Assessment of uncertainty in cloud radiative effects and heating rates through retrieval algorithm differences: Analysis using 3 years of ARM data at Darwin, Australia. Issue 10 (22nd May 2013) - Comstock, Jennifer M.; Protat, Alain; McFarlane, Sally A.; Delanoë, Julien; Deng, Min
Abstract : [1] 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 ( Re ), 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 Re shows significant discrepancies, which are attributed primarily to assumptions of particle shape. Uncertainty in Re 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 Re, can cause up to 2 K/d difference in the radiative heating rates between algorithms. Key Points: Cloud radiative effect uncertainty is driven by differences ice size and shape Retrieval algorithm uncertainty leads to 2 K/day difference in radiative heating