İklim ve Deniz Bilimleri
Bu koleksiyon için kalıcı URI
Gözat
Çıkarma tarihi ile İklim ve Deniz Bilimleri'a göz atma
Sayfa başına sonuç
Sıralama Seçenekleri
-
ÖgeThe merit of the North Sea-Caspian pattern in explaining climate variability in the Euro-Mediterranean region(Wiley, 2023) Çağlar, Ferat ; Yetemen, Onur ; Chun, Kwok Pan ; Şen, Ömer Lütfi ; orcid.org/0000-0002-2584-2883 ; orcid.org/0000-0003-1593-3519 ; orcid.org/0000-0001-9873-6240 ; orcid.org/0000-0002-8186-8594 ; İklim ve Deniz BilimleriTeleconnection patterns are one of the key features to understanding high-frequency natural climate variability. The North Sea-Caspian Pattern (NCP) was identified as a middle tropospheric dipole and its hydroclimatological implications have been substantially restricted to the Eastern Mediterranean region. Thus, the hydroclimatological influences of the NCP in the Euro-Mediterranean region were investigated via a comparative approach with dominant tropospheric teleconnections in the Eurasian region and synoptic features such as ridge-trough positioning and strength. By using high-resolution ERA5 reanalysis data, cross-correlations between indexes, anticorrelations at 500 hPa and composite anomaly maps for seasonally representative months were produced to understand the working mechanism of the NCP. Comparisons included the East Atlantic/Western Russian (EAWR) pattern, a rotated principal component analysis (RPCA) variant of NCP which utilizes pole-based representation. Analysis revealed that the NCP was correlated well with the Mediterranean trough displacement and with the strength of the East Asian trough. Climate anomalies indicated by the NCP were greater and more spatially consistent compared to other teleconnections. The NCP also showed higher contrasts of temperature and precipitation than the EAWR based on the composite anomaly maps. In conclusion, the NCP explained climate variability in all seasons linking remote centres of action within Eurasia's east and west extremes.
-
ÖgeModel-based prediction of water levels for the Great Lakes: a comparative analysis(Springer, 2024) Kurt, Onur ; 0000-0002-4486-2257 ; İklim ve Deniz BilimleriThis comprehensive study addresses the correlation between water levels and meteorological features, including air temperature, evaporation, and precipitation, to accurately predict water levels in lakes within the Great Lakes basin. Various models, namely multiple linear regression (MLR), nonlinear autoregressive network with exogenous inputs (NARX), Facebook Prophet (FB-Prophet), and long short-term memory (LSTM), are employed to enhance predictions of lake water levels. Results indicate that all models, except for FB-Prophet, perform well, particularly for Lakes Erie, Huron-Michigan, and Superior. However, MLR and LSTM show reduced performance for Lakes Ontario and St. Clair. NARX emerges as the top performer across all lakes, with Lakes Erie and Superior exhibiting the lowest error metrics—root mean square error (RMSE: 0.048 and 0.034), mean absolute error (MAE: 0.036 and 0.026), mean absolute percent error (MAPE: 0.021% and 0.014%), and alongside the highest R-squared value (R2: 0.977 and 0.968), respectively. Similarly, for Lake Huron-Michigan, NARX demonstrates exceptional predictive precision with an RMSE (0.029), MAE (0.022), MAPE (0.013%), and an outstanding R2 value of 0.995. Despite slightly higher error metrics, NARX consistently performs well for Lake Ontario. However, Lake St. Clair presents challenges for predictive performance across all models, with NARX maintaining relatively strong metrics with an RMSE (0.076), MAE (0.050), MAPE (0.029%), and R2 (0.953), reaffirming its position as the leading model for water level prediction in the Great Lakes basin. The findings of this study suggest that the NARX model accurately predicts water levels, providing insights for managing water resources in the Great Lakes region.
-
ÖgeImpact of atmospheric rivers on the winter snowpack in the headwaters of Euphrates-Tigris basin(Springer, 2024) Ezber, Yasemin ; Bozkurt , D. ; Şen, Ömer Lütfi ; 0000-0002-4512-685X ; 0000-0002-8186-8594 ; İklim ve Deniz BilimleriUnderstanding the hydrometeorological impacts of atmospheric rivers (ARs) on mountain snowpack is crucial for water resources management in the snow-fed river basins such as the Euphrates-Tigris (ET). In this study, we investigate the contribution of wintertime (December-January–February) ARs to precipitation and snowpack in the headwater regions of the ET Basin for the period of 1979–2019 using a state-of-the-art AR catalog and ERA5 reanalysis data. The results show that AR days in the headwaters region could be warmer by up to 3 °C and wetter by over 5 mm day−1 compared to non-AR days. The contribution of ARs to the total winter precipitation varies from year to year, with a maximum contribution of over 80% in 2010 and an average contribution of 60% over the 40-year period. While snow accumulation on AR days shows spatial variability, the average snow contribution is 27% of the seasonal average, ranging from 12 to 57% for different years. The south-facing parts of the mountain range experience significant snowmelt, with contributions ranging from 15 to 80% for different years. The high total precipitation (60%) and low snowpack (27%) contribution can be attributed to the semi-arid characteristics of the region and the occurrence of rain-on-snow events, where rain falling on existing snow rapidly melts the snowpack. The findings have implications for water resource management and call for continued research to improve our knowledge of ARs and their interactions with the complex terrain of the ET Basin.
-
ÖgeLatitude or altitude as the future refugium? A case for the future of forests in Asia Minor and its surroundings(Wiley, 2024) Ekberzade, Bikem ; Yetemen, Ömer ; Ezber, Yasemin ; Şen, Ömer Lütfi ; Dalfes, Hasan Nüzhet ; orcid.org/0000-0002-3271-2040 ; orcid.org/0000-0003-1593-3519 ; orcid.org/0000-0002-4512-685X ; orcid.org/0000-0002-8186-8594 ; orcid.org/0000-0002-2522-8381 ; İklim ve Deniz BilimleriAt the current juncture with climate change, centennial projections of species distributions in biodiversity hotspots, using dynamic vegetation models may provide vital insight into conservation efforts. This study aims to answer: (1) if climate change progresses under a business-as-usual scenario of anthropogenic emissions for this century, how may the forest ranges be affected? (2) will there be potential regional extinctions of the taxa simulated? (3) may any site emerge as a potential refugium? Study Area: Anatolian Peninsula and its surroundings, longitudes 24–50° E, latitudes 33–46° N. Time Period: 1961-2100. Major Taxa Studied: 25 woody species and a C3 grass-type. Method: Keeping a spatial window large enough to track potential changes in the vegetation range and composition especially in the mountain ranges within the study area, we parameterized a process-based regional-to-global dynamic vegetation model (LPJ-GUESS v 4.1), forced it with ERA5-Land reanalysis for the historical period, and five different bias-corrected centennial global circulation model (GCM) datasets under SSP5-8.5, and simulated the dynamic responses of key forest species. Bivariate spatio-temporal maps from the simulation results were constructed for final analysis. Results: A significant increase in woody taxa biomass for the majority of our study area, towards the end of the century was simulated, where temperate taxa with high tolerance for drought and a wider range of temperatures took dominance. The mountain ranges in our study area stood out as critical potential refugia for cold favoring species. There were no regional extinctions of taxa, however, important changes in areal dominance and potential future forest composition were simulated. Main Conclusions: Our simulation results suggest a high potential for future forest cover in our study region by the end of the century under a high emissions scenario, sans human presence, with important changes in vegetation composition, including encroachment of grasslands ecosystems by woody taxa.