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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Volume 17, issue 9 | Copyright
Atmos. Chem. Phys., 17, 5973-5989, 2017
https://doi.org/10.5194/acp-17-5973-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 16 May 2017

Research article | 16 May 2017

Cloud vertical distribution from combined surface and space radar–lidar observations at two Arctic atmospheric observatories

Yinghui Liu1, Matthew D. Shupe2, Zhien Wang3, and Gerald Mace4 Yinghui Liu et al.
  • 1Cooperative Institute of Meteorological Satellite Studies, University of Wisconsin at Madison, Madison, WI, USA
  • 2Cooperative Institute for Research in Environmental Sciences, University of Colorado and NOAA Earth System Research Laboratory, Boulder, CO, USA
  • 3Department of Atmospheric Science, University of Wyoming, Laramie, WY, USA
  • 4Atmospheric Sciences, University of Utah, Salt Lake City, UT, USA

Abstract. Detailed and accurate vertical distributions of cloud properties (such as cloud fraction, cloud phase, and cloud water content) and their changes are essential to accurately calculate the surface radiative flux and to depict the mean climate state. Surface and space-based active sensors including radar and lidar are ideal to provide this information because of their superior capability to detect clouds and retrieve cloud microphysical properties. In this study, we compare the annual cycles of cloud property vertical distributions from space-based active sensors and surface-based active sensors at two Arctic atmospheric observatories, Barrow and Eureka. Based on the comparisons, we identify the sensors' respective strengths and limitations, and develop a blended cloud property vertical distribution by combining both sets of observations. Results show that surface-based observations offer a more complete cloud property vertical distribution from the surface up to 11km above mean sea level (a.m.s.l.) with limitations in the middle and high altitudes; the annual mean total cloud fraction from space-based observations shows 25–40% fewer clouds below 0.5km than from surface-based observations, and space-based observations also show much fewer ice clouds and mixed-phase clouds, and slightly more liquid clouds, from the surface to 1km. In general, space-based observations show comparable cloud fractions between 1 and 2kma.m.s.l., and larger cloud fractions above 2kma.m.s.l. than from surface-based observations. A blended product combines the strengths of both products to provide a more reliable annual cycle of cloud property vertical distributions from the surface to 11kma.m.s.l. This information can be valuable for deriving an accurate surface radiative budget in the Arctic and for cloud parameterization evaluation in weather and climate models. Cloud annual cycles show similar evolutions in total cloud fraction and ice cloud fraction, and lower liquid-containing cloud fraction at Eureka than at Barrow; the differences can be attributed to the generally colder and drier conditions at Eureka relative to Barrow.

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Detailed and accurate vertical distributions of cloud properties are essential to accurately calculate the surface radiative flux and to depict the mean climate state, and such information is more desirable in the Arctic due to its recent rapid changes and the challenging observation conditions. This study presents a feasible way to provide such information by blending cloud observations from surface and space-based instruments with the understanding of their respective strength and limitations.
Detailed and accurate vertical distributions of cloud properties are essential to accurately...
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