HR: 0800h
AN: A51B-0769    [Abstracts]
TI: Spatial and spectral variability of the outgoing thermal IR spectra: A case study of July 2003
AU: * Huang, X
EM: xianglei@princeton.edu
AF: Program in Atmospheric & Oceanic Sciences, Princeton University, 300 Forrestal Road, Sayre Hall, P. O. Box CN710, Princeton, NJ 08544-0710 United States
AU: Yung, Y
EM: yly@gps.caltech.edu
AF: Division of Geological and Planetary Sciences, California Institute of Technology, Mail Stop 150-21, Caltech, Pasadena, CA 91125 United States
AU: Ramaswamy, V
EM: v.ramaswamy@noaa.gov
AF: NOAA/Geophysical Fluid Dynamics Laboratory, Princeton University, P. O. Box 308, Princeton, NJ 08542-0308 United States
AB: AIRS (Atmospheric Infrared Sounder) provides measurements of the outgoing thermal IR spectra with unprecedented data quality and coverage. Here we present a survey of the spatial variability in different climate zones seen from AIRS data using the spectral EOF analysis. Over the tropical and subtropical oceans, the first principal component (PC1) is mostly due to the thermal contrast between surface and thick cold cloud tops. The second principal component (PC2) is mainly due to the spatial variation of the lower tropospheric humidity (LTH) and the low clouds. The signature of dust aerosol over the Arabian Sea and the Atlantic off the coast of North Africa in the summertime can be clearly seen in the PC2. Both the PC1 and the PC2 capture the variations in the upper tropospheric water vapor due to the forced orthogonality of EOFs. The third principal component (PC3) is mainly due to the spatial variation of the lower stratospheric temperature. Over the midlatitude oceans, the PC1 is still due to the thermal contrast of emission temperature. During wintertime, the PC2 is mainly due to stratospheric temperature variations. In the summer, the PC2 over the northern-hemisphere midlatitude oceans is mainly due to the variations of the LTH and the low clouds; the PC2 over the southern-hemisphere midlatitude oceans is mainly due to the stratospheric temperature variations. Parallel studies using synthetic spectra based on NCAR CAM2 and GFDL AM2 simulation are also presented. The major discrepancies between the simulation and AIRS observations are identified and discussed. This study demonstrates the potential of AIRS data for future climate studies.
DE: 3359 Radiative processes
DE: 3360 Remote sensing
DE: 3319 General circulation
SC: Atmospheric Sciences [A]
MN: 2004 AGU Fall Meeting