Projected Summer Tourism Potential of the Black Sea Region

Abstract

The impacts of climate change and the extent of their consequences exhibit regional variability. The negative effects of climate change on the tourism industry require a comprehensive examination of the vulnerabilities of tourism–dependent countries. Considering that the tourism sector is an important source of income for these countries, it is imperative to evaluate the potential consequences of climate change. Its effects may lead to changes in the location and popularity of tourist destinations and the timing of the tourism season. If popular coastal destinations cannot respond effectively to the impacts of climate change, alternative tourism destinations need to be explored to reduce financial losses. This study aims to assess the potential of the Black Sea coasts as an alternative tourism destination. The evaluation was conducted using the Holiday Climate Index (HCI), a prominent indicator for determining human comfort. The research showed that Türkiye’s Black Sea coast may have the necessary comfort level for beach tourism in the summer season and may be attractive for more tourists considering the positive relationship between arrival and overnight stay and tourist comfort.

1. Introduction

The tourism sector is highly sensitive to environmental factors and climate change can seriously affect the natural balance and ecosystems in destinations. As an effective strategy to combat climate change, tourism should adopt the principle of environmental sustainability. Adaptation to climate change enables destinations to develop emergency plans to ensure tourist safety and comfort and to be prepared for risks arising from climate change [1]. Adaptation to sustainable tourism is of critical importance to ensure that tourist destinations, businesses, and communities act resiliently and flexibly against the effects of climate change. Businesses need to evaluate the risks related to climate change and develop strategies against these risks. Sustainable tourism practices can minimize the negative effects of climate change by both protecting natural resources and providing long–term resilience to tourist destinations [2]. In this way, the tourism sector can secure both the environment and the tourism experiences of future generations.

In sustainable tourism, natural resources are used effectively, and the cultural characteristics of the tourism region are preserved. Sustainable tourism within the context of climate change minimizes the comprehensive environmental impacts resulting from tourism activities and the main issue here is not to disrupt the balance in natural ecosystems. However, in addition to protecting natural resources and cultural items, and minimizing the environmental impact resulting from activities, another issue in terms of sustainable tourism is the sustainability of tourists’ holiday comfort [3,4].

Adverse climatic conditions that may disrupt tourist comfort in traditional and popular tourist locations have been affecting tourists’ preferences, and therefore the demand for some locations may decrease [5]. That reveals the need for new and more sustainable destinations in the tourism industry within the scope of climatic conditions that are predicted to change in the near, medium, and long-term future. Compared to popular ones, the popularity of locations that have not received much attention before may increase in terms of holiday comfort due to climate change [4]. The tourism sector must adopt the concept of sustainability with all its components. Otherwise, tourism might be one of the sectors most affected in the medium and long term because of rapid population growth, depleted natural resources, and demand change [6,7]. A tourism destination that does not embrace the concept of sustainability totally may lose its natural attractions and, in such a case, tourists might choose alternative destinations.

The selection of a vacation destination is substantially influenced by climate and climate change due to the sensitivity of tourists to these factors. The influence of climate on the seasonality of tourism demand is a significant factor in the global tourism industry. It plays a crucial role in determining the suitability of a destination for various touristic activities [8]. Whether it is winter or summer, tourist enterprises must make a profit in a short time while concentrating on activities with a limited activity period. Hence, within tourism destinations, the climate holds significant economic importance, as it serves as a crucial determinant of the region’s appeal about its suitability for tourism [9,10]. It is imperative to analyze the existing and potential climatic circumstances pertaining to tourism to facilitate future planning and regional investments.

Studies indicate that the preferences of tourists for travel destinations are affected by the specific type of tourism, such as coastal, urban, or mountain tourism [11,12,13,14]. In addition to socio-demographic factors, such as age, family status, and gender [14,15], the climatic characteristics of the tourist’s country of origin also play a role [11,16,17]. Coastal regions frequently attract a significant number of tourists during the summer season due to their appeal for beach–related activities.

Coastal tourism represents the most significant market segment within the global tourism industry, primarily relying on the thermal climate characteristics of a destination [14]. The impact of climate change on coastal tourism destinations may alter the distribution of climate conditions, leading to changes in tourism seasonality, demand, and travel patterns [18]. Climate change alters the climatic attributes, including variables such as sunshine duration, precipitation, humidity, wind speed, and air temperature [19]. The Mediterranean Basin, renowned for its appeal as a vacation spot, is recognized as a region particularly vulnerable to the impacts of climate change [20,21,22,23,24]. The potential future vulnerability of the Mediterranean Basin’s current favorable holiday conditions has been highlighted by several studies [18,25,26]. If current climate predictions turn out to be accurate, popular tourist destinations in the Mediterranean region may experience a decline in their appeal during the summer months [18], which coincide with the peak holiday season. It is primarily attributed to the intensification of extremely high temperatures. Consequently, the optimal duration of vacation periods is expected to diminish.

