Time Series Clustering of Sea Surface Temperature in the Mediterranean and Black Sea Marine System

ABSTRACT Sea surface temperature (SST) is a significant climatic variable that affects the climate of the Earth. Monitoring a location's SST pattern is useful for several research areas, including weather forecasting and climate change. In this study, the emerging hot spot and cold spot patterns of SST in the Mediterranean and Black Sea Marine System (MBMS) were examined, the spatial distribution characteristics and temporal changes of SST in the sub‐basins were analysed, and future predictions were made. A distinctive aspect of the research lies in the introduction of novel techniques, specifically the application of space time cube and evolving hot spot analysis, for visualising and evaluating SST in the MBMS. This approach sets the study apart by pioneering the utilisation of these methods in this particular context. In the examined region, SST demonstrates a decreasing trend from east to west and from south to north. The forecast suggests that this spatial distribution pattern will persist in 2033, further accentuated by the intensification of the warming effect. Nine different time series clusters are defined within this distribution pattern. Although it changes seasonally, the prevailing statistically significant hot spots in the study area are primarily characterised by new hot spots, intensifying hot spots, sporadic hot spots and oscillating hot spots. The trends of hot and cold spot clusters, along with SST values, were assessed for all sub‐basins in the MBMS. Conversely, the observed clustering category among statistically significant cold spots is identified as persistent cold spots, diminishing cold spots, sporadic cold spots, oscillating cold spots and historical cold spots. The spatiotemporal analysis in this research has provided notable insights, offering a spatial context to the previously explored temporal trends of SST in the MBMS.

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Publication Details

Journal
International Journal of Climatology
Published
2024-11-15
DOI
https://doi.org/10.1002/joc.8687
Citations
3
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
0.85
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article

Time Series Clustering of Sea Surface Temperature in the Mediterranean and Black Sea Marine System

Şevki DANACIOĞLU, Şermin Tağıl, Nami Yurtseven
3 citations
International Journal of Climatology
Climate variability and models
0.85
article

Time Series Clustering of Sea Surface Temperature in the Mediterranean and Black Sea Marine System

Şevki DANACIOĞLU, Şermin Tağıl, Nami Yurtseven
article en
3 citations

Abstract

ABSTRACT Sea surface temperature (SST) is a significant climatic variable that affects the climate of the Earth. Monitoring a location's SST pattern is useful for several research areas, including weather forecasting and climate change. In this study, the emerging hot spot and cold spot patterns of SST in the Mediterranean and Black Sea Marine System (MBMS) were examined, the spatial distribution characteristics and temporal changes of SST in the sub‐basins were analysed, and future predictions were made. A distinctive aspect of the research lies in the introduction of novel techniques, specifically the application of space time cube and evolving hot spot analysis, for visualising and evaluating SST in the MBMS. This approach sets the study apart by pioneering the utilisation of these methods in this particular context. In the examined region, SST demonstrates a decreasing trend from east to west and from south to north. The forecast suggests that this spatial distribution pattern will persist in 2033, further accentuated by the intensification of the warming effect. Nine different time series clusters are defined within this distribution pattern. Although it changes seasonally, the prevailing statistically significant hot spots in the study area are primarily characterised by new hot spots, intensifying hot spots, sporadic hot spots and oscillating hot spots. The trends of hot and cold spot clusters, along with SST values, were assessed for all sub‐basins in the MBMS. Conversely, the observed clustering category among statistically significant cold spots is identified as persistent cold spots, diminishing cold spots, sporadic cold spots, oscillating cold spots and historical cold spots. The spatiotemporal analysis in this research has provided notable insights, offering a spatial context to the previously explored temporal trends of SST in the MBMS.

International Journal of ClimatologyVol. 44(16)
Izmir University (TR), Bakırçay Üniversitesi
Life below water
Openalex Percentile: Top 27%
Climate variability and models
0.85
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