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Mediterranean biogeography is characterized as a global “hotspot” for climate change; understanding the impacts of these changes on local agricultural systems through high-resolution analyses has thus become a critical need. This study addresses this gap by evaluating the holistic effects of climate change on site-specific agriculture systems, focusing on the Eğirdir–Karacaören (EKB) and Beyşehir (BB) lake basins in the Lakes Region of Türkiye. This study employed machine learning modeling techniques to forecast changes in the yields of key crops, such as wheat, maize, apple, alfalfa, and sugar beet. Detailed spatial analyses of changes in agro-climatic conditions (heat stress, chilling requirement, frost days, and growing degree days for key crops) between the reference period (1995–2014) and two decadal periods projected for 2040–2049 and 2070–2079 were conducted under the Shared Socioeconomic Pathways (SSP3-7.0). Daily temperature, precipitation, relative humidity, and solar radiation data, derived from high-resolution climate simulations, were aggregated into annual summaries. These datasets were then spatially matched with district-level yield statistics obtained from the official data providers to construct crop-specific data matrices. For each crop, Random Forest (RF) regression models were fitted, and a Leave-One-Site-Out (LOSOCV) cross-validation method was used to evaluate model performance during the reference period. Yield prediction models were evaluated using the mean absolute error (MAE). The models achieved low MAE values for wheat (33.95 kg da⁻¹ in EKB and 75.04 kg da⁻¹ in BB), whereas the MAE values for maize and alfalfa were considerably higher, ranging from 658 to 986 kg da⁻¹. Projections for future periods indicate declines in relative yield across both basins. For 2070–2079, wheat and maize yields are projected to decrease by 10–20%, accompanied by wide uncertainty intervals. Both basins are expected to experience a substantial increase in heat stress days (>35 °C), a reduction in frost days, and an overall acceleration of plant phenology. Results provided insights to inform region-specific, evidence-based adaptation options, such as selecting heat-tolerant varieties, optimizing planting calendars, and integrating precision agriculture practices to improve resource efficiency under changing climatic conditions. Overall, this study establishes a scientific basis for enhancing the resilience of agricultural systems to climate change in two lake basins within the Mediterranean biogeography.

The ramifications of climate change, which are projected to lead to increased drought, desertification, and water scarcity, are expected to have a significant impact on the agricultural sector of Türkiye, particularly in the Mediterranean coastal regions. This study presents an extensive evaluation of potential agricultural drought conditions in southwestern Türkiye, using a high-resolution, convection-permitting (0.025°) modeling approach. We employ a single, physically consistent model chain, dynamically downscaling the CMIP6 MPI-ESM-HR Earth System Model with the COSMO-CLM regional climate model at a convection-permitting (CP) resolution (0.025°) under IPCC Shared Socioeconomic Pathways SSP3-7.0, reflecting a high-emission scenario with regional socioeconomic challenges. Southwestern Türkiye, situated at the intersection of the Mediterranean and continental climates, hosts rare climatic and ecological conditions that sustain a highly productive and diverse agricultural system. This region forms the backbone of Türkiye’s agricultural economy but is increasingly vulnerable to climate variability and fluctuations that threaten its agricultural stability and resilience. Our study employs a novel approach that utilizes multivariate assessment of agricultural drought in the Mediterranean Region by integrating precipitation, soil moisture, and temperature variables from 2.5 km resolution climate simulations. Agricultural drought conditions were evaluated using the Standardized Precipitation Index (SPI), the Standardized Soil Moisture Index (SSI), and the Standardized Temperature Index (STI), derived by normalizing respective climate variables from climate simulations spanning from 1995 to 2014 for the historical period, from 2040 to 2049 and from 2070 to 2079 for future projections. CP climate simulations (CPCSs) exhibit a modest warm and dry bias during all seasons but slightly wetter conditions during summer when compared with station observations. Correlations between indices indicate that soil moisture variations in the future will become more sensitive to changes in temperature rather than precipitation. Results from this specific model chain reveal that the probability of compound events where precipitation and soil moisture deficits coincide with anomalously high temperatures will rise for all threshold levels under the SSP3-7.0 scenario towards the end of the century. For the most severe conditions (|Z| > 1.2), the compound likelihood increases to about 3%, highlighting the enhanced occurrence of rare events in a changing climate. These findings, conditional on the model and scenario used, provide a high-resolution, physically grounded perspective on the potential intensification of agricultural drought regimes.