The determination of climatic comfort, a crucial factor in the planning of health and tourism, is subject to considerable variation based on individuals’ metabolic rates, clothing preferences, levels of physical activity, age, gender, body weight, emotional well-being, cultural backgrounds, previous climate experiences, and the climatic attributes of their origin regions [27]. The presence of substantial evidence highlighting the inherent significance of climate in the decision-making processes of tourists suggests that expected changes in climatic conditions will likely have notable effects on the demand for tourism [28,29,30]. Tourism activities that benefit from the natural attractions of a destination (e.g., coastal tourism) typically occur in open-air settings and are vulnerable to adverse weather conditions, such as heavy precipitation and strong winds. The air parameters that impact the comfort and safety of tourists include air temperature, humidity, radiation intensity, wind speed and direction, cloud cover, sunshine duration, and precipitation [10,12,31].

Studies in the existing body of literature have examined the optimal and undesirable parameters for various weather conditions, including temperature, precipitation, solar time, cloud cover, and wind speed. Several studies have indicated that temperatures ranging from 25 to 32 °C are considered optimal for tourists, while temperatures below 22 °C and above 34–35 °C are deemed unsuitable [12,17,32,33,34]. Furthermore, the studies emphasized the significance of ample sunlight and minimal cloud cover as crucial factors [31]. For example, wind speeds below 8 m/s are considered optimal in Spain [33,34,35]. Conversely, wind speeds exceeding 12 m/s are deemed unsatisfactory. Additionally, the absence of rainfall is identified as the preferred condition. The observation regarding precipitation holds true for Europe as a whole; however, wind speeds below 2.5 m/s are considered optimal for Europe [12], Greece, and the Caribbean [17,36]. Among these factors, precipitation and wind play a significant role in determining the comfort levels of individuals residing in the Black Sea Region. This particular region is renowned for its ample rainfall and strong winds, making it the focal point of investigation in this article.

Several indices have been devised to acquire comprehensive data regarding the climate desirability of popular tourist destinations that offer favorable summer conditions concerning human comfort. The Tourism Climate Index (TCI) [37] is a metric that assesses the degree of human comfort experienced during tourism-related activities. Nevertheless, several alternative indices have been developed through adjustments to the TCI, arguing it relies on subjective opinions. The Beach Climate Index (BCI) was created based on surveys conducted with over 1600 tourists who specifically sought sand, sea, and sun experiences [38]. Designed exclusively for sand-sea-sun usage, this index is not applicable to alternative daily activities. Furthermore, limiting the surveys only to the Northern European coasts may not be appropriate for tourists visiting other regions, as their preferences and profiles may differ. The Climate Index for Tourism (CIT) is an index that was developed through the process of surveying tourists [39]. Nevertheless, due to the exclusive inclusion of university students as participants in the study, the limited age range of the research sample resulted in a deficiency in cross-cultural understanding [39]. The Modified Climate Index for Tourism (MCIT) [10] differs from other indices as it utilizes hourly data instead of means. This index evaluates the appropriateness of daily weather conditions for engaging in tourist activities. The Holiday Climate Index (HCI) [40,41,42] is an index that differs from subjective opinions, as it relies on existing literature regarding tourists’ climate preferences to establish rating scales and weights for sub-indices.

One study utilizes the TCI and incorporates the International Panel on Climate Change’s (IPCC) earlier scenarios (A1B and A1FI) [30]. The findings of this study suggest that northern Mediterranean countries, which are presently popular destinations for traditional “sun and sand” tourists, may experience uncomfortably high temperatures during the summer season. However, the study also reveals that northern European countries demonstrate the potential for significant improvements in their summer climate conditions. In a different study employing the BCI [16], it has been found that the Mediterranean coast harbors the most favorable summer destinations. Furthermore, the research suggests that, over the century, the regions offering optimal comfort conditions for vacationing may extend northward. However, it is worth noting that no investigation has been conducted regarding the viability of the region as an alternative destination. Several studies have suggested that, due to climate change, the geographical location of the zone characterized by pleasant summer conditions will likely shift from the Mediterranean region towards higher latitudes and altitudes, potentially reaching the northern regions or even the poles [18,43,44,45,46]. The aforementioned studies, which suggest a potential shift in popular tourism destinations, have prompted us to investigate whether the Black Sea coasts can be an alternative destination for tourists if the Mediterranean coastal region of Türkiye, which currently attracts a significant number of tourists, may experience a decline in popularity or become entirely unappealing due to the effects of climate change.

According to the United Nations World Tourism Organization’s (UNWTO) report in 2021, Türkiye is included in the top 10 tourism destinations, which receive approximately 40% of the total global tourist arrivals [47]. The tourism industry holds significant importance for Türkiye’s gross domestic product (GDP), as it has consistently ranked among the most frequently visited countries from 1995 to 2019. Given the substantial economic significance of the tourism industry in Türkiye, potential consequences of adverse conditions on the tourism infrastructure can result in considerable reductions in income and employment opportunities. However, there is a limited body of research examining the impact of climate change on tourism destinations in Türkiye using indices [24,48].

