Jūros karščio bangų dinamija ir tendencijos pietryčių Baltijos jūroje
Servaitė, Inesa |
Konsultantas / Consultant |
Klimato kaita tampa vis rimtesne problema, veikiančia ne tik sausumos, bet ir vandens telkinius. Jūros karščio bangos yra trumpalaikės, bet ekstremalios temperatūros anomalijos, kurios pastaruoju metu vis dažniau pasireiškia Baltijos jūroje. Baltijos jūra tampa svarbi regiono tyrimams dėl sparčiai didėjančio vandens paviršiaus temperatūros ir unikalių okeanografinių sąlygų. Ilgalaikiai vandens temperatūros duomenys yra būtini, siekiant suprasti karščio bangų tendencijas, jų poveikį aplinkai bei visuomenei. Šiame tyrime naudojami ilgalaikiai in situ, palydoviniai ir hidrodinaminio modelio vandens paviršiaus temperatūros duomenys, siekiant išnagrinėti karščio bangų charakteristikas, jų pasiskirstymą ir dinamiką pietryčių Baltijos jūroje. Atlikus analizę, nustatyta, kad pietryčių Baltijos jūroje vidutiniškai susiformuoja 2 jūros karščio bangos kasmet, tik jų trukmė atskirais duomenų šaltiniais skiriasi: in situ duomenimis nustatyta, kad Palangoje jūros karščio bangos trukmė siekia 11 dienų, Nidoje – 10 dienų, palydoviniais duomenimis taip pat 11 dienų, hidrodinaminio modelio duomenimis ilgiausiai – 16 dienų. Visais atvejais vidutinis jūros karščio bangų intensyvumas (vandens temperatūros skirtumas nuo 90-ojo procentilio) siekia apie 1 °C. Atskirų mėnesių (gegužė−rugpjūtis) analizė atskleidė, kad visais tyrimo mėnesiais susiformuoja bent vienas jūros karščio bangos atvejis, ilgiausiai trunkančios birželį arba liepos mėnesiais (apie 2 savaites). Vertinant jūros karščio bangų kategorijas nustatyta, kad pietryčių Baltijos jūroje susiformuoja visų keturių kategorijų jūros karščio bangos. Skirtumai tarp duomenų šaltinių rezultatų nustatyti dėl palydovinių nuotraukų trūkumo, jų debesuotumo, duomenų šaltinių vandens temperatūros matavimų skirtingų gylių bei metodikos.
Climate change is becoming an increasingly serious problem affecting not only land, but also bodies of water. Marine heatwaves are short-lived, but extreme temperature anomalies that have recently become more common in the Baltic Sea. The Baltic Sea is becoming important for research in the region due to rapidly increasing water surface temperatures and unique oceanographic conditions. Long-term water temperature data is necessary in order to understand the trends of heatwaves, their impact on the environment and society. In this study, long-term in situ (1993-2023), satellite (2000-2023), and hydrodynamic modelling (1994-2023) water surface temperature data is used, in order to study the characteristics of marine heatwaves, their distribution and dynamics in the southeastern Baltic Sea. For the validation of satellite and model datasets, the following statistical indicators were used: correlation coefficient, coefficient of determination, standard error, root mean square error, relative bias, and the Nash–Sutcliffe efficiency. The results showed that satellite and model data fit the measurements quiet well, having high coefficients of determination (0.48–1.27), relative bias (−2.67–7.60 %), and Nash–Sutcliffe efficiency (0.74–1.00), as well as low mean errors (0.27–2.24 °C), meaning that it can be used for marine heatwave analysis. This study applies the methodology developed by Hobday (2016), which defines a marine heatwave as an event when the water temperature exceeds the 90th percentile for five or more consecutive days. The same methodology is also used to classify marine heatwaves into four categories. A two-day gap threshold is applied for all data sources: if there is a one- or two-days break between two marine heatwave events, they are considered as a single event. For satellite data, when gaps occur due to missing values, a five-day window were used. To evaluate marine heatwave categories, water temperature anomalies were calculated based on the difference between the climatological mean and the 90th percentile, as well as the local deviation between daily water temperature and the 90th percentile. Trends in marine heatwave occurrences, duration, and average intensity were assessed using linear regression analysis. The results showed, that on average, 2 heatwaves form in the southeastern Baltic Sea, only their duration differs according to the data sources: according to in situ data the average duration of marine heatwaves in Palanga reaches 11 days, in Nida – 10 days, according to satellite data – 11 days, and the longest according to hydrodynamic model data – 16 days. In all cases, the average intensity of the heatwave (water temperature difference from the 90th percentile) is around 1 °C. The analysis of individual months revealed that at least one marine heatwave is formed in every May-August month, usually the longest-lasting heatwave is in June or July (lasting around 2 weeks). The frequency and duration of marine heatwaves in the southeastern Baltic Sea show increasing trends. However, a statistically significant upward trend was identified only for the number of events based on satellite and hydrodynamic model data. The average marine heatwave intensity above the 90th percentile is increasing (not significantly) based on in situ data in Palanga, as well as hydrodynamic model and satellite data, while in Nida, based on in situ data, it is decreasing (also not significantly). The assessment of the marine heatwave categories revealed that all four categories of marine heatwaves form in the southeastern Baltic Sea. Based on in situ data, category I marine heatwaves are most frequently observed in Palanga and Nida, while satellite data indicate a predominance of category IV events, and the hydrodynamic model shows category II as the most frequent. Spatial analysis revealed that higher category marine heatwaves tend to form more frequently near the coast. The discrepancies in the results derived from different data sources can be attributed to the limited availability of satellite imagery, cloud cover, variations in water temperature measurement depths, and differences in methodology. For example, in this study, 955 satellite images were available, while the hydrodynamic model provided hourly data every day, which may have influenced the calculation of marine heatwave occurrences. Additionally, the measurement depths differed across all three data sources: in situ data were collected at a depth of 0.5 meters, hydrodynamic model calculates sea surface temperature from the bulk 1 meter depth, and satellite sensors scan the sea surface at a depth of 10–20 microns. These differences may have affected the estimation of marine heatwave intensity and category classification.