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Proceedings Paper

Using MODIS with AIRS to develop an operational cloud-cleared radiance product
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Paper Abstract

Today, most Numerical Weather Prediction (NWP) centers are assimilating cloud-free radiances. Radiances from the Atmospheric Infrared Sounder have been directly assimilated in NWP models with modest positive impacts. However, since only 5% percentage of AIRS fields of view (fovs) are cloud-free, only very small amounts of the data in the lower troposphere are assimilated. (Note that channels in the mid-upper stratosphere are always assimilated since they are never contaminated by clouds.) The highest vertical resolving power of AIRS is in the lower troposphere. To further improve forecast skill we must increase the use of channels in the lower troposphere. This can be accomplished by assimilating cloud-cleared radiances, which has a yield of about 50%. Since cloud-cleared radiance may have residual cloud contamination and forecast accuracy is very sensitive to the accuracy of the input observations, a technique has been developed to use the 1 km infrared channels on the Moderate Resolution Imaging Spectroradiometer (MODIS) to quality control the cloud-cleared radiances derived from an array of 3 x 3 high spectral infrared sounder AIRS 14 km fovs. This is accomplished by finding MODIS clear radiances values within the AIRS field of view. The MODIS clear radiances are compared to cloud-cleared AIRS radiances that have been convolved to the MODIS spectral resolution. Our studies have found that the cloud-cleared radiances error statistics are very similar to cloud-free (clear) when MODIS data are used to remove potential outliers in the population of AIRS cloud-cleared radiances.

Paper Details

Date Published: 20 January 2005
PDF: 6 pages
Proc. SPIE 5655, Multispectral and Hyperspectral Remote Sensing Instruments and Applications II, (20 January 2005); doi: 10.1117/12.578824
Show Author Affiliations
Mitchell D. Goldberg, National Oceanic and Atmospheric Administration/NESDIS (United States)
Thomas S. King, QSS Group, Inc. (United States)
Walter W. Wolf, QSS Group, Inc. (United States)
Chris Barnet, National Oceanic and Atmospheric Administration/NESDIS (United States)
Heng Gu, Systems Engineering and Security, Inc. (United States)
Lihang Zhou, QSS Group, Inc. (United States)


Published in SPIE Proceedings Vol. 5655:
Multispectral and Hyperspectral Remote Sensing Instruments and Applications II
Allen M. Larar; Makoto Suzuki; Qingxi Tong, Editor(s)

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