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Proceedings Paper

HT-FRTC: a fast radiative transfer code using kernel regression
Author(s): Jean-Claude Thelen; Stephan Havemann; Warren Lewis
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Paper Abstract

The HT-FRTC is a principal component based fast radiative transfer code that can be used across the electromagnetic spectrum from the microwave through to the ultraviolet to calculate transmittance, radiance and flux spectra. The principal components cover the spectrum at a very high spectral resolution, which allows very fast line-by-line, hyperspectral and broadband simulations for satellite-based, airborne and ground-based sensors. The principal components are derived during a code training phase from line-by-line simulations for a diverse set of atmosphere and surface conditions. The derived principal components are sensor independent, i.e. no extra training is required to include additional sensors. During the training phase we also derive the predictors which are required by the fast radiative transfer code to determine the principal component scores from the monochromatic radiances (or fluxes, transmittances). These predictors are calculated for each training profile at a small number of frequencies, which are selected by a k-means cluster algorithm during the training phase. Until recently the predictors were calculated using a linear regression. However, during a recent rewrite of the code the linear regression was replaced by a Gaussian Process (GP) regression which resulted in a significant increase in accuracy when compared to the linear regression. The HT-FRTC has been trained with a large variety of gases, surface properties and scatterers. Rayleigh scattering as well as scattering by frozen/liquid clouds, hydrometeors and aerosols have all been included. The scattering phase function can be fully accounted for by an integrated line-by-line version of the Edwards-Slingo spherical harmonics radiation code or approximately by a modification to the extinction (Chou scaling).

Paper Details

Date Published: 19 September 2016
PDF: 7 pages
Proc. SPIE 9976, Imaging Spectrometry XXI, 99760F (19 September 2016); doi: 10.1117/12.2235377
Show Author Affiliations
Jean-Claude Thelen, Met Office (United Kingdom)
Stephan Havemann, Met Office (United Kingdom)
Warren Lewis, Met Office (United Kingdom)

Published in SPIE Proceedings Vol. 9976:
Imaging Spectrometry XXI
John F. Silny; Emmett J. Ientilucci, Editor(s)

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