Evaluation of a strategy for the assimilation of satellite radiance observations with the local ensemble transform Kalman filter

José A. Aravéquia, Istvan Szunyogh, Elana J. Fertig, Eugenia Kalnay, David Kuhl, Eric Kostelich

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

This paper evaluates a strategy for the assimilation of satellite radiance observations with the local ensemble transform Kalman filter (LETKF) data assimilation scheme. The assimilation strategy includes a mechanism to select the radiance observations that are assimilated at a given grid point and an ensemble-based observation bias-correction technique. Numerical experiments are carried out with a reduced (T62L28) resolution version of the model component of the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS). The observations used for the evaluation of the assimilation strategy are AMSU-A level 1B brightness temperature data from the Earth Observing System (EOS) Aqua spacecraft. The assimilation of these observations, in addition to all operationally assimilated nonradiance observations, leads to a statistically significant improvement of both the temperature and wind analysis in the Southern Hemisphere. This result suggests that the LETKF, combined with the proposed data assimilation strategy for the assimilation of satellite radiance observations, can efficiently extract information from radiance observations.

Original languageEnglish (US)
Pages (from-to)1932-1951
Number of pages20
JournalMonthly Weather Review
Volume139
Issue number6
DOIs
StatePublished - Jun 2011

Keywords

  • Data assimilation
  • Ensembles
  • Kalman filters
  • Radiation
  • Satellite observations

ASJC Scopus subject areas

  • Atmospheric Science

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