Impact of Cloud Ice Particle Size Uncertainty in a Climate Model and Implications for Future Satellite Missions

Abstract

Ice particle size is pivotal to determining ice cloud radiative effect and precipitating rate. However, there is a lack of accurate ice particle effective radius (R_(ei)) observation on the global scale to constrain its representation in climate models. In support of future mission design, here we present a modeling assessment of the sensitivity of climate simulations to R_(ei) and quantify the impact of the proposed mission concept on reducing the uncertainty in climate sensitivity. We perturb the parameters pertaining to ice fall speed parameter and R_(ei) in radiation scheme, respectively, in National Center for Atmospheric Research CESM1 model with a slab ocean configuration. The model sensitivity experiments show that a settling velocity increase due to a larger R_(ei) results in a longwave cooling dominating over a shortwave warming, a global mean surface temperature decrease, and precipitation suppression. A similar competition between longwave and shortwave cloud forcing changes also exists when perturbing R_(ei) in the radiation scheme. Linearity generally holds for the climate response for R_(ei) related parameters. When perturbing falling snow particle size (R_(es)) in a similar way, we find much less sensitivity of climate responses. Our quadrupling CO₂ experiments with different parameter settings reveal that R_(ei) and R_(es) can account for changes in climate sensitivity significantly from +12.3% to −6.2%. By reducing the uncertainty ranges of R_(ei) and R_(es) from a factor of 2 to ±25%, a future satellite mission under design is expected to improve the climate state simulations and reduce the climate sensitivity uncertainty pertaining to ice particle size by approximately 60%. Our results highlight the importance of better observational constraints on R_(ei) by satellite missions.