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Remote Sensing and Climate Modeling: Synergies and Limitations

  • Book
  • © 2001

Overview

Editors:
  1. Martin Beniston

    1. Department of Geography, University of Fribourg, Switzerland

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    You can also search for this editor in PubMed   Google Scholar

  2. Michel M. Verstraete

    1. Space Applications Institute, Joint Research Centre, Ispra (VA), Italy

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Advances in Global Change Research (AGLO, volume 7)

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Table of contents (14 chapters)

  1. Front Matter

    Pages i-3
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  2. A global vegetation index for SeaWiFS: Design and applications

    • N. Gobron, F. Mélin, B. Pinty, M. M. Verstraete, J.-L. Widlowski, G. Bucini
    Pages 5-21

  3. Modeling sensible heat flux using estimates of soil and vegetation temperatures: the HEIFE and IMGRASS experiments

    • Li Jia, Massimo Menenti, Zhongbo Su, Zhao-Liang Li, Vera Djepa, Jiemin Wang
    Pages 23-49

  4. Exploitation of Surface Albedo Derived From the Meteosat Data to Characterize Land Surface Changes

    • Bernard Pinty, Michel M. Verstraete, Nadine Gobron, Fausto Roveda, Yves Govaerts, John V. Martonchik et al.
    Pages 51-67

  5. Towards a Climatology of Australian Land Surface Albedo for use in Climate Models

    • Ian F. Grant
    Pages 69-84

  6. Collocated surface and satellite observations as constraints for Earth radiation budget simulations with global climate models

    • Martin Wild
    Pages 85-102

  7. How well do aerosol retrievals from satellites and representation in global circulation models match ground-based AERONET aerosol statistics?

    • S. Kinne, B. Holben, T. Eck, A. Smirnov, O. Dubovik, I. Slutsker et al.
    Pages 103-158

  8. Remote Sensing of Snow and Characterization of Snow Albedo for Climate Simulations

    • Anne W. Nolin, Allan Frei
    Pages 159-180

  9. Using the Special Sensor Microwave Imager to Monitor Surface Wetness and Temperature

    • Alan Basist, Claude Williams
    Pages 181-202

  10. Snow Cover Fraction In A General Circulation Model

    • A. Roesch, M. Wild, A. Ohmura
    Pages 203-232

  11. Boreal Forest Fire Regimes And Climate Change

    • B. J. Stocks, B. M. Wotton, M. D. Flannigan, M. A. Fosberg, D. R. Cahoon, J. G. Goldammer
    Pages 233-246

  12. Specification of surface characteristics for use in a high resolution regional climate model: on the role of glaciers in the swiss alps

    • Stéphane Goyette, Claude Collet, Martin Beniston
    Pages 247-271

  13. Using Satellite Data Assimilation to Infer Global Soil Moisture Status and Vegetation Feedback to Climate

    • Wolfgang Knorr, Jan-Peter Schulz
    Pages 273-306

  14. The Use of Remotely-Sensed Data for the Estimation of Energy Balance Components in a Mountainous Catchment Area

    • P. A. Brivio, R. Colombo, M. Meroni
    Pages 307-327

  15. Integration of operationally available remote sensing and synoptic data for surface energy balance modelling and environmental applications on the regional scale

    • Stefan Niemeyer, Jürgen Vogt
    Pages 329-343

  16. Back Matter

    Pages 345-345
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Keywords

About this book

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 used to constrain the forecasts of the mathematical model to remain close to the observed state ofthe system.

Editors and Affiliations

  • Department of Geography, University of Fribourg, Switzerland

    Martin Beniston

  • Space Applications Institute, Joint Research Centre, Ispra (VA), Italy

    Michel M. Verstraete

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