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Using Satellite and ARM Observations to Evaluate Cold Air Outbreak Cloud Transitions in E3SM Global Storm-Resolving Simulations
  • +8
  • Xue Zheng,
  • Yunyan Zhang,
  • Stephen A. Klein,
  • Meng Zhang,
  • Zhibo Zhang,
  • Min Deng,
  • Christopher Ryutaro Terai,
  • Jingjing Tian,
  • Bart Geerts,
  • Peter Martin Caldwell,
  • Peter A Bogenschutz
Xue Zheng
Lawrence Livermore National Laboratory (DOE)

Corresponding Author:[email protected]

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Yunyan Zhang
Lawrence Livermore National Laboratory (DOE)
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Stephen A. Klein
Lawrence Livermore National Laboratory (DOE)
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Meng Zhang
Lawrence Livermore National Laboratory
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Zhibo Zhang
University of Maryland, Baltimore County
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Min Deng
Brookhaven National Laboratory
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Christopher Ryutaro Terai
Lawrence Livermore National Laboratory
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Jingjing Tian
PNNL
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Bart Geerts
University of Wyoming
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Peter Martin Caldwell
Lawrence Livermore National Laboratory (DOE)
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Peter A Bogenschutz
Lawrence Livermore National Laboratory
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Abstract

This study evaluates the performance of a global storm-resolving model (GSRM), the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM). We analyze marine boundary layer clouds in a cold air outbreak over the Norwegian Sea in a 40-day simulation, and compare them to observations from satellite and a field campaign of the Atmospheric Radiation Measurement program (ARM). SCREAM qualitatively captures the cold air outbreak cloud transition in terms of the boundary layer growth, cloud mesoscale structure, and phase partitioning. SCREAM also correctly locates the greatest ice and liquid in the mesoscale updraft. However, the study finds that SCREAM might underestimate cloud supercooled liquid water in the cumulus cloud regime.
This study showcases the promise of employing high-resolution and high-frequency observations under similar large-scale conditions for evaluating GSRMs. This approach can help identify model features for future process-level studies before allocating extra resources for a time-matched model intercomparison of a specific case.
14 Dec 2023Submitted to ESS Open Archive
27 Dec 2023Published in ESS Open Archive