HR: 0800h
AN: A51B-0767 [Abstracts]
TI: Retrieval of cloud properties from Atmospheric Infrared Sounder (AIRS) data
AU: * Lee, Y
EM: yklee@ariel.met.tamu.edu
AF: Texas A&M University, Department of Atmospheric Sciences
TAMU 3150
Texas A&M University, College Station, TX 77843
United States
AU: Yang, P
EM: pyang@ariel.met.tamu.edu
AF: Texas A&M University, Department of Atmospheric Sciences
TAMU 3150
Texas A&M University, College Station, TX 77843
United States
AU: Baum, B A
EM: bryan.baum@ssec.wisc.edu
AF: NASA Langley Research Center, NASA Langley Research Center, Hampton, VA 23681
United States
AU: Huang, H A
AF: University of Wisconsin-Madison, Cooperative Institute for Meteorological Satellite Studies, University
of Wisconsin-Madison, 1225 W. Dayton Street, Madison, WI 53706
United States
AU: Li, J
EM: junL@ssec.wisc.edu
AF: University of Wisconsin-Madison, Cooperative Institute for Meteorological Satellite Studies, University
of Wisconsin-Madison, 1225 W. Dayton Street, Madison, WI 53706
United States
AB:
This study reports on the inference of cloud top properties (cloud top pressure, thermodynamic phase, optical thickness, and
effective particle size) from radiometric measurements and atmospheric profiles generated from the Atmospheric Infrared
Sounder (AIRS) onboard the EOS AQUA platform. The CO2 slicing method is applied to infer cloud top pressure from AIRS Level
1B (L1B) radiances; additional use is made of Level-2 (L2) Support products. Since there are 2378 wavenumber channels
available within the infrared spectral region, more channels are used to find cloud top pressure than with the method as
applied to MODIS 15-micron band data. In this study, the CO2 slicing method uses forward calculations based on the
Stand-Alone AIRS Radiative Transfer Algorithm (SARTA); it has 100 vertical pressure layers from 0.005 to 1100 hPa and is
considered a fast and accurate radiative transfer model. The cloud thermodynamic phase is inferred from a bispectral method
based on the 8.5- and 11-micron channels similar to that used by the MODIS atmospheres team. Based on the cloud top pressure
and phase information in addition to a look-up database of ice particle scattering properties, optical thickness and
effective particle size are inferred. Examples will be shown for both ice cloud and water cloud cases.
DE: 0933 Remote sensing
SC: Atmospheric Sciences [A]
MN: 2004 AGU Fall Meeting