**1. Introduction**

Climate and weather are important decision making factors for tourists and also influence the successful operation of tourism businesses, especially winter tourism [1–4]. In recent years, winter outdoor tourism activities have gradually gained popularity in China [5]. Both the governmen<sup>t</sup> and enterprises have increased investment in winter tourism planning. The planning of winter tourism is affected by multiple factors (e.g., climate condition, terrain, land use, etc.); among them, climate and weather are the most important, and changes in these factors will directly affect tourism industry income. Winter tourism is strongly dependent on climate and weather. Under the background of climate change, changing factors lead to changing spatial suitability for winter tourism. To analyze the impact of weather and climate change on the industry, researchers usually develop a comprehensive index to measure the intensity of weather and climate. Weather and climatic index integrate two or multiple meteorological factors that represent weather and climatic characteristics. The weather index represents short-term weather characteristics, while the climate index represents medium and long-term climate characteristics. With the rapid growth of the economy and the increase in property density, the economic losses caused by extreme weather and climate events were increasing significantly. Several kinds of weather and climate indices were proposed by researchers and widely used in agricultural production, energy consumption, commodities, living consumption, health care, tourism, sports and leisure, transportation, insurance and finance and other fields [6–8].

### *Int. J. Environ. Res. Public Health* **2019**, *16*, 186

Vast numbers of references have suggested that the China region is extremely sensitive to climate change [9]. Winter tourism is closely related to climate variations, especially in northeast China regions where resorts are heavily dependent on snow. Increasing temperatures and snow scarce winter seasons pose a big challenge for the winter tourism industry [10]. Increasing winter temperatures, lack of snow, decreasing snow cover and snow depth will result in a shorter skiing season [11], which could lead to smaller number of visitors and reduced revenues, and thus have severe economic impacts on winter tourism destinations [12]. Researches have conducted numerous studies on the impact of climate change on winter tourism. Gaji´cˇcapka and Srnec [13] analyzed the time analysis (fluctuations and trends) in different meteorological parameters related to snow (air temperature, total precipitation and air pressure) as well as snow parameters (snow cover frequency, duration and magnitude) themselves. Hoffmann et al. [14] proposed an econometric analysis model with linear regression and count data, which found a positive influence of the awareness of possible climate change effects on the scope of corporate adaptation. Damm et al. [10] analyzed the economic effects of technical snow production under future climate conditions. Dingeldey and Soboll [15] presented an interactive multi-agent scenario assessment model and used it to examine the future impact of climate change on winter tourism in the German and Austrian Alps. Gonseth [16] assessed the sensitivity of winter tourism consumption to changing snow conditions. Bonzanigo et al. [17] explored how to effectively integrate a climate change adaptation perspective with local discourses about sustainability and tourism, an increasing priority for policy-makers in the region and elsewhere. Besides, several studies analyzed the potential impact on snowmaking under climate change in the future [11,18–20]. The purposes of researchers want to accurately assess regional impact, vulnerability, risks and opportunities of climate change on winter tourism [21–29]. Therefore, the impact of climate change should be taken into account in winter tourism destinations planning.

To determine spatial suitability for winter tourism, it is very meaningful to analyze the spatial change in winter tourism resources under climate change. Snow resources and meteorological elements are the basic factors of winter tourism. With climate change, winter tourism in some regions of the world has been seriously affected by rising temperatures [2,30]. Climate change studies in Northeast China have proved that regional mean snow cover duration decreased at −2.7 days per decade and mean maximum snow depth decreased at −0.5 cm per decade, while low-temperature days (≤−25 ◦C) had a significant decreasing trend of −3.9 days per decade during 1961–2010 [31]. Rising temperature has led to snowfall reduction and a shorter winter tourism season, which has a certain negative impact on snow and ice projects in winter tourism destinations. It has shortened the development season and increased the costs of their tourism products. Therefore, analyzing the temporal and spatial changes in winter tourism resources and allocation can help decision-makers adjust their tourism managemen<sup>t</sup> strategies.