There is a requirement for the development of one or multiple indices that can impartially evaluate the potential shifts in tourism destinations due to climate change, encompassing the climatic conditions of these destinations, preferred seasonal periods, and employing standardized data. These indices should integrate all aspects of the climate simultaneously. In this study, while evaluating climatic comfort, indices were used to evaluate certain threshold values according to their suitability in terms of human comfort.

2. Materials and Methods

2.1. Data and Domain

This study aims to project the potential of the Black Sea coastal regions in Türkiye in the forthcoming years. The study encompasses the provinces in the region with a coastline along the Black Sea, commencing from Kırklareli and extending to Artvin (Figure 1a).

The Black Sea and its surrounding regions exhibit a climate type characterized by mid-latitude and subtropical characteristics, featuring distinct summer and winter seasons [49]. This classification is based on the long-term monthly mean temperature values [50]. Figure 1b illustrates that the whole Black Sea coastline falls within the C class as per the Köppen-Geiger climate classification. This classification system, renowned for its global applicability, encompasses five fundamental climate types denoted by the letters A, B, C, D, and E. The classification of the C climate indicates the presence of a mild mid-latitude climate during the winter season. This particular climatic region experiences a mean temperature range of 18 °C to 0 °C during the coldest month of winter, while the mean temperature during the hottest month exceeds 10 °C [51,52]. The Eastern Black Sea region is a prominent geographical area in Türkiye characterized by the highest precipitation levels. This region experiences a consistent absence of drought and receives precipitation throughout all seasons. Notably, around 20% of the total annual precipitation occurs during the summer months. Based on the Köppen-Geiger climate classification, it has been established that the Cfa climate type is prevalent in the coastal regions of all provinces within the Eastern Black Sea region. The Cfb climate type is observed in Kastamonu, a province located along the Central and Western Black Sea coast [53]. This region is known for the common occurrence of the Cfa climate type. The Csa climate type, characterized by an arid Mediterranean climate with warm winters, very hot summers, and a mean temperature exceeding 22 ℃ during the hottest month, is observed in certain areas of Samsun and along the Black Sea coast of the Marmara Region [53].

This study employed the Max Planck Institute Earth System Model Mixed Resolution (MPI–ESM–MR) [54] and the Met Office Hadley Center Earth System Model (HadGEM2–ES) [55,56] as Global Circulation Models (GCMs). Comparative results were obtained with these two models. In order to measure the suitability of the regions for tourism in detail, GCM data was dynamically downscaled to 10 km grid resolution using RegCM4.4 [57] developed by Abdus Salam International Center for Theoretical Physics (ICTP). This data is part of the Coordinated Regional Climate Downscaling Experiment (CORDEX) and covers the Middle East North Africa (MENA) region [58,59]. Previous studies have shown that MPI–ESM–MR and HadGEM2–ES give better results in the MENA–CORDEX region than other GCMs [24,60]. The time resolution of the data used is 6 h, which strengthens the analysis. RCP8.5 [61] was examined for the years 2026–2050 and 1976–2000 was taken as the reference period. Climate normals are preferred in 30-year periods such as 1961–1990, 1971–2000, 1981–2010, and currently 1991–2020. However, as is known, in regional climate projection studies based on CMIP5, the 1971–2000 30-year period is generally used as the reference period and the 1986–2005 20-year period is used in some global projection studies. The underlying reason for this is that the reference period or historical period data in terms of climate models are limited to 2005. In this study, since it is aimed to compare the last quarter of the last century and one quarter (near future period) of this century after 2025, 25-year periods were preferred. Another advantage of choosing this reference period is to be able to more clearly show the change in the 21st century, when temperature increases began to become more evident, compared to the 20th century.

2.2. Method

Four sub-indexes are used while calculating HCI: Beach: thermal comfort (TC), aesthetics (A), precipitation (P), and wind speed (W) [42]. All values are calculated daily to increase time resolution. While calculating TC, daily mean temperature (T) and relative humidity (RH) values are calculated by means of Humidex, which is standard in Canada [62], given in Equation (1). The reason why Humidex is used instead of effective temperature is that it considers the effect of RH on the apparent temperature more clearly [24]. The aesthetics sub-index is evaluated on the cloud cover percentage. The precipitation sub-index is determined by the daily precipitation in mm. Finally, the wind considers the daily mean wind speed in km/h. The ratings assigned to the ranges of all these sub-indices are given in

Table 1. The ratings of thermal comfort (based on humidex), aesthetic (based on cloud cover), precipitation, wind, and HCI: Beach scores *.

