An Intercomparison of Microphysical Retrieval Algorithms for Upper- Tropospheric Ice Clouds

U pper-tropospheric ice clouds are important modulators of the Earth’s climate, cover 20% of the globe at any given time (Liou 1986), and occur ~43% of the time in long-term satellite datasets (Wylie and Menzel 1999). Ice clouds, such as cirrus, tend to ref lect less incoming solar radiation and absorb more infrared radiation than water clouds, which are typically optically thicker and occur at a lower altitude. Tropical cirrus clouds and convective anvils near the tropical tropopause layer (TTL) may play an important role in stratospheric–tropospheric water vapor exchange and dehydration of air in the TTL (Rosenfield et al. 1998; Sherwood 1999; Hartmann et al. 2001; Holton and Gettelman 2001; Jensen and Pfister 2004). Accurate cloud property retrievals are important for understanding the radiative feedback of high clouds and parameterization development for global models. One of the key uncertainties in climate model simulations is the feedback of upper-tropospheric clouds on the Earth’s radiation budget. The goals of the Global Energy and Water Cycle Experiment (GEWEX) Cloud System Study (GCSS) involve bringing together members of the observational and AN INTERCOMPARISON OF MICROPHYSICAL RETRIEVAL ALGORITHMS FOR UPPERTROPOSPHERIC ICE CLOUDS