Humid heat extremes are expected to intensify in conjunction with rising global temperatures, leading to prolonged and elevated exposure to hazardous levels of heat stress (HS). Even moderate levels of HS have been observed to trigger a range of health and socioeconomic impacts, underscoring the need for regional climate information. Therefore, we examine the present and future conditions of two different HS indices, wet bulb temperature (WBT) and environmental stress index (ESI), for the first time at such high resolution over northwestern Türkiye using a non-hydrostatic regional climate model, COSMO-CLM. The study is also pioneering in its effort to assess population exposure to these indices at the provincial scale. The findings indicate that the most substantial shifts in the probability density function of both HS indices from the middle of the 21^st century onward are expected to occur in June relative to the reference period. However, WBT intensity with ~ 4 °C increase is projected to undergo the most significant change in September, while ESI has the largest increase in July. According to ESI projections, almost all areas (> 95%) in cities such as Istanbul, Tekirdağ, Edirne and Çanakkale will experience severe HS at least once in July after 2071, while based on WBT projections, the same cities will face similar conditions after 2091. The 2091–2100 period will be subject to the longest exposure duration, the greatest areal expansion, and the highest population exposure levels. Conversely, Kütahya, Bilecik, and Kırklareli are expected to have the least substantial increase in exposure among 12 cities.

This study presents a comprehensive spatiotemporal assessment of climatic and bioclimatic conditions across Türkiye for both a historical reference period (1995–2014) and future projections (2020–2099) under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP3-7.0) scenarios using the regional climate model (RCM) COSMO-CLM to downscale large-scale signals to a regional scale at high resolution (0.11). A comparison of the model with ERA5-Land reanalysis data revealed annual biases of +1.41 °C (warm) and −0.28 mm/day (dry), emphasizing the importance of bias correction in regional climate assessments. Bias-corrected future projections indicate a marked warming trend and significant decline in precipitation, especially after the 2060s, with pronounced spatial variability across regions. The most intense warming period of the century is the 2060–2079 period, with an anticipated increase of 0.109 °C/year under the SSP3-7.0 scenario, while, under the SSP2-4.5, it is the 2040–2059 period with an increase of 0.068 °C/year. Bioclimatic variables further illustrate shifts in temperature extremes, seasonal variability, and precipitation patterns. Coastal regions are expected to experience a delay in the onset of wet seasons of 1–2 months, while high-altitude zones show earlier shifts of up to 4 months. Four distinct clusters were identified by using k-means clustering method, each with unique temporal and spatial evolution under both SSP scenarios. Clusters 1 and 2, which predominantly represent continental and interior regions, exhibit a strong association with earlier precipitation onset. Notably, arid and semi-arid conditions expand northward, replacing temperate zones in Central Anatolia. Overall, findings suggest that Türkiye is undergoing a substantial climatic transition toward hotter and drier conditions, regardless of the emission scenario. This study has critical implications for ecological resilience, agricultural sustainability, and water resource management, and offers valuable information for targeted climate adaptation strategies and land-use planning in vulnerable regions of Türkiye.

Assessing climate risk due to climate change for the present and future periods has been the focus of both academic and applied research in recent years, reflecting its critical importance. In this study, we evaluated climate risks for the Marmara Region in northwestern Türkiye by integrating high-resolution climate projections with socio-economic data, aiming to inform and support regional climate policies.To achieve this, we generated climate projections at a 0.025° x 0.025° resolution using the convection-permitting COSMO-CLM model, driven by EC-Earth3-Veg from CMIP6. These projections cover both the reference period (1995–2014) and a future period (2050–2059) under the SSP3-7.0 scenario) for a broader western part of Türkiye. The Marmara Region was selected as a focal area due to its vital economic significance, its diverse and densely populated urban centers, and its extensive agricultural areas. This approach allows for a comprehensive assessment of climate impacts on a region with critical socio-economic importance, providing actionable guidance to inform policy development and adaptation strategies.We conducted a comprehensive climate risk assessment by integrating hazard data with components of sensitivity, vulnerability, and adaptive capacity components, which were derived from reliable socio-economic datasets provided by institutions such as the Turkish Statistical Institute and the Turkish State Meteorological Service. For the weighting phase, we employed multiple methodologies, including the Analytic Hierarchy Process (AHP), Principal Component Analysis (PCA), and variance-based distribution methods, to investigate their respective contributions to the final risk evaluation.Preliminary findings reveal city-level climate risks for both the present and future periods, offering critical insights for key vulnerabilities and areas of concern. These results provide essential guidance for regional policymakers, enabling the identification of specific risk hotspots and developing targeted strategies that address the region-specific challenges. These results serve as a foundation for developing targeted strategies to mitigate climate risks, strengthening resilience, and enhance adaptation capacity in the Marmara Region.