Thermal Comfort (TC)		Aesthetic (A)		Precipitation		Wind		HCI: Beach Score
Humidex		Cloud Cover
	Rate	%	Rate	mm	Rate	km/h	Rate		Descriptive Rating
(−∞, 10) [10, 15) [15, 17) [17, 18) [18, 19) [19, 20) [20, 21) [21, 22) [22, 23) [23, 26) [26, 28) [28, 31) [31, 33) [33, 34) [34, 35) [35, 36) [36, 37) [37, 38) [38, 39) [39, ∞)	−10 −5 0 1 2 3 4 5 6 7 9 10 9 8 7 6 5 4 2 0	[0, 1) [1, 15) [15, 26) [26, 36) [36, 46) [46, 56) [56, 66) [66, 76) [76, 86) [86, 96) [96, 100]	8 9 10 9 8 7 6 5 4 3 2	[0, 0.01) [0.01, 3) [3, 6) [6, 9) [9, 12) [12, 25) [25, ∞)	10 9 8 6 4 0 −1	[0, 0.6) [0.6, 10) [10, 20) [20, 30) [30, 40) [40, 50) [50, 70) [70, ∞)	8 10 9 8 6 3 0 −10	[0, 20) [20, 40) [40, 50) [50, 60) [60, 70) [70, 80) [80, 90) [90, 100)	Dangerous Unacceptable Marginal Acceptable Good Very Good Excellent Ideal

* Adapted from [24,40,41,42].

and

Table 2. The ratings of thermal comfort (based on humidex), aesthetic (based on cloud cover), precipitation, wind, and HCI: Urban scores *.

Thermal Comfort (TC)		Aesthetic (A)		Precipitation		Wind		HCI: Urban Score
Humidex		Cloud Cover
	Rate	%	Rate	mm	Rate	km/h	Rate		Descriptive Rating
(−∞, −6) [−6, 0) [0, 7) [7, 11) [11, 15) [15, 18) [18, 20) [20, 23) [23, 26) [26, 27) [27, 29) [29, 31) [31, 33) [33, 35) [35, 37) [37, 39) [39, ∞)	1 2 3 4 5 6 7 9 10 9 8 7 6 5 4 2 0	[0, 1) [1, 11) [11, 21) [21, 31) [31, 41) [41, 51) [51, 61) [61, 71) [71, 81) [81, 91) [91, 100) 100	8 9 10 9 8 7 6 5 4 3 2 1	[0, 0.01) [0.01, 3) [3, 6) [6, 9) [9, 12) [12, 25) [25, ∞)	10 9 8 5 2 0 −1	[0, 0.01) [0.01, 10) [10, 20) [20, 30) [30, 40) [40, 50) [50, 70) [70, ∞)	8 10 9 8 6 3 0 −10	[0, 20) [20, 40) [40, 50) [50, 60) [60, 70) [70, 80) [80, 90) [90, 100)	Dangerous Unacceptable Marginal Acceptable Good Very Good Excellent Ideal

* Adapted from [24,40,41,42].

. The rating of each sub-index is used to calculate the HCI: Beach score with the help of the weighting formula given in Equation (2). The descriptive rating of the obtained HCI: Beach score is given in the same table. Although it is possible to calculate negative HCI: Beach scores in extreme cases as a result of negative values in the sub-indexes, if negative values are found, those scores will be considered equal to 0.

$$\mathrm{Humidex}=T+\frac{5}{9}\times \left[\left(6.112\times {10}^{\frac{7.5\times T}{273.7+T}}\times \frac{RH}{100}\right)-10\right]$$

(1)

HCI: Beach = 2(TC) + 4(A) + (3(P) + W)

(2)

HCI: Urban = 4(TC) + 2(A) + (3(P) + W)

(3)

The indices give the relationship between tourism and climate to evaluate positive and negative climatic conditions according to the needs of visitors. Thermal comfort ratings in Table 1 and Table 2 state, for example, that wind blowing at a speed of more than 70 km per hour is at a level that greatly reduces comfort and therefore a −10 rating is given. However, its speed of up to 10 km per hour is ideal for tourist comfort and a rating of 8–10 is given. Similarly, climate variables such as humidity, precipitation, and cloudiness are also taken into account in the calculation as they can affect the comfort level. The different calculations in the HCI: Urban and HCI: Beach indices are due to the fact that the preferences of tourists appealing to the two segments may differ. Compared to the other indices in the literature, HCI is a more advanced index. For instance, in the first designed TCI, the ratings were highly subjective. However, in later developed indices, the ratings were decided based on many studies in the literature examining tourists’ preferences.

3. Results

In this part of the study, which was conducted using RegCM4.4 driven with the boundary conditions of the HadGEM2–ES (hereinafter: RegCM–HG) and MPI–ESM–MR (hereinafter: RegCM–MPI) models under the RCP8.5 scenario, with reference to the data on the regions located on the coastline of the Black Sea between the years 1976–2000 and 2026–2050, HCI: Beach and HCI: Urban index calculations are presented.

