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Influence of parameterization changes on Arctic low cloud properties and cloud radiative effects in two versions of the HadGEM3 Atmospheric Model: GA7.1 and GA6
  • Patrick Charles Taylor,
  • Robyn C. Boeke,
  • Alejandro Bodas-Salcedo
Patrick Charles Taylor
National Aeronautics and Space Administration (NASA)

Corresponding Author:[email protected]

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Robyn C. Boeke
Science Systems and Applications, Inc.
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Alejandro Bodas-Salcedo
Met Office Hadley Centre
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Abstract

Arctic clouds play a key role in Arctic climate variability and change; however, contemporary climate models struggle to simulate cloud properties accurately. Model-simulated cloud properties are determined by the physical parameterizations and their interactions within the model configuration. Quantifying effects of individual parameterization changes on model-simulated clouds informs efforts to improve cloud properties in models and provides insights on climate system behavior. This study quantities the influence of individual parameterization schemes on Arctic low cloud properties within the Hadley Centre Global Environmental Model 3 atmospheric model using a suite of experiments where individual parameterization packages are changed one-at-a-time between two configurations: GA6 and GA7.1. The results indicate that individual parameterization changes explain most of the cloud property differences, whereas multiple parameterizations, including non-cloud schemes, contribute to cloud radiative effect differences. The influence of a parameterization change on cloud properties is found to vary by meteorological regime. We employ a three-term decomposition to quantify contributions from (1) regime independent, (2) regime dependent, and (3) the regime frequency of occurrence changes. Decomposition results indicate that each term contributes differently to each cloud property change and that non-cloud parameterization changes make a substantial contribution to the LW and SW cloud radiative effects by modifying clear-sky fluxes differently across regimes. The analysis provides insights on the role of non-cloud parameterizations for setting cloud radiative effects, a model pathway for cloud-atmosphere circulation interactions, and raises questions on the most useful observational approaches for improving models.
04 Mar 2024Submitted to ESS Open Archive
04 Mar 2024Published in ESS Open Archive