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Initialisation of Land Surface Variables for Numerical Weather Prediction

  • Patricia de Rosnay
  • Gianpaolo Balsamo
  • Clément Albergel
  • Joaquín Muñoz-Sabater
  • Lars Isaksen
Chapter
Part of the Space Sciences Series of ISSI book series (SSSI, volume 46)

Abstract

Land surface processes and their initialisation are of crucial importance for Numerical Weather Prediction (NWP). Current land data assimilation systems used to initialise NWP models include snow depth analysis, soil moisture analysis, soil temperature and snow temperature analysis. This paper gives a review of different approaches used in NWP to initialise land surface variables. It discusses the observation availability and quality, and it addresses the combined use of conventional observations and satellite data. Based on results from the European Centre for Medium-Range Weather Forecasts (ECMWF), results from different soil moisture and snow depth data assimilation schemes are shown. Both surface fields and low-level atmospheric variables are highly sensitive to the soil moisture and snow initialisation methods. Recent developments of ECMWF in soil moisture and snow data assimilation improved surface and atmospheric forecast performance.

Keywords

Land surface Data assimilation Numerical weather prediction Soil moisture Snow 

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Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • Patricia de Rosnay
    • 1
  • Gianpaolo Balsamo
    • 1
  • Clément Albergel
    • 1
  • Joaquín Muñoz-Sabater
    • 1
  • Lars Isaksen
    • 1
  1. 1.European Centre for Medium-Range Weather ForecastsReadingUK

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