This study investigates climate change patterns in the western region of Türkiye using high-resolution bioclimatic variables to capture the detailed spatial and temporal changes. It is funded by the project titled Predicting the Distribution of Future Basic Forest Tree Species Using Different Climate Projections and Developing Adaptation Strategies for Turkey' which is implemented under the “Climate Change Adaptation Grant Program (CCAGP)”.The western part of Türkiye is characterized by vast agricultural areas and majority of the nation’s forest stock both of which play critical roles in the country's economy and ecology. The region's agricultural lands serve as one of the primary suppliers of food and resources to urban centers, ensuring food security and economic stability. Additionally, the forests in this area are ecological hotspots, hosting approximately 300 endemic plant species and contributing to biodiversity conservation. The importance of agriculture and forestry in the region emphasize the need for a thorough understanding of climate impacts, facilitating the development of sustainable agricultural and forestry management practices and policies to protect these vital resources.To explore these dynamics in depth, we conducted the regional climate model simulations using COSMO-CLM at a convective permitting resolution 2.5 km x 2.5 km, driven by the EC-EARTH3-Veg from the CMIP6. These simulations were carried out for both historical (1995-2014) and future periods, including the mid-century (2050-2059) and the end of the century (2090-2099) under SSP3-7.0 scenario. To assess the reliability of the regional climate model, we compared its output with observational data from the region for the reference period. Key variables such as temperature and precipitation were analyzed, and their values were contrasted against the on-site measurements. Subsequently, we calculated bioclimatic variables for the reference period, as well as for the mid-century and end-of-century projections, to assess how these climatic changes might affect the region over time.This high-resolution analysis enables a detailed assessment of 19 bioclimatic variables and their trends throughout the century how the agricultural and forest areas respond to climate change. Acquiring knowledge of the projected increase in temperature and the decline in precipitation by the end of the century is crucial for understanding the impacts on these vital areas, which are essential for ecosystem health and biodiversity. Under the SSP3-7.0 scenario, our findings indicate that annual mean temperatures increase around 4.5°C when comparing the period of 1995-2014 with that of 2090-2099. Also, we found that annual precipitation amount over the region decreases around 170 mm/year, which indicates a nearly 25% reduction in the freshwater availability by the end of the century. Especially, the precipitation of the wettest month shows a comparable decrease across these periods. Understanding these shifting in bioclimatic variables is crucial to preserve the agricultural and forest areas with their biodiversity.

It is becoming more and more crucial to comprehend and manage the effects of extreme temperatures in order to preserve agricultural productivity and food security as climate change continues to intensify weather variability. Due to the increasing demand for olive products such as olive oil and olives in the world in recent years, olive cultivation has started to be cultivated economically in countries with a Mediterranean climate. This study investigates the future changes in growing degree days (GDD) for olive in southwestern Türkiye during the 21st century, using convection-permitting simulations under the SSP3-7.0 scenario. Future climate projections based on the SSP3-7.0 scenario suggest pronounced warming trend, particularly in the summer season. In comparison to the reference period of 1995-2014, temperatures in the 2040-49 period are expected to rise by 2.5°C, and by 3.5°C in the 2070-79 period. The second largest warming trends occur in spring and autumn, approaching those of summer in the second projection decade. After the significant decrease in the winter season, the autumn season is expected to experience the second largest reduction in precipitation, with a similar drying trend extending into the spring months in 2070-79, exacerbating the already reduced winter precipitation. Considering the ten-year average of olive production in Türkiye, our study area contains most of the cities with the highest production. Therefore, GDD is calculated for olives over the period between 1 April and 15 October, using a base temperature of 12oC. The results show a clear increase in GDD for olives in the future climate projections, especially in the second period. This increase indicates that olives will grow faster and mature earlier due to the accumulation of more heat. If the olives ripen too early, this can affect the yield and quality of the oil. Nevertheless, the relative effects of an increase in GDD across phenological stages may expose the plant to the risk of damage due to higher frequency of extreme weather events (e.g. heatwaves and late spring frosts). Insufficient water can lead to slower growth and smaller fruit sizes, and also lower oil content in olives that reduces the production of high-quality extra virgin olive oil. Olive growers in southwest Türkiye can mitigate some of the negative consequences of climate change while preserving their productivity and quality by focusing on climate-resilient types, water conservation, and sustainable farming methods.This work is funded by the project titled 'ACLIFS - Assessment of Climate Change Impacts on Food Safety and Enhancing the Resilience of Rural Communities' which is implemented under the “Climate Change Adaptation Grant Program (CCAGP)”.Key words: Growing degree days, convection-permitting model, COSMO-CLM, future projections, SSP3-7.

