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Covariance Between Arctic Sea Ice and Clouds Within Atmospheric State Regimes at the Satellite Footprint LevelUnderstanding the cloud response to sea ice change is necessary for modeling Arctic climate. Previous work has primarily addressed this problem from the interannual variability perspective. This paper provides a refined perspective of sea ice-cloud relationship in the Arctic using a satellite footprint-level quantification of the covariance between sea ice and Arctic low cloud properties from NASA A-Train active remote sensing data. The covariances between Arctic low cloud properties and sea ice concentration are quantified by first partitioning each footprint into four atmospheric regimes defined using thresholds of lower tropospheric stability and mid-tropospheric vertical velocity. Significant regional variability in the cloud properties is found within the atmospheric regimes indicating that the regimes do not completely account for the influence of meteorology. Regional anomalies are used to account for the remaining meteorological influence on clouds. After accounting for meteorological regime and regional influences, a statistically significant but weak covariance between cloud properties and sea ice is found in each season for at least one atmospheric regime. Smaller average cloud fraction and liquid water are found within footprints with more sea ice. The largest-magnitude cloud-sea ice covariance occurs between 500m and 1.2 km when the lower tropospheric stability is between 16 and 24 K. The covariance between low cloud properties and sea ice is found to be largest in fall and is accompanied by significant changes in boundary layer temperature structure where larger average near-surface static stability is found at larger sea ice concentrations.
Document ID
20160010671
Acquisition Source
Langley Research Center
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Taylor, Patrick C.
(NASA Langley Research Center Hampton, VA, United States)
Kato, Seiji
(NASA Langley Research Center Hampton, VA, United States)
Xu, Kuan-Man
(NASA Langley Research Center Hampton, VA, United States)
Cai, Ming
(Florida State Univ. Tallahassee, FL, United States)
Date Acquired
August 31, 2016
Publication Date
December 28, 2015
Publication Information
Publication: Journal of Geophysical Research: Atmospheres
Volume: 120
Issue: 24
Subject Category
Earth Resources And Remote Sensing
Meteorology And Climatology
Report/Patent Number
NF1676L-20102
Funding Number(s)
CONTRACT_GRANT: NNH12ZDA001N
WBS: WBS 509496.02.08.06.93
Distribution Limits
Public
Copyright
Other

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