models now tend to address subkilometric scales, assimilating high spatial resolution satellite data in the land surface models used in atmospheric models is critical. This evolution is also challenging for hydrological modeling. This book gathers papers reporting research on various aspects of coupled data assimilation in Earth system models. It includes contributions presenting recent progress in ocean-atmosphere, land-atmosphere, and soil-vegetation data assimilation. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by-nc-nd/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by-nc-nd/4.0/ 
546 |a English 
653 |a land data assimilation system 
653 |a land data assimilation 
653 |a rainfall-runoff simulation 
653 |a 4D-Var data assimilation 
653 |a total water storage 
653 |a accuracy 
653 |a ocean-atmosphere assimilation 
653 |a precipitation 
653 |a Earth system models 
653 |a numerical weather prediction 
653 |a fluorescence 
653 |a GRACE 
653 |a MCA analysis 
653 |a weakly coupled data assimilation 
653 |a GPM IMERG 
653 |a atmospheric models 
653 |a rainfall correction 
653 |a remote sensing 
653 |a microwave remote sensing 
653 |a SMAP 
653 |a land surface modeling 
653 |a bending angle 
653 |a floods soil moisture 
653 |a vegetation 
653 |a GPSRO 
653 |a WRF 
653 |a merged CMORPH 
653 |a land surface model 
653 |a temperature 
653 |a 4D-Var 
653 |a data assimilation 
653 |a data-driven methods 
653 |a GSI 
653 |a radio occultation data 
653 |a rainfall 
653 |a soil moisture 
653 |a sea level anomaly 
653 |a total cloud cover 
653 |a land surface models 
653 |a Mediterranean basin 
653 |a interpolation 
653 |a sea surface height 
653 |a drought 
653 |a TRMM 3B42 
653 |a analog data assimilation 
653 |a ocean models 
856 4 0 |a www.oapen.org  |u https://mdpi.com/books/pdfview/book/1818  |7 0  |z Get Fullteks 
856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/41454  |7 0  |z DOAB: description of the publication