3.1. HCI: Beach Ratings in Black Sea Coasts

All the Black Sea coasts examined in the study are located in the middle latitude and have distinct summer and winter seasons [50]. In the Köppen-Geiger climate classification, all Black Sea coasts covered by the study have a C climate type [51]. Although the winter reference period results are very close to each other in the two models, there are small differences for Sakarya and Kocaeli. The index results in the Black Sea coastal region are between 40 and 50 which is marginal. This situation does not change much in either model in the future scenarios of 2026–2050; however, the HCI: Beach scores will improve on a small scale in the coastal areas in the RegCM–HG model and the differences will be quite small in the RegCM–MPI model compared to the reference period (Figure 2). The index means of the reference period of March, April, and May in the spring period (Figure 3) give good results in all regions of Kırklareli, Istanbul, and Kocaeli, that is, between 60 and 70. On the other hand, the coastal parts of Sakarya, Düzce, and Bartın, and a region with a size of more than half of the surface area of these provinces are in this range. In the central part of the Black Sea region, there are coastal regions that are in the good range of index results in other provinces except Kastamonu. In both models, index results for the eastern part of the Black Sea region in the reference period are in the acceptable range of 50–60. Considering the 2026–2050 projections, both RegCM–HG and RegCM–MPI models have a good range of indices for the coastal part of each province of the Black Sea region within the scope of the study, except Artvin. In the RegCM–HG model, the area size of the coastal part of Artvin, which is in the good range in the index scores, is larger than the RegCM–MPI. Another point where the two models differ significantly is the size of the region, which is in the good range in Kastamonu’s index scores.

In the summer season, the index results of all Black Sea coasts in the reference period are in the excellent range (Figure 4). The index values of a small part of Artvin are in the good range in terms of surface area, as in other seasons. According to the projections for the future, the entire coastline, which has values in the very good range, may expand for both models in 2026–2050. There are no obvious differences between the two models for the coastline. In the future period studied in both models, the HCI: Beach results in some regions in the coastal part of Sakarya, Ordu, and Samsun may be in the range of 90–100, indicating ideal comfort conditions. However, the HCI: Beach score is expected to be between 90 and 100 according to the RegCM–HG model estimates for Şile on the Asian continent of Istanbul, Kilyos on the European continent, and some coastal regions of the Rize and Trabzon. These regions are in the 80–90 range for the RegCM–MPI model. The results show that the Black Sea coasts in Türkiye may have the level of comfort required for beach tourism in the summer season, and even some regions in Istanbul, Sakarya, Ordu, Samsun, Trabzon, and Rize may be in ideal conditions. According to the RegCM–HG results of the reference period between 1976–2000, it is seen that the entire coastal part of the Kırklareli, Istanbul, Kocaeli, and Sakarya in Türkiye have an HCI: Beach index score between 70 and 80, that is, very good conditions. Except for Artvin, Kastamonu, and Bartın, other provinces have small areas where the HCI: Beach score is very good. However, results are mostly between 60 and 70 in the western, central, and eastern Black Sea region, and mostly between 50 and 60 in Rize. It is noteworthy that the HCI scores of the regions are very close to each other in the RegCM–MPI model for the same reference period. According to the 2026–2050 projections, in the RegCM–HG model, it is seen that the area of the coasts where scores between 70 and 80 are seen in the autumn season on all Black Sea coasts expands. As a difference in the RegCM–MPI model, it can be said that there may not be very good holiday conditions for beach tourism in Artvin (Figure 5).

3.2. HCI: Urban Ratings in Black Sea Coasts

It is noteworthy that the winter coastline HCI: Urban results are higher than the HCI: Beach results. It is seen that especially the HCI: Urban scores of Istanbul, Kocaeli, and Düzce indicate much better conditions when compared with HCI: Beach scores for the winter months in both reference and future scenarios. However, there is not much difference in the HCI: Urban results for the future period and the reference period (Figure 6). Considering the mean index results for the spring season (Figure 7), it is seen that most areas of the region have comfort conditions in the 60–70 range for the reference period. There are slight differences between the two models in the size of the regions where results from 70 to 80 are seen, which are considered very good. For example, in the RegCM–HG model, very good comfort conditions are seen in Kastamonu and Artvin, albeit in very small areas, but, in RegCM–MPI, index results are not seen in this range in these provinces.

The season with the highest HCI: Urban results based on seasonal means is summer. In the summer season, it is seen that the reference years are in the 80–90 range, where the two models show excellent results for the entire Black Sea coastline. However, only a small part of the coastline of Artvin is in this range. In the RegCM–HG model, the coastline with excellent HCI: Urban conditions for the reference period is spatially larger than in RegCM–MPI. According to the projections for the years 2026–2050, in the RegCM–HG model, it is seen that the regions where the HCI: Urban results may decrease to the range of 70–80 may increase in all provinces except Kastamonu in the coastal region. However, in the RegCM–MPI model, there is no significant change in the coastline in the index results for the years 2026–2050 (Figure 8). In the reference period for the autumn season, it is seen that the range of results is very good, especially in the coastal regions. In both models, it is seen that the regions with 70–80 scores in the autumn season are larger in terms of area when compared to the spring season for both the reference and 2026–2050 periods (Figure 9).

