Articles | Volume 18, issue 5
https://doi.org/10.5194/amt-18-1269-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-1269-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Mar 2025
Research article |
| 13 Mar 2025
| 13 Mar 2025
Mid-Atlantic nocturnal low-level jet characteristics: a machine learning analysis of radar wind profiles
Department of Physics, University of Maryland, Baltimore County (UMBC), Baltimore, MD 21250, USA
Goddard Earth Sciences Technology and Research (GESTAR) II, Baltimore, MD 20771, USA
John T. Sullivan
Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA
Belay Demoz
Department of Physics, University of Maryland, Baltimore County (UMBC), Baltimore, MD 21250, USA
Goddard Earth Sciences Technology and Research (GESTAR) II, Baltimore, MD 20771, USA
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Short summary
This paper presents a supervised-machine-learning approach for the automatic isolation of nocturnal low-level jets (NLLJs) using observations from a radar wind profiler. This analysis isolated 90 southwesterly NLLJs observed from May to September 2017–2021, highlighting key features in the evolution and morphology of the mid-Atlantic NLLJ.
This paper presents a supervised-machine-learning approach for the automatic isolation of...
