Validating IASI Temperature and Moisture Sounding Retrievals over East Asia Using Radiosonde Observations

Author:

Kwon Eun-Han1,Sohn B. J.1,Smith William L.2,Li Jun3

Affiliation:

1. School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea

2. Department of Atmospheric and Planetary Sciences, Hampton University, Hampton, Virginia

3. Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin—Madison, Madison, Wisconsin

Abstract

Abstract Temperature and moisture profiles retrieved from Infrared Atmospheric Sounding Interferometer (IASI) data are evaluated using collocated radiosonde data from September 2008 to August 2009 over East Asia. The level-2 products used in this study were provided by the National Oceanic and Atmospheric Administration/National Environmental Satellite, Data, and Information Service. By using radiosonde observations as a reference, the bias and root-mean-square error (RMSE) of the temperature and water vapor profiles are obtained to examine the performance of the IASI retrievals depending on surface types and the degree of atmospheric moisture. Overall, retrievals over the land or under drier atmospheric conditions show degraded performance for both the temperature and the moisture, especially for the boundary layer temperature. It is further shown that the vertical distributions of the RMSEs and the biases of the IASI retrievals resemble the variability pattern of the radiosonde observations from the mean profiles. These retrieval aspects are thought to be related to the surface emissivity effect on the IASI retrieval and the difficulties of accounting for large atmospheric variability in the retrieval process. Although the retrieval performance appears to degrade under cloudy conditions, cloudy- and clear-sky retrievals show similar statistical behaviors varying with surface type and atmospheric moisture. Furthermore, the similar statistical behaviors between first guess and final retrievals suggest that error characteristics inherent to the first guess were not sufficiently resolved by the physical retrieval process, leaving a need to improve the first guess for the better retrieval.

Publisher

American Meteorological Society

Subject

Atmospheric Science,Ocean Engineering

Reference30 articles.

1. Remote sensing from the infrared atmospheric sounding interferometer instrument 2. Simultaneous retrieval of temperature, water vapor, and ozone atmospheric profiles;Aires;J. Geophys. Res.,2002

2. The physical retrieval methodology for IASI: The δ-IASI code;Carissimo;Environ. Modell. Software,2005

3. AIRS: Improving weather forecasting and providing new data on greenhouse gases;Chahine;Bull. Amer. Meteor. Soc.,2006

4. Chahine, M. T., E.Manning, P.Rosenkranz, L.Strow, and J.Susskind, 2007: AIRS-team retrieval for core products and geophysical parameters, level 2. Algorithm Theoretical Basis Doc. NASA JPL D-17006, version 4.0, 231 pp. [Available online at http://eospso.gsfc.nasa.gov/eos_homepage/for_scientists/atbd/docs/AIRS/20070301_L2_ATBD_signed.pdf.]

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