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On assessing ERA5 and MERRA2 representations of cold-air outbreaks across the Gulf Stream
  • +13
  • Seethala Chellappan,
  • Paquita Zuidema,
  • James B Edson,
  • Michael A Brunke,
  • Gao Chen,
  • Xiang-Yu Li,
  • David Painemal,
  • Claire E Robinson,
  • Taylor Shingler,
  • Michael Shook,
  • Armin Sorooshian,
  • Kenneth L Thornhill,
  • Florian Tornow,
  • Hailong Wang,
  • Xubin Zeng,
  • Luke D. Ziemba
Seethala Chellappan
Rosenstiel School of Marine and Atmospheric Science

Corresponding Author:[email protected]

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Paquita Zuidema
University of Miami/RSMAS
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James B Edson
Woods Hole Oceanographic Institution
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Michael A Brunke
University of Arizon, Tucson, AZ
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Gao Chen
NASA Langley Research Center
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Xiang-Yu Li
Pacific Northwest National Laboratory
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David Painemal
SSAI/NASA Langley Research Center
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Claire E Robinson
Science Systems and Applications
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Taylor Shingler
NASA Langley
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Michael Shook
Langley Research Center
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Armin Sorooshian
University of Arizona
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Kenneth L Thornhill
NASA Langley Research Center
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Florian Tornow
Columbia University and NASA GISS
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Hailong Wang
Pacific Northwest National Laboratory
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Xubin Zeng
The University of Arizona
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Luke D. Ziemba
NASA Langley Research Center
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Abstract

The warm Gulf Stream sea surface temperatures (SSTs) strongly impact the evolution of winter clouds behind atmospheric cold fronts. Such cloud evolution remains challenging to model. The Gulf Stream is too wide within the ERA5 and MERRA2 reanalyses, affecting the turbulent surface fluxes. Known problems within the ERA5 boundary layer (too-dry and too-cool with too strong westerlies), ascertained primarily from ACTIVATE 2020 campaign aircraft dropsondes and secondarily from older buoy measurements, reinforce surface flux biases. In contrast, MERRA2 winter surface winds and air-sea temperature/humidity differences are slightly too weak, producing surface fluxes that are too low. Reanalyses boundary layer heights in the strongly-forced winter cold-air-outbreak regime are realistic, whereas late-summer quiescent stable boundary layers are too shallow. Nevertheless, the reanalysis biases are small, and reanalyses adequately support their use for initializing higher-resolution cloud process modeling studies of cold-air outbreaks.