Seppala, HannahZhang, ZhiboZheng, Xue2025-04-232025-04-232025-03-13https://doi.org/10.22541/au.174188980.08184748/v1http://hdl.handle.net/11603/38040Arctic 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.47 pagesen-USThis 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.Public Domainhttps://creativecommons.org/publicdomain/mark/1.0/Text