DOE OSTI · 2565086
Developing a Lagrangian Frame Transformation on Satellite Data to Study Cloud Microphysical Transitions in Arctic Marine Cold Air Outbreaks
Abstract
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.
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Seppala, Hannah [Physics Department University of Maryland, Baltimore County (UMBC) Baltimore MD USA] (ORCID:0000000292335638), Zhang, Zhibo [Physics Department University of Maryland, Baltimore County (UMBC) Baltimore MD USA, Goddard Earth Sciences Technology and Research (GESTAR) II UMBC Baltimore MD USA] (ORCID:0000000194911654), Zheng, Xue [Atmospheric, Earth, and Energy Division, Lawrence Livermore National Laboratory Livermore CA USA] (ORCID:0000000293721776). 2025-05-08. Developing a Lagrangian Frame Transformation on Satellite Data to Study Cloud Microphysical Transitions in Arctic Marine Cold Air Outbreaks. https://doi.org/10.1029/2025gl115637
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