Advancing Earth Surface Representation via Enhanced Use of Earth Observations in Monitoring and Forecasting Applications

The representation of the Earth's surface in global monitoring and forecasting applications is moving towards capturing more of the relevant processes, while maintaining elevated computational efficiency and therefore a moderate complexity. These schemes are developed and continuously improved...

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Bibliographic Details
Main Author: Ruston, Benjamin (auth)
Other Authors: Karbou, Fatima (auth), Trigo, Isabel F. (auth), Balsamo, Gianpaolo (auth), Escobar, Vanessa M. (auth), Drusch, Matthias (auth), Mecklenburg, Susanne (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 books978-3-03921-065-7 
020 |a 9783039210640 
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024 7 |a 10.3390/books978-3-03921-065-7  |c doi 
041 0 |a English 
042 |a dc 
100 1 |a Ruston, Benjamin  |4 auth 
700 1 |a Karbou, Fatima  |4 auth 
700 1 |a Trigo, Isabel F.  |4 auth 
700 1 |a Balsamo, Gianpaolo  |4 auth 
700 1 |a Escobar, Vanessa M.  |4 auth 
700 1 |a Drusch, Matthias  |4 auth 
700 1 |a Mecklenburg, Susanne  |4 auth 
245 1 0 |a Advancing Earth Surface Representation via Enhanced Use of Earth Observations in Monitoring and Forecasting Applications 
260 |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2019 
300 |a 1 electronic resource (262 p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a The representation of the Earth's surface in global monitoring and forecasting applications is moving towards capturing more of the relevant processes, while maintaining elevated computational efficiency and therefore a moderate complexity. These schemes are developed and continuously improved thanks to well instrumented field-sites that can observe coupled processes occurring at the surface-atmosphere interface (e.g., forest, grassland, cropland areas and diverse climate zones). Approaching global kilometer-scale resolutions, in situ observations alone cannot fulfil the modelling needs, and the use of satellite observation becomes essential to guide modelling innovation and to calibrate and validate new parameterization schemes that can support data assimilation applications. In this book, we review some of the recent contributions, highlighting how satellite data are used to inform Earth surface model development (vegetation state and seasonality, soil moisture conditions, surface temperature and turbulent fluxes, land-use change detection, agricultural indicators and irrigation) when moving towards global km-scale resolutions. 
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 direct and inverse methods 
653 |a absorption coefficient 
653 |a emissivity 
653 |a land-surface model 
653 |a n/a 
653 |a variational retrieval 
653 |a temporal autocorrelation 
653 |a Bayesian bias correction 
653 |a hyperspectral 
653 |a infrared 
653 |a BRDF 
653 |a satellite rainfall 
653 |a MCD43C1 
653 |a penetration depth 
653 |a RTTOV 
653 |a earth-observations 
653 |a earth system modelling 
653 |a representative depth 
653 |a land 
653 |a Changjiang (Yangtze) estuary 
653 |a CDOM 
653 |a soil moisture 
653 |a surface 
653 |a Maqu network 
653 |a surface soil moisture 
653 |a MODIS 
653 |a soil effective temperature 
653 |a GOCI 
653 |a microwave remote sensing 
653 |a rain gauge 
653 |a QAA inversion 
653 |a broadband emissivity 
653 |a radiation 
653 |a surface parameters 
653 |a satellite data 
653 |a East Africa 
856 4 0 |a www.oapen.org  |u https://mdpi.com/books/pdfview/book/1510  |7 0  |z Get Fullteks 
856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/40380  |7 0  |z DOAB: description of the publication