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Title: Quantification of marine aerosol subgrid variability and its correlation with clouds based on high-resolution regional modeling: Quantifying Aerosol Subgrid Variability

Abstract

One limitation of most global climate models (GCMs) is that with the horizontal resolutions they typically employ, they cannot resolve the subgrid variability (SGV) of clouds and aerosols, adding extra uncertainties to the aerosol radiative forcing estimation. To inform the development of an aerosol subgrid variability parameterization, here we analyze the aerosol SGV over the southern Pacific Ocean simulated by the high-resolution Weather Research and Forecasting model coupled to Chemistry. We find that within a typical GCM grid, the aerosol mass subgrid standard deviation is 15% of the grid-box mean mass near the surface on a 1 month mean basis. The fraction can increase to 50% in the free troposphere. The relationships between the sea-salt mass concentration, meteorological variables, and sea-salt emission rate are investigated in both the clear and cloudy portion. Under clear-sky conditions, marine aerosol subgrid standard deviation is highly correlated with the standard deviations of vertical velocity, cloud water mixing ratio, and sea-salt emission rates near the surface. It is also strongly connected to the grid box mean aerosol in the free troposphere (between 2 km and 4 km). In the cloudy area, interstitial sea-salt aerosol mass concentrations are smaller, but higher correlation is found between themore » subgrid standard deviations of aerosol mass and vertical velocity. Additionally, we find that decreasing the model grid resolution can reduce the marine aerosol SGV but strengthen the correlations between the aerosol SGV and the total water mixing ratio (sum of water vapor, cloud liquid, and cloud ice mixing ratios).« less

Authors:
ORCiD logo [1]; ORCiD logo [1];  [2];  [3]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]
  1. Pacific Northwest National Laboratory, Richland Washington USA
  2. Pacific Northwest National Laboratory, Richland Washington USA; College of Atmospheric Science, Nanjing University of Information and Technology, Nanjing China
  3. Pacific Northwest National Laboratory, Richland Washington USA; School of Earth and Space Sciences, University of Science and Technology of China, Hefei China
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1374643
Report Number(s):
PNNL-SA-126774
Journal ID: ISSN 2169-897X; KP1703020
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Geophysical Research: Atmospheres; Journal Volume: 122; Journal Issue: 12
Country of Publication:
United States
Language:
English
Subject:
global climate models; GCM; clouds; aerosols; atmospheric; subgrid

Citation Formats

Lin, Guangxing, Qian, Yun, Yan, Huiping, Zhao, Chun, Ghan, Steven J., Easter, Richard, and Zhang, Kai. Quantification of marine aerosol subgrid variability and its correlation with clouds based on high-resolution regional modeling: Quantifying Aerosol Subgrid Variability. United States: N. p., 2017. Web. doi:10.1002/2017JD026567.
Lin, Guangxing, Qian, Yun, Yan, Huiping, Zhao, Chun, Ghan, Steven J., Easter, Richard, & Zhang, Kai. Quantification of marine aerosol subgrid variability and its correlation with clouds based on high-resolution regional modeling: Quantifying Aerosol Subgrid Variability. United States. doi:10.1002/2017JD026567.
Lin, Guangxing, Qian, Yun, Yan, Huiping, Zhao, Chun, Ghan, Steven J., Easter, Richard, and Zhang, Kai. Fri . "Quantification of marine aerosol subgrid variability and its correlation with clouds based on high-resolution regional modeling: Quantifying Aerosol Subgrid Variability". United States. doi:10.1002/2017JD026567.
@article{osti_1374643,
title = {Quantification of marine aerosol subgrid variability and its correlation with clouds based on high-resolution regional modeling: Quantifying Aerosol Subgrid Variability},
author = {Lin, Guangxing and Qian, Yun and Yan, Huiping and Zhao, Chun and Ghan, Steven J. and Easter, Richard and Zhang, Kai},
abstractNote = {One limitation of most global climate models (GCMs) is that with the horizontal resolutions they typically employ, they cannot resolve the subgrid variability (SGV) of clouds and aerosols, adding extra uncertainties to the aerosol radiative forcing estimation. To inform the development of an aerosol subgrid variability parameterization, here we analyze the aerosol SGV over the southern Pacific Ocean simulated by the high-resolution Weather Research and Forecasting model coupled to Chemistry. We find that within a typical GCM grid, the aerosol mass subgrid standard deviation is 15% of the grid-box mean mass near the surface on a 1 month mean basis. The fraction can increase to 50% in the free troposphere. The relationships between the sea-salt mass concentration, meteorological variables, and sea-salt emission rate are investigated in both the clear and cloudy portion. Under clear-sky conditions, marine aerosol subgrid standard deviation is highly correlated with the standard deviations of vertical velocity, cloud water mixing ratio, and sea-salt emission rates near the surface. It is also strongly connected to the grid box mean aerosol in the free troposphere (between 2 km and 4 km). In the cloudy area, interstitial sea-salt aerosol mass concentrations are smaller, but higher correlation is found between the subgrid standard deviations of aerosol mass and vertical velocity. Additionally, we find that decreasing the model grid resolution can reduce the marine aerosol SGV but strengthen the correlations between the aerosol SGV and the total water mixing ratio (sum of water vapor, cloud liquid, and cloud ice mixing ratios).},
doi = {10.1002/2017JD026567},
journal = {Journal of Geophysical Research: Atmospheres},
number = 12,
volume = 122,
place = {United States},
year = {Fri Jun 16 00:00:00 EDT 2017},
month = {Fri Jun 16 00:00:00 EDT 2017}
}