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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
Published on: April 8, 2020
Large discrepancies in dominant microphysical processes governing mixed-phase clouds across climate models.
Hannah C Frostenberg1, Montserrat Costa-Surós2, Paraskevi Georgakaki3,4
1Department of Space, Earth and Environment, Chalmers University of Technology, Gothenburg, Sweden.
Climate models struggle with cloud ice and liquid balance. Primary ice nucleation (PIN) is key in some regions, but models differ on other ice processes, impacting climate predictions.
Area of Science:
- Atmospheric Science
- Climate Modeling
- Cloud Microphysics
Background:
- The supercooled liquid fraction (SLF) in mixed-phase clouds is crucial for climate but challenging to model.
- Uncertainties in ice-related microphysical processes significantly impact cloud phase simulations.
Purpose of the Study:
- To investigate the relative importance of four key microphysical processes on SLF in mixed-phase clouds.
- To compare model responses to primary ice nucleation (PIN) and secondary ice production (SIP) parameterizations across different climate models.
Main Methods:
- Utilized three global climate models: EC-Earth3-AerChem, NorESM2-MM, and ECHAM6.3-HAM2.3.
- Analyzed the influence of primary ice nucleation (PIN), secondary ice production (SIP), sedimentation, and ice crystal transport on SLF.
- Implemented a unified SIP parameterization to assess model-specific interactions.
Main Results:
- All models identified PIN as the dominant factor influencing SLF at cold, high northern latitudes.
- Significant model divergence was observed in other regions and at higher temperatures.
- Varied model responses to SIP parameterization highlighted fundamental differences in microphysical process interactions.
Conclusions:
- Model agreement on PIN's dominance is limited to specific conditions.
- Discrepancies in model responses to SIP and other processes indicate differing priorities in cloud phase representation.
- The divergence among models may limit the reliability of conclusions drawn from single-model studies on cloud microphysics.
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