Developing a Lagrangian Frame Transformation on Satellite Data to Study Cloud Microphysical Transitions in Arctic Marine Cold Air Outbreaks

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https://essopenarchive.org/users/900658/articles/1276093-developing-a-lagrangian-frame-transformation-on-satellite-data-to-study-cloud-microphysical-transitions-in-arctic-marine-cold-air-outbreaks?commit=740bb5589dd322fa9ca5489b4c7e16a9b77297e9

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https://doi.org/10.22541/au.174188980.08184748/v1
 http://hdl.handle.net/11603/38040

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UMBC Faculty Collection
UMBC GESTAR II
UMBC Joint Center for Earth Systems Technology (JCET)
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https://orcid.org/0000-0002-9233-5638
 https://orcid.org/0000-0001-9491-1654

Date

2025-03-13

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journal articles
preprints
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This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
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Abstract

Arctic marine cold air outbreaks (CAOs) generate distinct and dynamic cloud regimes due to intense air-sea interactions. To understand the temporal evolution of CAO cloud properties and compare different CAO events, a Lagrangian perspective is particularly useful. We developed a novel technique that enables the conversion of inherently Eulerian satellite data into a Lagrangian framework, combining the broad spatiotemporal coverage of satellite observations with the advantages of Lagrangian tracking. This technique was applied to eight CAO cases associated with a recent field campaign. Our results reveal a striking contrast among the cases in terms of cloud-top phase transitions, providing new insights into the evolution of CAO cloud properties.