HR: 0830h
AN: A21C-0987    [PDF]
TI: Two Dimensional Characterization of Atmospheric Profile Retrievals From Limb Sounding Observations
AU: * Bowman, K W
EM: kevin.bowman@jpl.nasa.gov
AF: Jet Propulsion Laboratory, 4800 Oak Grove Dr. MS: 183-601, Pasadena, CA 91009 United States
AU: Worden, J
EM: john.worden@jpl.nasa.gov
AF: Jet Propulsion Laboratory, 4800 Oak Grove Dr. MS: 183-601, Pasadena, CA 91009 United States
AU: Jones, D
AF: Harvard University, Pierce Hall 186 29 Oxford Street, Cambridge, MA 02138 United States
AB: Limb sounders measure atmospheric radiation that is dependent on atmospheric temperature and constituents that have a radial and angular distribution in Earth-centered coordinates. In order to evaluate the sensitivity of a limb retrieval to radial and angular distributions of trace gas concentrations, we perform and characterize one-dimensional (vertical) and two-dimensional (radial and angular) atmospheric profile retrievals. Our simulated atmosphere for these retrievals is a distribution of carbon monoxide (CO), which represents a plume off the coast of south-east Asia. Both the one dimensional (1D) and two dimensional (2D) limb retrievals are characterized by evaluating their averaging kernels and error covariances on a radial and angular grid that spans the plume. We apply this 2D characterization of a limb retrieval to a comparison of the 2D retrieval with the 1D (vertical) retrieval. By characterizing a limb retrieval in two dimensions the location of the air mass where the retrievals are most sensitive can be determined. For this test case the retrievals are most sensitive to the CO concentrations about 2 degrees latitude in front of the tangent point locations. We find the information content for the 2D retrieval is an order of magnitude larger and the degrees of freedom is about a factor of two larger than that of the 1D retrieval primarily because the 2D retrieval can estimate angular distributions of CO concentrations. This 2D characterization allows the radial and angular resolution as well as the degrees of freedom and information content to be computed for these limb retrievals. We also use the 2D averaging kernel to develop a strategy for validation of a limb retrieval with an in-situ measurement.
DE: 0365 Troposphere--composition and chemistry
DE: 3260 Inverse theory
DE: 3337 Numerical modeling and data assimilation
DE: 3360 Remote sensing
SC: Atmospheric Sciences [A]
MN: 2003 Fall Meeting