Fast and Accurate Radiative Transfer Calculations Using Principal Component Analysis for Climate Modeling

Radiative transfer (RT) computations are an essential component of energy budget calculations in climate models. However, full treatment of RT processes is computationally expensive, prompting usage of 2-stream approximations in operational climate models. This simplification introduces errors of the order of 10% in the top of the atmosphere (TOA) fluxes [Randles et al., 2013]. Natraj et al. [2005, 2010] and Spurr and Natraj [2013] demonstrated the ability of a technique using principal component analysis (PCA) to speed up RT simulations. In the PCA method for RT performance enhancement, empirical orthogonal functions are developed for binned sets of inherent optical properties that possess some redundancy; costly multiple-scattering RT calculations are only done for those (few) optical states corresponding to the most important principal components, and correction factors are applied to approximate radiation fields. Here, we extend the PCA method to a broadband spectral region from the ultraviolet to the shortwave infrared (0.3-3 micron), accounting for major gas absorptions in this region. Comparisons between the new model, called Universal Principal Component Analysis model for Radiative Transfer (UPCART), 2-stream models (such as those used in climate applications) and line-by-line RT models are performed, in order for spectral radiances, spectral fluxes and broadband fluxes. Each of these are calculated at the TOA for several scenarios with varying aerosol types, extinction and scattering optical depth profiles, and solar and viewing geometries. We demonstrate that very accurate radiative forcing estimates can be obtained, with better than 1% accuracy in all spectral regions and better than 0.1% in most cases as compared to an exact line-by-line RT model. The model is comparable in speeds to 2-stream models, potentially rendering UPCART useful for operational General Circulation Models (GCMs). The operational speed and accuracy of UPCART can be further improved by optimizing binning schemes and parallelizing the codes, work on which is under way.