Machine learning analysis and nowcasting of marine fog visibility using FATIMA Grand Banks campaign measurements

Gultepe, Eren; Wang, Sen; Blomquist, Byron; Fernando, Harindra J. S.; Kreidl, O. Patrick; Delene, David J.; Gultepe, Ismail

doi:10.3389/feart.2023.1321422

i

Machine learning analysis and nowcasting of marine fog visibility using FATIMA Grand Banks campaign measurements

2024
By Gultepe, Eren ; Wang, Sen ; Blomquist, Byron ; ...

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Journal Title:

Frontiers in Earth Science
Personal Author:

Gultepe, Eren ; Wang, Sen ; Blomquist, Byron ; Fernando, Harindra J. S. ; Kreidl, O. Patrick ; Delene, David J. ; Gultepe, Ismail
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; CIRES (Cooperative Institute for Research in Environmental Sciences) ; PSL (Physical Sciences Laboratory)
Description:

This study presents the application of machine learning (ML) to evaluate marine fog visibility conditions and nowcasting of visibility based on the FATIMA (Fog and turbulence interactions in the marine atmosphere) campaign observations collected during July 2022 in the North Atlantic in the Grand Banks area and vicinity of Sable Island, northeast of Canada.
Source:

Frontiers in Earth Science, 11
DOI:

https://doi.org/10.3389/feart.2023.1321422
ISSN:

2296-6463
Format:

pdf
Publisher:

Frontiers Media SA
Document Type:

Journal Article
License:

https://creativecommons.org/licenses/by/4.0/
Rights Information:

CC BY
Compliance:

Library
Main Document Checksum:

urn:sha-512:de676be3e8d121cb3e4c32894b723de571a627b52d6d376afcd7447e963fb64682c892326f5c4108e1c1fb64dcb3f4098b9f2f3ee4fe4a91a2566d127395ab39
Download URL:

https://repository.library.noaa.gov/view/noaa/69534/noaa_69534_DS1.pdf
File Type:

[PDF - 48.11 MB ]

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