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Titlebook: Remote Sensing and Climate Modeling: Synergies and Limitations; Martin Beniston,Michel M. Verstraete Book 2001 Springer Science+Business M

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书目名称Remote Sensing and Climate Modeling: Synergies and Limitations
编辑Martin Beniston,Michel M. Verstraete
视频video
丛书名称Advances in Global Change Research
图书封面Titlebook: Remote Sensing and Climate Modeling: Synergies and Limitations;  Martin Beniston,Michel M. Verstraete Book 2001 Springer Science+Business M
描述1 2 Michel M. VERSTRAETE and Martin BENISTON 1 Space Applications Institute, EC Joint Research Centre, Ispra, Italy 2 Department of Geography, University of Fribourg, Switzerland This volume contains the proceedings ofthe workshop entitled “Satellite Remote Sensing and Climate Simulations: Synergies and Limitations” that took place in Les Diablerets, Switzerland, September 20–24, 1999. This international scientific conference aimed at addressing the current and pot- tial role of satellite remote sensing in climate modeling, with a particular focus on land surface processes and atmospheric aerosol characterization. Global and regional circulation models incorporate our knowledge ofthe dynamics ofthe Earth‘s atmosphere. They are used to predict the evolution of the weather and climate. Mathematically, this system is represented by a set ofpartial differential equations whose solution requires initial and bo- dary conditions. Limitations in the accuracy and geographical distribution of these constraints, and intrinsic mathematical sensitivity to these conditions do not allow the identification of a unique solution (prediction). Additional observations on the climate system are thus us
出版日期Book 2001
关键词Aerosol; Albedo; Climatology; Scale; Snow; climate change; global circulation; remote sensing; vegetation
版次1
doihttps://doi.org/10.1007/0-306-48149-9
isbn_softcover978-90-481-5648-1
isbn_ebook978-0-306-48149-9Series ISSN 1574-0919 Series E-ISSN 2215-1621
issn_series 1574-0919
copyrightSpringer Science+Business Media Dordrecht 2001
The information of publication is updating

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Snow Cover Fraction In A General Circulation Model,ed snow depth and remote sensing observations of snow cover data. A 3-dimensional Echam4 simulation showed that this modification raises the SCF by up to approximately 20%, mainly in areas with a relatively thin snow cover..The comparison between remotely sensed and simulated mean monthly surface al
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Specification of surface characteristics for use in a high resolution regional climate model: on thity, the evapotranspiration efficiency, the snow masking depth, while the soil type determines the soil thermal conductivity and specific heat, thus determining the behaviour of the momentum and sensible heat fluxes, as well as the evapotranspiration at the surface. This in turn may have significant
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