3.3. Cases for Kocaeli, Rize, and Sinop

According to the information obtained from the Ministry of Culture and Tourism, Kocaeli, Rize, and Sinop, which have a coast on the Black Sea in Türkiye, have been declared as “coastal” tourism regions by the Ministry of Culture and Tourism in Türkiye, and have been announced in the list of “Tourism Centers and Culture and Tourism Conservation and Development Zones” in accordance with the Tourism Encouragement Law No. 2634 [63]. The thresholds used for the HCI: Beach and HCI: Urban indices are indicated by the color scale used in the analysis (

Table 3. HCI Color Scale.

Color Scale	Descriptive Rating
0–19.99	Dangerous
20–39.99	Unacceptable
40–49.99	Marginal
50–59.99	Acceptable
60–69.99	Good
70–79.99	Very Good
80–89.99	Excellent
90–100	Ideal

).

In the HCI: Beach index analysis, past and future comparisons between 1976–2000 and 2026–2050 were examined with the RegCM–MPI model. For Kocaeli, despite the score increases in January, February, March, April, July, August, October, November, and December, no categorical change was observed. January, February, March, and December may continue marginal, April and November acceptable, October good, and July and August excellent. Acceptable conditions for May may be very good, and very good conditions for June and September may be excellent. More categorical changes were observed in the RegCM–HG model. No future categorical changes were seen for January, February, July, and August. On the other hand, past marginal comfort conditions for March and December may be acceptable, past acceptable conditions for April and November may be good, past good conditions for May and October may be very good, and past very good conditions for June and September may be excellent (

Table 4. Monthly HCI: Beach and HCI: Urban values for Kocaeli, Rize, and Sinop.

Index	Province	Model	Period	January	February	March	April	May	June	July	August	September	October	November	December
HCI: Beach	Kocaeli	RegCM–MPI	1976–2000	41	42	45	55	66	79	84	85	79	68	52	44
			2026–2050	43	44	48	57	71	81	85	86	81	69	56	46
		RegCM–HG	1976–2000	43	44	46	54	68	79	86	86	78	66	54	46
			2026–2050	46	47	50	60	74	83	86	86	83	72	61	50
	Rize	RegCM–MPI	1976–2000	40	41	45	56	63	74	80	81	76	67	54	44
			2026–2050	42	43	48	57	68	78	83	83	80	71	58	45
		RegCM–HG	1976–2000	43	44	47	56	69	78	85	85	78	71	57	48
			2026–2050	48	48	52	61	74	82	85	84	81	75	63	52
	Sinop	RegCM–MPI	1976–2000	42	42	45	55	65	77	83	84	79	68	53	45
			2026–2050	43	44	48	57	70	80	84	85	81	71	58	46
		RegCM–HG	1976–2000	44	44	46	54	67	78	85	86	78	69	55	47
			2026–2050	46	46	50	59	73	83	86	85	83	74	61	51
HCI: Urban	Kocaeli	RegCM–MPI	1976–2000	60	61	63	70	76	83	85	84	83	76	66	62
			2026–2050	61	62	65	71	79	83	83	82	83	77	68	62
		RegCM–HG	1976–2000	61	61	64	69	77	83	84	85	83	74	67	63
			2026–2050	62	63	66	72	81	81	77	79	83	79	71	64
	Rize	RegCM–MPI	1976–2000	51	52	55	62	66	74	77	78	74	66	59	53
			2026–2050	51	53	56	62	70	76	79	79	76	69	61	53
		RegCM–HG	1976–2000	52	53	55	60	69	77	81	79	72	66	58	54
			2026–2050	54	54	57	62	71	78	80	79	74	68	61	56
	Sinop	RegCM–MPI	1976–2000	56	57	60	67	72	79	82	82	78	71	62	58
			2026–2050	57	58	61	67	74	80	82	82	79	72	64	58
		RegCM–HG	1976–2000	57	58	60	65	74	81	84	83	77	70	62	59
			2026–2050	58	59	62	67	77	81	81	82	80	74	65	60

).

Looking at the RegCM–MPI model for Rize, past marginal comfort conditions for January, February, March, and December may remain the same in the future. Although there have been improvements in the past acceptable comfort conditions for April and November, good for May, very good for June, and excellent for July and August, they may remain in the same category. On the other hand, very good past comfort conditions for September may be excellent and past good comfort conditions for October may be very good. When we look at the RegCM–HG model, the past marginal comfort conditions for January and February, the past excellent comfort conditions for July and August, and the past very good comfort conditions for October may remain in the same category. Past marginal comfort conditions for March and December may be acceptable, and past acceptable comfort conditions for April and November will be good. The past good comfort conditions for May may be very good in the future, and the past very good comfort conditions for June and September may be in the excellent category (Table 4).

