Editorial Type:
Article
Article Type:
Research Article

A Synergistic Analysis of Cloud Cover and Vertical Distribution from A-Train and Ground-Based Sensors over the High Arctic Station Eureka from 2006 to 2010

Yann Blanchard Laboratoire Atmosphères, Milieux, Observations Spatiales, UPMC-UVSQ-CNRS, Paris, France

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Jacques Pelon Laboratoire Atmosphères, Milieux, Observations Spatiales, UPMC-UVSQ-CNRS, Paris, France

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Edwin W. Eloranta Space Science and Engineering Center, University of Wisconsin–Madison, Madison, Wisconsin

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Kenneth P. Moran Physical Sciences Division, NOAA/Earth System Research Laboratory, Boulder, Colorado

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Julien Delanoë Laboratoire Atmosphères, Milieux, Observations Spatiales, UPMC-UVSQ-CNRS, Paris, France

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Geneviève Sèze Laboratoire de Météorologie Dynamique du CNRS, Ecole Polytechnique, Palaiseau, France

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Print Publication:
01 Nov 2014
DOI:
https://doi.org/10.1175/JAMC-D-14-0021.1
Page(s):
2553–2570
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Abstract

Active remote sensing instruments such as lidar and radar allow one to accurately detect the presence of clouds and give information on their vertical structure and phase. To better address cloud radiative impact over the Arctic area, a combined analysis based on lidar and radar ground-based and A-Train satellite measurements was carried out to evaluate the efficiency of cloud detection, as well as cloud type and vertical distribution, over the Eureka station (80°N, 86°W) between June 2006 and May 2010. Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat data were first compared with independent ground-based cloud measurements. Seasonal and monthly trends from independent observations were found to be similar among all datasets except when compared with the weather station observations because of the large reported fraction of ice crystals suspended in the lower troposphere in winter. Further investigations focused on satellite observations that are collocated in space and time with ground-based data. Cloud fraction occurrences from ground-based instruments correlated well with both CALIPSO operational products and combined CALIPSO–CloudSat retrievals, with a hit rate of 85%. The hit rate was only 77% for CloudSat products. The misdetections were mainly attributed to 1) undetected low-level clouds as a result of sensitivity loss and 2) missed clouds because of the distance between the satellite track and the station. The spaceborne lidar–radar synergy was found to be essential to have a complete picture of the cloud vertical profile down to 2 km. Errors are quantified and discussed.

Corresponding author address: Yann Blanchard, LATMOS, Boîte 102, Université Pierre et Marie, Curie, 4 place Jussieu, 75252 Paris CEDEX 05, France. E-mail: yann.blanchard@latmos.ipsl.fr

Abstract

Active remote sensing instruments such as lidar and radar allow one to accurately detect the presence of clouds and give information on their vertical structure and phase. To better address cloud radiative impact over the Arctic area, a combined analysis based on lidar and radar ground-based and A-Train satellite measurements was carried out to evaluate the efficiency of cloud detection, as well as cloud type and vertical distribution, over the Eureka station (80°N, 86°W) between June 2006 and May 2010. Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat data were first compared with independent ground-based cloud measurements. Seasonal and monthly trends from independent observations were found to be similar among all datasets except when compared with the weather station observations because of the large reported fraction of ice crystals suspended in the lower troposphere in winter. Further investigations focused on satellite observations that are collocated in space and time with ground-based data. Cloud fraction occurrences from ground-based instruments correlated well with both CALIPSO operational products and combined CALIPSO–CloudSat retrievals, with a hit rate of 85%. The hit rate was only 77% for CloudSat products. The misdetections were mainly attributed to 1) undetected low-level clouds as a result of sensitivity loss and 2) missed clouds because of the distance between the satellite track and the station. The spaceborne lidar–radar synergy was found to be essential to have a complete picture of the cloud vertical profile down to 2 km. Errors are quantified and discussed.

Corresponding author address: Yann Blanchard, LATMOS, Boîte 102, Université Pierre et Marie, Curie, 4 place Jussieu, 75252 Paris CEDEX 05, France. E-mail: yann.blanchard@latmos.ipsl.fr
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