Full Spectrum Correlated-k for Shortwave Atmospheric Radiative Transfer

The Full Spectrum Correlated-k (FSCK) method, originally developed for applications in combustion systems, is adapted for use in shortwave atmospheric radiative transfer. By weighting k-distributions by the Planck function, or by the solar source function in the case of shortwave radiation, the FSCK method eliminates the requirement that the Planck function be constant over a spectral interval. As a consequence, the full spectrum may be integrated over a single spectral band as long as the assumption of correlation from one vertical atmospheric level to the next remains valid. As a result of the vertical distribution of absorbing gases in the atmosphere, primarily ozone and water vapor, the correlation assumption breaks down when the full shortwave spectrum is treated as a single band. Problems with the lack of correlation across the full spectrum are removed by partitioning the spectrum at 0.68 μm into two bands. For wavelengths greater than 0.68 μm ozone continuum absorption is less important relative to absorption by water vapor and carbon dioxide, while the opposite is true at wavelengths shorter than 0.68 μm. This two band approach in the FSCK formalism produces clear-sky flux and heating rate errors less than 1% and 6%, respectively, relative to monochromatic calculations and requires only 15 quadrature points per layer, which represents a 60-90% reduction in computation time relative to other models currently in use. An evaluation of fluxes calculated by the FSCK method in cases with idealized clouds demonstrates that gray cloud scattering in two spectral bands is sufficient to reproduce line-by-line generated fluxes, in which spectrally varying cloud scattering properties were used. Two different approaches for modeling absorption by cloud drops were also examined. Explicitly including spectrally varying cloud absorption in the solar source function-weighted k-distributions results in realistic in-cloud heating rates, although incloud heating rates were consistently underpredicted by approximately 8-12% as compared to line-by-line results. A gray cloud absorption parameter that was chosen to fit line-by-line results optimally for one atmosphere, but applied to different atmospheres or cloud combinations, also closely approximated line-by-line in-cloud heating rates, although the heating rate errors were less consistent in magnitude and sign than the explicit approach.