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Evaluation of modeled aerosol-cloud interactions using data from the ORACLES and LASIC field campaigns
  • +18
  • Calvin Howes,
  • Pablo Saide,
  • Paquita Zuidema,
  • Jianhao Zhang,
  • Michael Diamond,
  • Jenny Wong,
  • Steven Howell,
  • Nenes Athanasios,
  • Mary Kacarab,
  • L. Ruby Leung,
  • Amie Dobracki,
  • Graham Feingold,
  • Sharon Burton,
  • Richard Ferrare,
  • Johnathan Hair,
  • Marta Fenn,
  • Steffen Freitag,
  • Chongai Kuang,
  • Arthur Sedlacek,
  • Yang Zhang,
  • Uin Janek
Calvin Howes
University of California - Los Angeles

Corresponding Author:[email protected]

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Pablo Saide
University of California Los Angeles
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Paquita Zuidema
University of Miami
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Jianhao Zhang
University of Miami
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Michael Diamond
University of Washington
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Jenny Wong
University of Toronto
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Steven Howell
University of Hawaii at Manoa
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Nenes Athanasios
Swiss Federal Institute of Technology Lausanne
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Mary Kacarab
University of California Riverside
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L. Ruby Leung
Pacific Northwest National Laboratory
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Amie Dobracki
University of Hawaii at Manoa
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Graham Feingold
NOAA ESRL CSL
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Sharon Burton
NASA Langley Research Center
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Richard Ferrare
NASA Langley Research Center
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Johnathan Hair
NASA Langley Research Center
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Marta Fenn
SSAI
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Steffen Freitag
University of Hawaii at Manoa
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Chongai Kuang
Brookhaven National Laboratory
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Arthur Sedlacek
Brookhaven National Lab
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Yang Zhang
Northeastern University
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Uin Janek
Brookhaven National Laboratory
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Abstract

Aerosol-cloud interactions are both uncertain and important in global and regional climate models, and especially in the southeast Atlantic Ocean. This uncertainty in the region is largely due to two correlated factors---the expansive, bright, semi-permanent stratocumulus cloud deck and the fact that southern Africa is the largest source of biomass-burning aerosols in the world. We study this region using the WRF-Chem model with CAM5 aerosols and in situ observations from the ORACLES and LASIC field campaigns in August-October of 2016 through 2018. We compare aerosol and cloud properties to measure and improve model performance and expand upon observational findings of aerosol-cloud effects. Relevant comparison variables include aerosol number concentration, mean particle diameter and spread, CCN activation tendency, hygroscopicity, and cloud droplet number concentrations. Specifically, our approach is to analyze colocated model data along flight tracks to resolve aerosol-cloud interactions. Within and between single-day flights, there is high spatiotemporal variability that can get lost to large-scale averaging analyses. We have found that CCN is substantially under-represented in the model compared to observations. For a given aerosol number concentration, size, supersaturation and hygroscopicity, the model will consider fewer particles as CCN than observations indicate. We plan to explore this result further, diagnosing the model-observation differences more consistently and updating the model with more physically accurate values of aerosol size, concentration, or hygroscopicity based on observations. We will also intercompare multiple instrument platforms involved with the ORACLES and LASIC campaigns. With improved small-scale aerosol-cloud interactions, this work also shows promise to substantially improve that representation in climate models.