Initialisation of Land Surface Variables for Numerical Weather Prediction View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2012

AUTHORS

Patricia de Rosnay , Gianpaolo Balsamo , Clément Albergel , Joaquín Muñoz-Sabater , Lars Isaksen

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. More... »

PAGES

607-621

References to SciGraph publications

Book

TITLE

The Earth's Hydrological Cycle

ISBN

978-94-017-8788-8
978-94-017-8789-5

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-94-017-8789-5_7

DOI

http://dx.doi.org/10.1007/978-94-017-8789-5_7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1004010442


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