The frequency and intensity of heat stress are expected to escalate markedly in the near future under various global climate change scenarios, with densely populated cities becoming hotspots because of the urban heat island effect. Therefore, heat stress analysis for highly populated cities is crucial since changes in this stress exacerbate vulnerability, increase health-related risks and impose constraints on outdoor activity. This study investigates changes in heat stress during 21st century in terms of frequency, intensity and durations while quantifying population exposure to heat stress covering Northwestern Türkiye, with particular attention to Istanbul, the most populous city in Türkiye with nearly sixteen million population.In this study, we use climate simulations from convection-permitting model COSMO-CLM under SSP3-7.0 emission scenario to investigate future changes in heat stress. The analysis focuses on calculating Wet Bulb Temperature (WBT) values and assessing consecutive hours when Wet Bulb Temperature (WBT) is above specific thresholds, which are critical indicators of heat stress severity. In addition, we conduct comprehensive heat stress evaluation by computing Environmental Stress Index (ESI) values, an effective alternative to WBGT, to assess outdoor activity limitations. These analyses are performed for the reference period of 1985-2015 and extended to future periods of 2030-2039, 2050-2059, 2070-2079 and 2090-2099, providing a detailed temporal perspective on the progression of heat stress and its implications under changing climatic conditions.WBT uses air temperature and relative humidity as its primary parameters while ESI incorporates radiation alongside air temperature and relative humidity. Thus, this study also comprehensively analyzes the role of radiation in amplifying heat stress. Our results reveal a remarkable seasonal shift in heat stress pattern within the study area with Istanbul standing out as a hotspot where heat stress indices are notably higher than those of other cities in the covered region, highlighting the effect of urbanization in heat stress dynamics.Notably, ESI values in the southern parts of Istanbul, where urbanization is more concentrated, exceed critical thresholds that makes any physical activity to be hazardous especially by the end of this century. Moreover, projections demonstrate that in the late 21st century, majority of Istanbul’s population will be exposed to heat stress levels exceeding the risky thresholds. Furthermore, this study explores the extent of population exposure to heat stress, the duration of consecutive hours exceeding critical thresholds, and the percentage of areas where indices exceed their limits.Key words: Climate modelling, heat stress, heat extremes, population exposure, COSMO-CLM

Global climate projections show that humid heat extremes will expand toward the higher latitudes, making the midlatitudes hotspots for these extremes. Therefore, a thorough explanation of their regional characteristics becomes crucial, given that the changes in these extremes can potentially render a large proportion of the global population at risk. Here, we perform the first analysis of historical and projected changes in the intensity and frequency of humid heat extremes and quantify the population exposure to these extremes in Turkey, using long‐term simulations from the non‐hydrostatic mesoscale model of Consortium for Small‐scale Modeling (COSMO‐CLM) under the RCP8.5 emission scenario. We portray not only the nationwide changes in the humid heat extremes and population exposure but also their regional aspects by exploiting the K‐means clustering algorithm. Our results suggest significant future increases in the intensity and frequency of these extremes over a wide geographical area, which includes the surroundings of Adana, Antalya, Izmir, Sakarya, Ordu and Diyarbakir, most of which are coastal locations. Over most of these regions, severe humid heat stress is expected to last nearly a month every year, with almost 56% of the land area is projected to experience local historical upper tail heat stress conditions for at least an additional 10 consecutive hours. Further, we explicate a significant rise in the number of people exposed to severe humid heat stress, concentrated along most coastal regions, by as much as 1.6 million person‐days. More than 20% of Turkey's population may confront severe humid heat stress for at least 1 h, with that percentage falling to 4.15% for at least five consecutive hours, which indicates that people will not only endure more intense humid heat stress but also be exposed to these conditions consecutively over a period of many hours.