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Assimilation of Meteosat radiance data within the 4D‐Var system at ECMWF: Data quality monitoring, bias correction and single‐cycle experiments
Author(s) -
Munro Rosemary,
Köpken Christina,
Kelly Graeme,
Thépaut JeanNoël,
Saunders Roger
Publication year - 2004
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1256/qj.02.229
Subject(s) - radiance , environmental science , geostationary orbit , data assimilation , remote sensing , meteorology , brightness temperature , sky brightness , data quality , geostationary operational environmental satellite , context (archaeology) , satellite , troposphere , brightness , sky , geography , physics , metric (unit) , operations management , astronomy , optics , economics , archaeology
This paper describes the direct assimilation of water vapour (WV) clear‐sky radiance (CSR) data from geostationary satellites within the context of the ECMWF four‐dimensional variational assimilation (4D‐Var) system. The assimilation of Meteosat–7 WV CSR data became operational on 9 April 2002. As 4D‐Var includes a time dimension, the high temporal resolution of the geostationary radiance data can be exploited to provide information not only on the upper‐tropospheric humidity but also on the upper‐tropospheric wind field. The data assimilated have a spatial resolution of approximately 80 km and a time resolution of 1 hour. Extensive pre‐operational monitoring of the CSR data has been carried out, showing a systematic warm bias of approximately 2–3 K in the Meteosat WV CSR data compared to radiances simulated from model first‐guess fields. The systematic biases between the brightness temperatures derived from the model and the observations are investigated and compared to other satellite radiance data. For assimilation purposes this is accounted for by using a bias correction based on a statistical regression. The monitoring also shows contamination of certain time slots caused by intruding solar stray light and a certain degree of residual cloud contamination present in the CSR. Data quality control is introduced to exclude affected data. Initial single‐cycle 3D‐Var with first guess at appropriate time and 4D‐Var experiments demonstrate both the direct and indirect effects of the Meteosat WV CSR data on the model fields, particularly of humidity and wind. The operational implementation of the assimilation of the Meteosat WV CSR data, including results from pre‐operational experiments and forecast impacts, is discussed in a companion paper. Copyright © 2004 Royal Meteorological Society