Cloud tomographic retrieval algorithms. I: Surrogate minimization method. (January 2022)

• Record Type: Journal Article
• Authors: Doicu, Adrian; Doicu, Alexandru; Efremenko, Dmitry; Trautmann, Thomas
• Is Part Of: Journal of quantitative spectroscopy & radiative transfer. Volume 277(2022)
• Publication Date: 2022-01
• Subjects: Cloud tomographic retrieval -- Multi-dimensional models; Spectrum analysis -- Periodicals; Radiation -- Periodicals; Analyse spectrale -- Périodiques; Rayonnement -- Périodiques; Radiation; Spectrum analysis; Periodicals; 543.0858
• DOI: 10.1016/j.jqsrt.2021.107954
• Languages: English
• ISSNs: 0022-4073

Abstract

Highlights: A cloud tomographic retrieval algorithm for solving the inverse problem has been designed. The algorithm uses SHDOM for radiative transfer calculation The surrogate minimization method is used for solving the inverse problem Extinction field is retrieved with relative error of order of 0.1. Abstract: A cloud tomographic retrieval algorithm relying on (i) the spherical harmonics discrete ordinate method for computing the radiative transfer and (ii) the surrogate minimization method for solving the inverse problem has been designed. The retrieval algorithm uses regularization, accelerated projected gradient methods, and two types of surrogate functions. The performances of the retrieval algorithm are analyzed on a few synthetic two- and three-dimensional problems.