Preprints
https://doi.org/10.5194/egusphere-2024-1601
https://doi.org/10.5194/egusphere-2024-1601
05 Jun 2024
 | 05 Jun 2024
Status: this preprint is open for discussion.

Synoptic background of the Adriatic Sea high-frequency sea-level extremes

Krešimir Ruić, Jadranka Šepić, and Marin Vojković

Abstract. Large oscillations in sea-level can pose significant threats to coastal communities and endanger infrastructure. The large sea-level variations are driven by different physical processes that occur on various spatial and temporal scales. This study focuses on the high-frequency component (periods shorter than 2 hours) of sea-level oscillations, particularly those induced by atmospheric processes. Episodes of extreme high-frequency sea level oscillations were identified at six tide gauge stations in the Adriatic Sea using the peak-over-threshold method. The length of time series was ~17 years. Characteristic synoptic situations preceding the Extremes were extracted using the k-medoid clustering method applied on the ERA5 reanalysis data. Analyses were conducted on the following ERA5 fields: mean sea-level pressure (MSLP), temperature at 850 hPa, and geopotential at 500 hPa. The structural similarity index measure (SSIM) was used as the distance metric. The data were divided into a training set (from the start of measurements to the beginning of 2018) and a testing set (from the beginning of 2018 to the end of 2020). For each station, k-medoid method was applied for selection of both 2 and 3 characteristic clusters. Two types of synoptic situations leading to extreme high-frequency sea level oscillations were extracted for all stations: “bad-weather” situation which favours both storm surges and intense high-frequency sea level oscillations, and “good-weather” situation which favours only intense high-frequency sea-level oscillations. The two situations mostly differ in surface fields, with the “bad-weather” situation characterised by larger MSLP gradients over the Adriatic and stronger surface winds. At higher levels, situations are more similar, and mostly described by inflow of warm air from the south-west and strong westerly to south-westerly jet stream. Inclusion of the third clusters led to refinement of one of two characteristic situations at all stations aside for Bakar and Rovinj where it led to a new “bora (strong north-easterly wind) -favourable” situation. The extracted clusters were used to label all days of the testing period, with particular attention given to days in which episodes of extreme high-frequency sea-level oscillations occurred. The potential of using k-medoid method for future prediction of these high-frequency, atmospherically induced sea-level oscillations is discussed.

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Krešimir Ruić, Jadranka Šepić, and Marin Vojković

Status: open (until 31 Jul 2024)

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Krešimir Ruić, Jadranka Šepić, and Marin Vojković
Krešimir Ruić, Jadranka Šepić, and Marin Vojković

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Short summary
Identifying the driving processes of intense sea-level (SL) oscillations has been the goal of many scientific endeavors. Our study focuses on intense SL oscillations in the Adriatic Sea resulting from atmospheric processes. Using machine learning methods, we identified several synoptic situations during which these oscillations occur. This can aid future predictions of extreme SL events, potentially reducing infrastructure damage and protecting lives.