Journal of Applied Meteorology · 2004 · 29 citations · 11 references
Natural SciencesEarth SciencesMeteorologyAtmospheric ScienceCloud PhysicsRemote SensingAtmospheric AbsorptionCloud ProcessesCloud PropertiesCloud Remote SensingCloud StructureInfrared Remote SensingCloud AbsorptionCloud CharacterizationCloud Microphysical RetrievalsCloud Microphysics RetrievalsCloud Radiative Property RetrievalCloud Spectral PropertiesRadiative Transfer In CloudsVariances
Abstract This paper describes the theory and application of the minimum local emissivity variance (MLEV) technique for simultaneous retrieval of cloud pressure level and effective spectral emissivity from high-spectral-resolution radiances, for the case of single-layer clouds. This technique, which has become feasible only with the recent development of high-spectral-resolution satellite and airborne instruments, is shown to provide reliable cloud spectral emissivity and pressure level under a wide range of atmospheric conditions. The MLEV algorithm uses a physical approach in which the local variances of spectral cloud emissivity are calculated for a number of assumed or first-guess cloud pressure levels. The optimal solution for the single-layer cloud emissivity spectrum is that having the “minimum local emissivity variance” among the retrieved emissivity spectra associated with different first-guess cloud pressure levels. This is due to the fact that the absorption, reflection, and scattering processes of clouds exhibit relatively limited localized spectral emissivity structure in the infrared 10–15-μm longwave region. In this simulation study it is shown that the MLEV cloud pressure root-mean-square errors for a single level with effective cloud emissivity greater than 0.1 are ∼30, ∼10, and ∼50 hPa, for high (200– 300 hPa), middle (500 hPa), and low (850 hPa) clouds, respectively. The associated cloud emissivity root-mean-square errors in the 900 cm−1 spectral channel are less than 0.05, 0.04, and 0.25 for high, middle, and low clouds, respectively.
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Michael D. King, W. Paul Menzel, Patrick S. Grant et al. · Journal of Atmospheric and Oceanic Technology · 1996 · 208 citations · Full text