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      Variability of Bulk Water Vapor Content in the Marine Cloudy Boundary Layers from Microwave and Near-Infrared Imagery

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      Atmospheric Chemistry and Physics Discussions
      Copernicus GmbH

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          Abstract

          <p><strong>Abstract.</strong> This work uses the synergy of collocated microwave radiometry and near-infrared imagery to study the marine boundary layer water vapor. The Advanced Microwave Scanning Radiometer (AMSR) provides the total column water vapor, while the Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared imagery provides the water vapor above the cloud layers. The difference between the two gives the vapor between the surface and the cloud top, which may be interpreted as the boundary layer water vapor under certain conditions. As a by product of this algorithm, we also store cloud top information of the MODIS pixels used, a proxy for the inversion height, as well as the sea surface temperature and total column water vapor from the AMSR measurements. Hence, the AMSR-MODIS dataset provides several of the variables associated with the boundary layer thermodynamic structure. Comparisons against radiosondes, and GPS-Radio Occultation data demonstrate the robustness of these boundary layer water vapor estimates. We explore the annual cycle of the number of observations as a proxy for stratus cloud amount, in well known stratus regions; we then exploit the 16 years of AMSR-MODIS synergy to study for the first time the annual variations of the boundary layer water vapor in comparison to the sea surface temperature and the boundary layer cloud top height (equivalent to the inversion height) climatologies, and lastly, we explore the climatological behavior of these variables on stratocumulus-to-cumulus transitions.</p>

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          Author and article information

          Journal
          Atmospheric Chemistry and Physics Discussions
          Atmos. Chem. Phys. Discuss.
          Copernicus GmbH
          1680-7375
          February 14 2019
          : 1-22
          Article
          10.5194/acp-2019-4
          0d4c3433-2b5d-4e22-a789-d89c72f86e68
          © 2019

          https://creativecommons.org/licenses/by/4.0/

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