Looking at the RegCM–MPI model for Sinop, January, February, March, and December may continue the marginal comfort conditions of the past. The acceptable conditions of April and November in the past may remain the same. July and August may also remain in the same category in the future and may maintain excellent comfort conditions. The good conditions of May and October in the past may be very good, and the very good conditions of June and September may be excellent in the future. Looking at the RegCM–HG model, January and February may continue with the marginal comfort conditions of the past, April may continue with the acceptable comfort conditions of the past, and June and July may continue with the excellent comfort conditions of the past. The past marginal comfort conditions of March and December may be acceptable in the future. The past good comfort conditions of May and October may be very good, the past very good comfort conditions of June and September may be excellent, and the past acceptable conditions of November may be good (Table 4).

In the HCI: Urban index analysis, when looking at the past and future comparison between the years 1976–2000 and 2026–2050 for the RegCM–MPI model for Kocaeli, there is no categorical change in any month. It is seen that the past good comfort conditions of January, February, March, November, and December may remain the same. The very good comfort conditions of April, May, and October in the past may not change in the future. The past excellent comfort conditions of June, July, August, and September may remain the same. In the RegCM–HG model, no categorical change is observed except for five months. The past good comfort conditions of January, February, March, and December may remain the same. The excellent comfort conditions of June and September may not change. On the other hand, the good comfort conditions of April and November may be very good. May’s very good comfort conditions may be excellent. In June and August, there may be a decrease from the excellent category to the very good category, with a decrease of 7 and 6 points, respectively (Table 4).

Looking at Rize, the past acceptable comfort conditions of January, February, March, and December in the RegCM–MPI model may remain the same. The good comfort conditions of April and October in the past may not change. The very good comfort conditions of June, July, August, and September may remain the same. May’s good comfort conditions may be acceptable. The acceptable comfort conditions of November may be good. In the RegCM–HG model, the past acceptable comfort conditions of January, February, March, and December may remain the same, as in the other model. The same applies to April and October, and the good comfort conditions of these months may not change in the future. The very good comfort conditions of June, August, and September and the excellent comfort conditions of July may remain the same. Past good comfort conditions in May may be very good and past acceptable comfort conditions in November may be good (Table 4).

A categorical change may be seen in the RegCM–MPI model for Sinop in just one month. The very good comfort conditions of June may be excellent in the future. The acceptable comfort conditions of January, February, and December in the past may remain the same. The good comfort conditions of March, April, and November may remain the same. The very good comfort conditions of May, September, and October may continue. The past excellent comfort conditions of July and August may remain the same. In the RegCM–HG model, a categorical change is observed in two months. The past very good comfort conditions of September may be excellent, and the past acceptable comfort conditions of December may be good. The past acceptable comfort conditions of January and February, the past good conditions of March, April, and November, the very good comfort conditions of May and October, and the excellent comfort conditions of June, July, and August may remain in the same categories (Table 4).

4. Discussion and Conclusions

Coastal tourism is the largest segment of global leisure tourism and is closely linked to a destination’s resources, such as sea, beaches, natural beauty, rich terrestrial and marine biodiversity, diversified cultural and historical heritage, and especially climatic conditions. Coastal tourism is highly dependent on natural (climate, landscape, ecosystems, etc.) and cultural (historical and cultural heritage, arts and crafts, traditions, etc.) resources. It covers activities that can only be performed in certain areas and under certain conditions. Therefore, certain areas are considered to be particularly suited to the particular types of tourism activities for which they are becoming globally recognized. The fact that countries with a coast on the Mediterranean are popular coastal tourism destinations is an example. However, environmental conditions such as climate change negatively affect these resources and tourism in coastal areas. In addition to carrying out studies to protect the ideal holiday destination conditions in this region by reducing the effects of climate change or adapting to these effects, the creation of alternative tourism destinations may also be beneficial in terms of protecting tourism revenues in adaptation studies.

Türkiye’s popular coastal tourism destinations are also expected to be affected by the adverse conditions of climate change, as coastal tourism cities may face unprecedented challenges under a changing climate. One of the most important effects is the decrease in the comfort level of tourists due to extreme temperatures. This study aimed to see whether the Black Sea coasts can be alternative tourism destinations in the future due to the decrease in tourist comfort due to extreme temperatures in coastal cities in the Aegean and Mediterranean regions of Türkiye.

Most of the previous studies have focused on tourism climatic conditions required by sun, sea, and sand (3S) tourism activities, but none have examined new destinations for coastal tourism activities. Tourism climate indices are effective tools and techniques that can translate weather and climate conditions into information about tourism decisions. In this study, the HCI index was used for the tourism climate assessment of the Black Sea coastal cities of Türkiye. HCI-based findings revealing the climatic characteristics of Türkiye’s coastal tourism cities can provide a convincing basis for policymakers and the tourism industry.

