Statistical and neural network assessment of the climatology of fog and mist at Pula Airport in Croatia

<p>A study was conducted on the climatological characteristics of fog and mist at Pula Airport in the northeastern Adriatic, using statistical and machine learning approaches. The study utilized meteorological data from Pula Airport, along with satellite sea surface temperature (SST) data from...

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Main Authors: M. Zoldoš, T. Džoić, J. Jurković, F. Matić, S. Jambrošić, I. Ljuština, M. Telišman Prtenjak
Format: Article
Language:English
Published: Copernicus Publications 2025-04-01
Series:Nonlinear Processes in Geophysics
Online Access:https://npg.copernicus.org/articles/32/89/2025/npg-32-89-2025.pdf
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author M. Zoldoš
M. Zoldoš
T. Džoić
J. Jurković
F. Matić
S. Jambrošić
I. Ljuština
M. Telišman Prtenjak
author_facet M. Zoldoš
M. Zoldoš
T. Džoić
J. Jurković
F. Matić
S. Jambrošić
I. Ljuština
M. Telišman Prtenjak
author_sort M. Zoldoš
collection DOAJ
description <p>A study was conducted on the climatological characteristics of fog and mist at Pula Airport in the northeastern Adriatic, using statistical and machine learning approaches. The study utilized meteorological data from Pula Airport, along with satellite sea surface temperature (SST) data from two coastal areas west and east of the airport, to gain insights into the influence of sea temperature on fog formation. To identify weather patterns associated with the occurrence of fog and mist, wind and mean sea level pressure (MSLP) data from the fifth-generation reanalysis (ERA5) of the European Centre for Medium-Range Weather Forecasts (ECMWF) were analyzed using Growing Neural Gas (GNG), a machine learning algorithm. A notable finding was a declining trend in the frequency of fog and mist at the airport, which can be linked to the results of the GNG analysis of the ERA5 data. This analysis showed a decrease in synoptic patterns favorable for fog and mist. Fog occurs mainly between October and March and is primarily associated with weak westerly and northwesterly winds. Additionally, fog is more likely to occur when the sea surface temperature is higher than the air temperature. Mist has similar characteristics to fog, although it is more likely to occur with easterly winds.</p>
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spelling doaj-art-c58d3116858c472ebda59fcac188a5652025-08-20T02:24:33ZengCopernicus PublicationsNonlinear Processes in Geophysics1023-58091607-79462025-04-01328910610.5194/npg-32-89-2025Statistical and neural network assessment of the climatology of fog and mist at Pula Airport in CroatiaM. Zoldoš0M. Zoldoš1T. Džoić2J. Jurković3F. Matić4S. Jambrošić5I. Ljuština6M. Telišman Prtenjak7Risk Management Division, Erste & Steiermärkische Bank d.d., Rijeka, 51000, CroatiaAviation Meteorology department, Croatia Control Ltd., Velika Gorica, 10410, CroatiaLaboratory of Physical Oceanography, Institute of Oceanography and Fisheries, Split, 21000, CroatiaAviation Meteorology department, Croatia Control Ltd., Velika Gorica, 10410, CroatiaUniversity Department of Marine Studies, University of Split, Split, 21000, CroatiaAviation Meteorology department, Croatia Control Ltd., Velika Gorica, 10410, CroatiaAviation Meteorology department, Croatia Control Ltd., Velika Gorica, 10410, CroatiaDepartment of Geophysics, Faculty of Science, University of Zagreb, Zagreb, 10000, Croatia<p>A study was conducted on the climatological characteristics of fog and mist at Pula Airport in the northeastern Adriatic, using statistical and machine learning approaches. The study utilized meteorological data from Pula Airport, along with satellite sea surface temperature (SST) data from two coastal areas west and east of the airport, to gain insights into the influence of sea temperature on fog formation. To identify weather patterns associated with the occurrence of fog and mist, wind and mean sea level pressure (MSLP) data from the fifth-generation reanalysis (ERA5) of the European Centre for Medium-Range Weather Forecasts (ECMWF) were analyzed using Growing Neural Gas (GNG), a machine learning algorithm. A notable finding was a declining trend in the frequency of fog and mist at the airport, which can be linked to the results of the GNG analysis of the ERA5 data. This analysis showed a decrease in synoptic patterns favorable for fog and mist. Fog occurs mainly between October and March and is primarily associated with weak westerly and northwesterly winds. Additionally, fog is more likely to occur when the sea surface temperature is higher than the air temperature. Mist has similar characteristics to fog, although it is more likely to occur with easterly winds.</p>https://npg.copernicus.org/articles/32/89/2025/npg-32-89-2025.pdf
spellingShingle M. Zoldoš
M. Zoldoš
T. Džoić
J. Jurković
F. Matić
S. Jambrošić
I. Ljuština
M. Telišman Prtenjak
Statistical and neural network assessment of the climatology of fog and mist at Pula Airport in Croatia
Nonlinear Processes in Geophysics
title Statistical and neural network assessment of the climatology of fog and mist at Pula Airport in Croatia
title_full Statistical and neural network assessment of the climatology of fog and mist at Pula Airport in Croatia
title_fullStr Statistical and neural network assessment of the climatology of fog and mist at Pula Airport in Croatia
title_full_unstemmed Statistical and neural network assessment of the climatology of fog and mist at Pula Airport in Croatia
title_short Statistical and neural network assessment of the climatology of fog and mist at Pula Airport in Croatia
title_sort statistical and neural network assessment of the climatology of fog and mist at pula airport in croatia
url https://npg.copernicus.org/articles/32/89/2025/npg-32-89-2025.pdf
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