PCA-based radiative transfer: Improvements to aerosol scheme, vertical layering and spectral binning. (September 2017)

• Record Type: Journal Article
• Authors: Kopparla, Pushkar; Natraj, Vijay; Limpasuvan, Drew; Spurr, Robert; Crisp, David; Shia, Run-Lie; Somkuti, Peter; Yung, Yuk L
• Is Part Of: Journal of quantitative spectroscopy & radiative transfer. Volume 198(2017)
• Page Start: 104
• Page End: 111
• Publication Date: 2017-09
• Subjects: Spectrum analysis -- Periodicals; Radiation -- Periodicals; Analyse spectrale -- Périodiques; Rayonnement -- Périodiques; Radiation; Spectrum analysis; Periodicals; 543.0858
• DOI: 10.1016/j.jqsrt.2017.05.005
• Languages: English
• ISSNs: 0022-4073

Abstract

Highlights: Aerosol handling and binning schemes of the PCA-RT model are optimized. Maximum errors were brought under 0.01% in the range 0.3–3 micron. Errors magnitudes and distributions are stable over 70 diverse atmospheric profiles. Abstract: The Principal Component Analysis (PCA)-based fast radiative transfer method has been shown to have at least an order of magnitude increase in computational speed while maintaining an overall accuracy of 0.01% (compared to line-by-line calculations) over narrow and broad spectral bands. In this paper, we describe several improvements made to the method and provide a discussion of the method's performance over a diverse set of atmospheric profiles and land surface types. We also test the model over uniform pressure level profiles. The method is now capable of providing atmospheric spectra with residuals under 0.1%, calculated with respect to the continuum, throughout the shortwave region between 0.3 − 3 μ m at high resolution, which is substantial improvement over errors reported in earlier work. Future directions for applications and further optimization are examined.