Christopher D. Barnet

A Computationally Efficient Retrieval Algorithm for Hyperspectral Sounders Incorporating A Priori Information

In this letter, we describe a novel implementation scheme for the inversion of the radiative-transfer equation as encountered in satellite remote sensing and incorporating a priori information. Unlike traditional maximum a posteriori approaches, the new algorithm does not require the use of a forward-model tangent linear and does not pay a large computational time penalty in the use of numerical derivatives. Using spectral data from the European Organisation for the Exploitation of Meteorological Satellites Infrared Atmospheric Sounding Interferometer sensor, we provide a demonstration of the algorithm and comparison to the National Oceanic and Atmospheric Administrations operationally available product using carbon monoxide as target gas.

Tropospheric Dynamics and Chemistry as Revealed by AIRS Ultraspectral Remote Sensing during INTEX-A

We present retrievals of tropospheric carbon monoxide from NASAs Atmospheric InfraRed Sounder (AIRS) acquired during the 2004 Intercontinental Chemical Transport Experiment North America (INTEX-A) along with modeling and in situ measurements from NASAs DC-8.

Using an Optimized Version of the AIRS Water Vapor Retrieval Algorithm to Analyze a 3-year Period of Water Vapor Measurements

We present an optimization study of AIRS water vapor retrieval algorithm by comparison with in situ measurements. This optimized algorithm is being used for a more accurate characterization of AIRS water vapor distributions.