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Published November 2007 | Published
Journal Article Open

Interpretation of AIRS Data in Thin Cirrus Atmospheres Based on a Fast Radiative Transfer Model

Abstract

A thin cirrus cloud thermal infrared radiative transfer model has been developed for application to cloudy satellite data assimilation. This radiation model was constructed by combining the Optical Path Transmittance (OPTRAN) model, developed for the speedy calculation of transmittances in clear atmospheres, and a thin cirrus cloud parameterization using a number of observed ice crystal size and shape distributions. Numerical simulations show that cirrus cloudy radiances in the 800–1130-cm^(-1) thermal infrared window are sufficiently sensitive to variations in cirrus optical depth and ice crystal size as well as in ice crystal shape if appropriate habit distribution models are selected a priori for analysis. The parameterization model has been applied to the Atmospheric Infrared Sounder (AIRS) on board the Aqua satellite to interpret clear and thin cirrus spectra observed in the thermal infrared window. Five clear and 29 thin cirrus cases at nighttime over and near the Atmospheric Radiation Measurement program (ARM) tropical western Pacific (TWP) Manus Island and Nauru Island sites have been chosen for this study. A X^2-minimization program was employed to infer the cirrus optical depth and ice crystal size and shape from the observed AIRS spectra. Independent validation shows that the AIRS-inferred cloud parameters are consistent with those determined from collocated ground-based millimeter-wave cloud radar measurements. The coupled thin cirrus radiative transfer parameterization and OPTRAN, if combined with a reliable thin cirrus detection scheme, can be effectively used to enhance the AIRS data volume for data assimilation in numerical weather prediction models.

Additional Information

© 2007 American Meteorological Society. Received: January 24, 2006; Accepted: December 26, 2006. We thank Annmarie Eldering for suggesting further examination of applying the X^2- minimization method to AIRS radiances, and Jennifer M. Comstock for providing MPL raw data retrieval. This research has been supported by DOE Grant DEFG03- 00ER62904 and NOAA Grant NA03NES4400011.

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August 19, 2023
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