The results show that the Black Sea coasts in Türkiye may have the level of comfort required for beach tourism in the summer season, and even some regions in Istanbul, Sakarya, Ordu, Samsun, Trabzon, and Rize may be in ideal conditions. For the results of the study, it can be said that the index scores of the examined Black Sea Region coasts may increase in the future. This result shows that the comfort conditions for tourists may increase in the region. Studies in the literature examining the effects of climate change on tourist comfort have found positive relationships between arrival data and tourist comfort indices [24,48,64]. Furthermore, the existing literature has indicated a significant correlation between tourism indices and the number of overnight stays in different tourism destinations, despite the lack of a specific definition for these indices [16,65,66]. Based on these findings, it can be said that the coasts of the Black Sea Region, where comfort conditions may increase in the future, may attract more tourists. Based on the possible transfer of increased tourist traffic from the Mediterranean Region to the Black Sea Region, it is necessary to take actions to provide physical conditions that may improve tourist comfort in addition to the climate conditions in the Black Sea Region. In this context, along with transportation and infrastructure improvements, sustainable plans and activities for the creation of physically capable facilities, and coastal arrangements that do not worsen the ecology and the environment should be evaluated and implemented holistically.

The presence of ample evidence that highlights the significance of climate in the decision-making processes of tourists suggests that projected climate changes may have critical consequences for the demand for tourism [28,30,66]. The impact of climate change on coastal tourism destinations can result in changes to the distribution of climate conditions, affecting tourism seasonality, demand, and travel patterns [18,67]. This is due to the alteration of climate characteristics, including sunshine duration, precipitation, humidity, wind speed, and mean temperature, which are known to be influenced by climate change. According to climate projections, it is contended that popular Mediterranean destinations may experience a decline in attractiveness by the 2050s. This diminished appeal can be attributed to the intensification of hot climatic conditions during the peak summer months, which coincide with the period of increased holiday activity. Consequently, the optimal duration for vacationing is expected to decrease. Furthermore, it has been suggested that climate change scenarios indicate potential changes such as the Mediterranean region experiencing increased pleasantness during the spring and autumn seasons [18]. Climate change is anticipated to lead to significant declines in tourism demand, seasonal variations, and the rise of alternative destinations [48,68,69]. The increasing temperatures are expected to enhance the appeal and popularity of geographic locations such as Northern Europe, Scandinavia, and Alaska among tourists [70]. Several studies have suggested that the geographical location of the zone characterized by favorable summer conditions may shift due to climate change. Specifically, these studies indicate that this zone will likely move from the Mediterranean region towards higher latitudes and altitudes, potentially reaching the northern regions or even the poles [18,43,44,45,46,68].

There is an increasing body of literature that focuses on projecting changes in travel patterns caused by climate change. These publications aim to support the tourism sector in its strategic planning and enable it to adapt to evolving climatic circumstances [71]. Adaptation to climate change is a process in which strategies aim to mitigate, cope with, and benefit from climate events. A sustainable approach to tourism destinations requires having a long-term perspective. As markets develop and change, destinations are forced to respond to climate change in terms of tourist facilities and services through adaptation [72,73]. The four main ways the tourism sector can combat climate change and ensure sustainable tourism are as follows [74]: 1. Offsetting the carbon emissions created by tourism. 2. Reducing the impact of tourism on climate change by changing industry practices and consumer behavior. Mitigation can be achieved through behavioral (e.g., changing travel patterns), technological (e.g., movement towards electric vehicles), and policy approaches [75]. 3. Adapting destinations and consumer behavior to climate change. 4. Working with climate scientists to increase understanding of the links between tourism carbon emissions, climate change, and societal needs and adaptation. The adaptation techniques that are most commonly cited include efforts to diversify products or alter destinations. Diversification of tourism and tourist products offered is a possible strategy to adapt to the effects of climate change [76]. This adaptation strategy may involve changes in the areas of policy and management practices and the business models used, and can increase the competitiveness and sustainability of coastal tourism. This measure, which involves the development of products with different atmospheric requirements and less dependence on weather conditions (e.g., congress tourism and health tourism) in a tourist destination, can provide sustainability to the sector in the face of climate change. Developing local, sustainable experiences can contribute to economic growth without increasing tourist numbers while creating more resilient tourism systems [77]. In the last decade, there has been a rapid increase in adaptation strategies for national adaptation policies [78]. National climate policies also contribute to the increase in local adaptation strategies [79]. There is no archetypal planning method for climate change and adaptation strategies may vary locally. For example, as floods and water scarcity are Europe’s most pressing vulnerability to climate change, adaptation planning and implementation focus on flood protection and water management [78,80]. In this context, it is valuable for the study to examine the potential for the emergence of an alternative tourism destination that might be evaluated within the scope of adaptation efforts. As a result, adaptation to climate change in sustainable tourism enables tourist destinations and businesses to be prepared for future climate change scenarios. This is a critical element for the long-term sustainability of tourism, because effectively coping with climate change contributes to the creation of more environmentally, economically, and socially resilient and sustainable tourism models.