Using Satellite Observations to Evaluate Model Microphysical Representation of Arctic Mixed‐Phase Clouds

Abstract

Uncertainties in cloud and aerosol radiative effects are a principal contributor to climate model uncertainty, and remain so despite decades of model development (Boucher et al., 2013). These uncertainties arise from the difficulty of representing aerosol-cloud interactions and other key physical processes at the typical resolutions of global climate models (GCMs). Evaluations of available models from the Coupled Model Intercomparison Project Phase 6 (CMIP6; Eyring et al., 2016) indicate that changes in climate sensitivity relative to CMIP5 (Taylor et al., 2012) are mostly due to changes in cloud representation, specifically for extratropical low-level clouds (Zelinka et al., 2020). Using observations to reevaluate the representation of these clouds in the latest generation of GCMs is a vital part of testing the validity of these new predictions.In the Arctic, clouds mediate climate change through interactions with land and sea ice, and impacts on surface radiative fluxes (H. Morrison et al., 2012). As the thermodynamic phase of Arctic clouds shifts from ice to liquid in response to warming, the radiative effect they exert on the surface changes (Mitchell et al., 1989). This cloud phase feedback depends on cloud optical thickness and lifetime changes. In the Arctic, observations indicate that liquid and ice clouds exert very different radiative forcings on the surface

LGM Paleoclimate Constraints Inform Cloud Parameterizations and Equilibrium Climate Sensitivity in CESM2

“…Wang et al, 2014), yet "nimax" was not re-coded to account for the new source terms. Shaw et al (2022) reported the "nimax" issue and noted that, without a correction, the heterogeneous ice nucleation processes can increase the mass of cloud ice but not raise the 1 for details of the model configurations.…”

“…number concentration, that is, artificially increasing ice crystal size and sedimentation. Investigating Arctic clouds, Shaw et al (2022) found that "nimax" suppressed the formation of stable ice clouds and affected cloud feedbacks. Additionally, "nimax" prevents secondary ice number production through the Hallett-Mossop process.…”

“…Shaw et al. (2022) reported the “nimax” issue and noted that, without a correction, the heterogeneous ice nucleation processes can increase the mass of cloud ice but not raise the number concentration, that is, artificially increasing ice crystal size and sedimentation. Investigating Arctic clouds, Shaw et al.…”

Evidence for Secondary Ice Production in Southern Ocean Maritime Boundary Layer Clouds

“…In this work, we focus on assessing simulated ice number concentrations and simulated sensitivity to the HM process in the CESM2-CAM6 release model configuration used in Gettelman et al (2020), which does include this limiter. Shaw et al (2022) have highlighted this as a controlling feature on cloud properties, especially in the mixed phase cloud regime, because the ice number rates from Hoose et al (2010) were not included in the limiter. Shaw et al (2022) notes this ice number limiter is un-intentionally low.…”

“…Shaw et al (2022) have highlighted this as a controlling feature on cloud properties, especially in the mixed phase cloud regime, because the ice number rates from Hoose et al (2010) were not included in the limiter. Shaw et al (2022) notes this ice number limiter is un-intentionally low. We expect the ice number limiter dampens the simulated sensitivity to the parameterized HM process and we will test this with a sensitivity test of a developmental model version without the limiter.…”