Estimation of snow resources is one problem for winter tourism destinations. Snow resources include snow depth and snow cover days as two factors. Because of the significant signal difference between snow and other surface objects, snow cover is easily obtained by optical remote sensing such as MODIS data (e.g., MOD10C1). Compared with snow cover, snow depth data are difficult to obtain because of the poor penetration of optical remote sensing. Therefore, snow depth data are often traditionally obtained by weather station observations. With the development of passive microwave technology, passive microwave remote sensing data (e.g., Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I)) were widely applied to obtain snow depth due to their all-weather good penetrating ability, not being affected by cloud cover and high temporal resolution. The snow depth retrieved from passive microwave remote sensing data has been gradually promoted, and the brightness temperature gradient is the most representative algorithm [32]. Several studies have applied snow depth observation data to analyze the nonlinear relationship between snow depth and the brightness temperature gradient [33,34]. Che et al. [33] calculated the snow depth based on land use classification and the brightness temperature gradient and obtained the snow depth in China.

### *Int. J. Environ. Res. Public Health* **2019**, *16*, 186

Besides snow resources, meteorological elements are equally important factors for winter tourism. Therefore, the weather index estimation for outdoor activities is another problem for winter tourism. In winter, outdoor snow sports are closely related to weather conditions, and among all the meteorological elements, air temperature and wind speed affect snow sports directly. Furthermore, snow quality is closely related to air temperature. High air temperature makes snow texture sticky and heavy, influencing sliding speed. Low temperature forms brittle ice that causes weak adhesion and easy skidding. For the influence of weather on outdoor sports, the present studies mainly focus on the degree of human body comfort, and the environmental comfort index was analyzed based on sensible human temperatures [35,36]. However, there were fewer studies on the weather conditions for human comfort in sports. In 2017, the Chinese Meteorological Administration issued a standard for the skiing meteorology index [37]. As one of the industries impacted by climate change, several studies analyzed the sensitivity of winter tourism to snow depth and temperature increase over the last decades [2,32,38,39]. The present researchers analyzed the impacts of climate change on winter skiing tourism areas and indicated that future climate change would shorten the skiing season and sharply reduce skiing visitors, causing economic loss in low altitude and low latitude skiable areas [40]. Several studies found that climate change has a negative impact on the sustainable development of winter tourism, skiing tourism and tourism vulnerability [17,41,42]. In the comprehensive evaluation of winter tourism resources, the present study mainly focuses on the qualitative analysis and characteristic description and lacks a precise quantitative analysis of spatial suitability assessment, which limited its application [43–45]. Under the background of climate change, winter tourism industries will face serious challenges. For governmen<sup>t</sup> managers, how to rationally determine the winter tourism development zone under the influence of climate change has become an important problem that urgently needs to be solved. This has grea<sup>t</sup> significance for the sustainable development of the regional tourism industrial economy.

The winter tourism literature indicates that: (1) meteorological conditions and snow resources are two primary factors for winter tourism suitability assessment; however, very few studies have analyzed the temporal and spatial distribution coupling relationship of the two factors as well as the impacts on tourism planning. (2) The present research is mainly focused on the qualitative description of winter resources, lacking quantitative analysis of spatial suitability distribution, and is not suitable for tourism planning decisions. (3) The impact of climate change on winter tourism is uncertain. To avoid the impact of climate fluctuations on winter tourism, it is of grea<sup>t</sup> significance to obtain the spatially suitable development areas. To address these problems, this study proposes the meteorological suitability and snow abundance indices for winter tourism based on meteorological and snow data. Firstly, by analyzing the influence of weather conditions on snow cover and outdoor activities, air temperature, wind speed, relative humidity, and visibility are selected to establish the climate suitability index. Secondly, the depth and duration of snow cover are selected to characterize the spatial abundance of regional snow resources, which is used to establish a snow abundance index. To express the coupling effect of these two indices on winter tourism, the spatial joint probability of the two indices is calculated to express the spatial suitability for winter tourism using the Copula function. Finally, taking Jilin province as the area, this study analyzes temporal and spatial distribution and establishes the suitability of winter tourism resources. This study will provide a new method to analyze the impact of climate change on winter tourism. The proposed method and results will have a guiding significance for ice-snow tourism planning in winter tourism destination countries.
