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Volume 10, issue 4
Earth Syst. Sci. Data, 10, 2279-2293, 2018
https://doi.org/10.5194/essd-10-2279-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Earth Syst. Sci. Data, 10, 2279-2293, 2018
https://doi.org/10.5194/essd-10-2279-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  14 Dec 2018

14 Dec 2018

Using CALIOP to estimate cloud-field base height and its uncertainty: the Cloud Base Altitude Spatial Extrapolator (CBASE) algorithm and dataset

Johannes Mülmenstädt1, Odran Sourdeval1, David S. Henderson2, Tristan S. L'Ecuyer2, Claudia Unglaub1, Leonore Jungandreas1, Christoph Böhm3, Lynn M. Russell4, and Johannes Quaas1 Johannes Mülmenstädt et al.
  • 1Institute of Meteorology, Universität Leipzig, Leipzig, Germany
  • 2University of Wisconsin at Madison, Madison, Wisconsin, USA
  • 3Institute for Geophysics and Meteorology, Universität zu Köln, Cologne, Germany
  • 4Scripps Institution of Oceanography, University of California, San Diego, San Diego, California, USA

Abstract. A technique is presented that uses attenuated backscatter profiles from the CALIOP satellite lidar to estimate cloud base heights of lower-troposphere liquid clouds (cloud base height below approximately 3km). Even when clouds are thick enough to attenuate the lidar beam (optical thickness τ5), the technique provides cloud base heights by treating the cloud base height of nearby thinner clouds as representative of the surrounding cloud field. Using ground-based ceilometer data, uncertainty estimates for the cloud base height product at retrieval resolution are derived as a function of various properties of the CALIOP lidar profiles. Evaluation of the predicted cloud base heights and their predicted uncertainty using a second statistically independent ceilometer dataset shows that cloud base heights and uncertainties are biased by less than 10%. Geographic distributions of cloud base height and its uncertainty are presented. In some regions, the uncertainty is found to be substantially smaller than the 480m uncertainty assumed in the A-Train surface downwelling longwave estimate, potentially permitting the most uncertain of the radiative fluxes in the climate system to be better constrained. The cloud base dataset is available at https://doi.org/10.1594/WDCC/CBASE.

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One of the key pieces of information about a cloud is how high its base is. Unlike cloud top, cloud base is hard to observe from a satellite perspective – the cloud blocks the view. But without using satellites, it is difficult to compile global datasets. Here we describe how we worked around the limitations of a cloud-detecting laser satellite to observe global cloud base heights. This dataset will expand our knowledge of the cloudy atmosphere and its interaction with the planetary surface.
One of the key pieces of information about a cloud is how high its base is. Unlike cloud top,...
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