Premium
Assessment of uncertainty in cloud radiative effects and heating rates through retrieval algorithm differences: Analysis using 3 years of ARM data at Darwin, Australia
Author(s) -
Comstock Jennifer M.,
Protat Alain,
McFarlane Sally A.,
Delanoë Julien,
Deng Min
Publication year - 2013
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/jgrd.50404
Subject(s) - radiative transfer , cirrus , radiative flux , lidar , environmental science , radar , meteorology , shortwave , ice cloud , atmospheric sciences , ice crystals , cloud forcing , cloud top , remote sensing , algorithm , physics , cloud computing , aerosol , radiative forcing , mathematics , computer science , geology , optics , telecommunications , operating system
Ground‐based radar and lidar observations obtained at the Department of Energy's Atmospheric Radiation Measurement Program's Tropical Western Pacific site located in Darwin, Australia, are used to retrieve ice cloud properties in anvil and cirrus clouds. Cloud microphysical properties derived from four different retrieval algorithms (two radar‐lidar and two radar‐only algorithms) are compared by examining mean profiles and probability density functions of effective radius ( R e ), ice water content (IWC), visible extinction coefficient, ice number concentration, ice crystal fall speed, and vertical air velocity. Retrieval algorithm uncertainty is quantified using radiative flux closure exercises. The effect of uncertainty in retrieved quantities on the cloud radiative effect and radiative heating rates is presented. Our analysis shows that IWC compares well among algorithms, but R e shows significant discrepancies, which are attributed primarily to assumptions of particle shape. Uncertainty in R e and IWC translates into sometimes large differences in cloud shortwave radiative effect (CRE) though the majority of cases have a CRE difference of roughly 10 W m −2 on average. These differences, which we believe are primarily driven by the uncertainty in R e , can cause up to 2 K/d difference in the radiative heating rates between algorithms.