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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 2
Atmos. Meas. Tech., 11, 1019-1030, 2018
https://doi.org/10.5194/amt-11-1019-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 11, 1019-1030, 2018
https://doi.org/10.5194/amt-11-1019-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 22 Feb 2018

Research article | 22 Feb 2018

Global spectroscopic survey of cloud thermodynamic phase at high spatial resolution, 2005–2015

David R. Thompson et al.
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Boardman, J. W. and Kruse, F. A.: Analysis of Imaging Spectrometer Data Using N-Dimensional Geometry and a Mixture-Tuned Matched Filtering Approach, IEEE T. Geosci. Remote, 49, 4138–4152, 2011.
Brown, L. D. and Levine, M.: Variance estimation in nonparametric regression via the difference sequence method, Ann. Stat., 35, 2219–2232, 2007.
Ceppi, P. and Hartmann, D. L.: Connections between clouds, radiation, and midlatitude dynamics: A review, Current Climate Change Reports, 1, 94–102, 2015.
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The distribution of ice and liquid particles in clouds (i.e., their thermodynamic phase) has a large impact on Earth's climate. We report a global high spatial resolution survey of cloud phase based on a decade of data from the Hyperion orbital imaging spectrometer. Seasonal and latitudinal trends corroborate observations by the Atmospheric Infrared Sounder (AIRS). Most variance observed at climate model grid scales of 100 km is explained by spatial structure at finer spatial resolutions.
The distribution of ice and liquid particles in clouds (i.e., their thermodynamic phase) has a...
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