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Cloud Impacts on Photochemistry: Statistical Analysis of Global Chemistry Models and Measurements from the Atmospheric Tomography Mission
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  • Samuel Hall,
  • Kirk Ullmann,
  • Michael Prather,
  • Clare Flynn,
  • Lee Murray,
  • Arlene Fiore,
  • Gustavo Correa,
  • Sarah Strode,
  • Stephen Steenrod,
  • Lamarque Jean-Francois,
  • Jonathan Guth,
  • Beatrice Josse,
  • Johannes Flemming,
  • Vincent Huijnen,
  • N. Abraham,
  • Alexander Archibald
Samuel Hall
National Center for Atmospheric Research

Corresponding Author:[email protected]

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Kirk Ullmann
National Center for Atmospheric Research
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Michael Prather
Univ California Irvine
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Clare Flynn
University of California Irvine
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Lee Murray
University of Rochester
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Arlene Fiore
Columbia University of New York
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Gustavo Correa
Columbia University
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Sarah Strode
Universities Space Research Association
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Stephen Steenrod
USRA GESTAR
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Lamarque Jean-Francois
National Center for Atmospheric Research
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Jonathan Guth
Météo-France
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Beatrice Josse
Météo-France Toulouse
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Johannes Flemming
European Centre for Medium-Range Weather Forecasts
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Vincent Huijnen
Royal Netherlands Meteorological Institute
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N. Abraham
University of Cambridge
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Alexander Archibald
University of Cambridge
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Abstract

The influence of clouds on photochemistry remains a significant uncertainty in global chemistry models. Variability in cloud fraction, morphology, phase and optical properties provides significant challenges to models with horizontal resolutions that far exceed the scale of most clouds. Measured photolysis frequencies derived from the Charged-coupled device Actinic Flux Spectroradiometers (CAFS) on board the NASA DC-8 during the Atmospheric Tomography (ATom) mission in 2016 provide an extensive set of statistics on how clouds alter the photolytic rates throughout remote ocean basins. Here we focus on north and tropical pacific transects during the first deployment (ATom-1) in August 2016 including regular profiles through cloudy, partly cloudy and clear conditions. Nine global chemistry–climate or –transport models provide similar statistics on J-values for regional domains encompassing the measured flight path. The statistical picture of the impact of clouds on J-values emerges through the distribution of the ratio of the cloud influenced models and measurement to corresponding cloud free model runs (J-cloudy/J-clear). The models all reproduce general patterns of enhancement above and shading below cloud, but diverge in distribution patterns and clear sky prevalence.