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Relationship between marine boundary layer clouds and lower tropospheric...

Yue, Q., B. Kahn, E. J. Fetzer, and J. Teixeira (2011), Relationship between marine boundary layer clouds and lower tropospheric stability observed by AIRS, CloudSat, and CALIOP, J. Geophys. Res., 116, D18212, doi:10.1029/2011JD016136.

Thirteen months of matched temperature and water vapor profiles from the Atmospheric Infrared Sounder (AIRS), collocated European Centre for Medium‐Range Weather Forecasts (ECMWF) model analyses, National Centers for Environmental Prediction‐National Center for Atmospheric Research reanalysis, and cloud profiles from the CloudSat and Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) instruments are investigated to quantify aspects of maritime boundary layer (MBL) clouds and their thermodynamic environment. This study highlights the strengths and limitations of this multisensor A‐Train approach. The AIRS retrieval yield (percentage of high‐quality temperature and water vapor profiles to the surface) over the oceans between 40°S and 40°N within MBL clouds is between 61% and 71% globally and is greater than 80%–90% throughout most of the subtropics. The lower tropospheric stability (LTS) and estimated inversion strength (EIS) are derived from AIRS temperature and water vapor profiles over the global oceans as well as from collocated ECMWF model analysis data. Positive values of EIS derived from AIRS well represent MBL conditions, demonstrating that AIRS contains quantitatively useful information with regard to relative changes in dynamic range of temperature and water vapor in the MBL. The relative magnitude and seasonality of LTS and EIS from the collocated satellite data set in stratocumulus regions are very similar to spatially and temporally collocated ECMWF model analyses, but differences are found between different subsampling criteria of reanalysis data. For coincident vertical profiles, the MBL in AIRS data shows a more smoothed structure than that of ECMWF. This multisensor investigation establishes a basis for using A‐train observations to quantify elements of low cloud‐climate feedback.

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