Quarterly Journal of the Royal Meteorological Society · 2006 · 263 citations · 11 references
Natural SciencesEarth SciencesMeteorologyAtmospheric RadiationAtmospheric ScienceWeather ForecastingAtmospheric Sounding From SatellitesCloud Remote SensingData AssimilationInfrared Remote SensingNumerical Weather Prediction Data AssimilationSatellite SensorsAssimilation ErrorsCloud Contamination CorrectionCloud Contamination DetectionForecast Performance EvaluationMeasurement Bias CorrectionMicrowave SoundingRadianceSatellite Radiance Assimilation
Abstract The development of an assimilation system for radiance data from the Atmospheric InfraRed Sounder (AIRS) is described, in particular the identification of cloud contamination, bias correction and the characterization of errors in the measured radiances and radiative‐transfer model. The results of assimilation experiments are presented. These show that a conservative use of AIRS radiance data (in a system already extensively observed with other satellite data) results in a small, but consistent, improvement in the quality of analyses and forecasts. Larger impacts of AIRS are found in hypothetical experiments that test the use of radiances from only a single sounding instrument. In these, the use of AIRS is found to outperform the use of data either from a single Advanced Microwave Sounding Unit‐A (AMSU‐A) or from a single High‐resolution InfraRed Sounder (HIRS). In this hypothetical context the relative forecast performance of each sensor is found to correlate with the size and vertical scale of increments caused by the assimilation of the radiances. Copyright © 2006 Royal Meteorological Society.
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Florence Rabier, Heikki Järvinen, E. Klinker et al. · Quarterly Journal of the Royal Meteorological Society · 2000 · 903 citations