Efficient nonlinear inversion for atmospheric sounding and other applications
Applied Optics, Vol. 48, Issue 10, pp. 1790-1796 (2009)
http://dx.doi.org/10.1364/AO.48.001790
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Abstract
Retrieving atmospheric and/or surface state variables using remote observations typically involves minimizing a nonlinear cost function in measurement space. Many methods exist for minimizing nonlinear functions, but the applicability of one method over another has a large dependence on the degree of nonlinearity of the cost function and the initial guess error. We present a minimization method, called DRAD, that is applicable to highly nonlinear cost functions and to problems where little a priori information about the retrieved variables is available. To illustrate the method, water vapor and temperature profiles are retrieved using simulated Atmospheric Infrared Sounder observations. We focus on the efficiency of DRAD for retrievals generated for a wide range of initial guess errors. For a comparison, we also generate retrievals using the Levenberg–Marquardt method.
© 2009 Optical Society of America
OCIS Codes
(260.3090) Physical optics : Infrared, far
(280.4991) Remote sensing and sensors : Passive remote sensing
(280.6780) Remote sensing and sensors : Temperature
(010.0280) Atmospheric and oceanic optics : Remote sensing and sensors
ToC Category:
Remote Sensing and Sensors
History
Original Manuscript: July 29, 2008
Revised Manuscript: February 9, 2009
Manuscript Accepted: February 19, 2009
Published: March 23, 2009
Citation
Richard Lynch, Jean-Luc Moncet, and Xu Liu, "Efficient nonlinear inversion for atmospheric sounding and other applications," Appl. Opt. 48, 1790-1796 (2009)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-48-10-1790
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