Systematic Errors that are Due to the Monochromatic-Equivalent Radiative Transfer Approximation in Thermal Emission Problems.

An underlying assumption of data assimilation models is that the radiative transfer model used by them can simulate observed radiances with zero bias and small error. For practical reasons a fast parameterized radiative transfer model is used instead of a highly accurate line-by-line model. These fast models usually replace the spectral integration of the product of the transmittance and the Planck function with a monochromatic equivalent, namely, the product of a spectrally averaged transmittance and a spectrally averaged Planck function. The error of using this equivalent form is commonly assumed to be negligible. However, this error is not necessarily negligible and introduces a systematic height-dependent bias to the assimilation scheme. Although the bias could be corrected by a separate bias correction scheme, it is more effective to correct its source, the fast radiative transfer model. I examine the magnitude of error when the monochromatic-equivalent approach is used and demonstrate how a fast parameterized radiative model with Planck-weighted mean transmittances can effectively reduce if not eliminate these errors at source. I focus on channel 12 of the High-Resolution Infrared Radiation Sounder onboard the National Oceanic and Atmospheric Administration (NOAA)-14 satellite that, among all the channels of this instrument, displays the largest error.