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  • Küçük Resim
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    Observed and projected geographical and temporal changes in the Köppen-Geiger climate types in Türkiye
    (Springer, 2025) Türkeş, Murat; Yurtseven, Nami
    This study aimed at comparing the geographical and climatological changes in the spatial distributions and average elevations of Türkiye’s recent past (1961 − 1990) present (1991 − 2020) and projected future climate types in detail via the Köppen-Geiger (K-G) classification. The future K-G climate types were examined for the periods of 2041–2070 and 2071–2099 based on low (SSP1 − 2.6), medium (SSP2-4.5), and very high (SSP5-8.5) Shared Socioeconomic Pathways (SSP) scenarios. From 1961 − 1990 to 1991 − 2020, the mid-latitude semi-arid steppe (BSk), subtropical semi-arid steppe (BSh), and dry summer Mediterranean (Csa) climates expanded from 21.9% to 24.2%, 0.1% to 0.4%, and 28.9% to 31.8%, respectively. Conversely, the dry and warm summer cold (Dsb) climate decreased from 24% to 19.3%. Future projections, especially those under high emissions, reveal significant changes in the Dsb and Dfb (cold and humid with warm summer) climates. The main cold climate is expected to change toward drier and warmer cold climates. The current expansion of semi-arid steppe and Mediterranean climates and the contraction of the Dsb climate type can be seen as early indicators of the significant changes foreseen in future periods. As well, average elevations of climatic types will increase in both two future periods and two scenarios, especially in the very high scenarios. For example, under the very high scenario for the period of 2041 − 2070, the average elevations of the Cs, Cf, Ds, Df, and ET climates will increase by approximately 120 m, 220 m, 185 m, 290 m, and 1040 m, respectively. These results also show that the elevations and thicknesses of orographic-climatic vegetation layers may change; for example, the forest upper limit may be approximately 120–220 m higher in the future than in the present, for example, in humid temperate Black Sea forests. © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2025.
  • Küçük Resim
    Öğe
    Time series clustering of sea surface temperature in the Mediterranean and Black Sea marine system
    (Wiley, 2024) Tağıl, Şermin; Danacıoğlu, Şevki; Yurtseven, Nami
    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.