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A new ice cloud parameterization for infrared radiative transfer simulation of cloudy radiances: Evaluation and optimization with IIR observations and ice cloud profile retrieval products
Author(s) -
Vidot Jérôme,
Baran Anthony J.,
Brunel Pascal
Publication year - 2015
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2015jd023462
Subject(s) - ice crystals , radiative transfer , cirrus , ice cloud , remote sensing , effective radius , environmental science , atmospheric radiative transfer codes , meteorology , computational physics , physics , geology , optics , astrophysics , galaxy
A new ice cloud optical property database in the thermal infrared has been parameterized for the RTTOV radiative transfer model. The Self‐Consistent Scattering Model (SCSM) database is based on an ensemble model of ice crystals and a parameterization of the particle size distribution. This convolution can predict the radiative properties of cirrus without the need of a priori information on the ice particle shape and an estimate of the ice crystal effective dimension. The ice cloud optical properties are estimated through linear parameterizations of ambient temperature and ice water content. We evaluate the new parameterization against existing parameterizations used in RTTOV. We compare infrared observations from Imaging Infrared Radiometer, on board CALIPSO, against RTTOV simulations of the observations. The simulations are performed using two different products of ice cloud profiles, retrieved from the synergy between space‐based radar and lidar observations. These are the 2C‐ICE and DARDAR products. We optimized the parameterization by testing different SCSM databases, derived from different shapes of the particle size distribution, and weighting the volume extinction coefficient of the ensemble model. By selecting a large global data set of ice cloud profiles of visible optical depths between 0.03 and 4, we found that the simulations, based on the optimized SCSM database parameterization, reproduces the observations with a mean bias of only 0.43 K and a standard deviation of 6.85 K. The optimized SCSM database parameterization can also be applied to any other radiative transfer model.

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