Journal articles: 'Climate Index for Tourism (TCI)'

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Haryadi, Adhityo, Eko Kusratmoko, and Asep Karsidi. "Climate Comfort Analysis for Tourism in Samosir District." E3S Web of Conferences 94 (2019): 05001. http://dx.doi.org/10.1051/e3sconf/20199405001.

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Tourism has become one of the sectors which are the mainstay source of foreign exchange in Indonesia. One of the region which has tourism potential is Samosir District at North Sumatra Province. Climatic conditions affect the tourist comfortability while doing the tourism activity. Studies on climate comfort in Toba Lake Region, especially in Samosir District have not been done. Way to determine the level of comfort associated with tourism activities are known to the Tourism Climate Index (TCI). This research aims to determine the level of climate comfort tourist destinations in Samosir District based on the value of TCI and knowing the relation between TCI value with the number of visits a tourist destination.

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Alonso-Pérez, Silvia, Javier López-Solano, Lourdes Rodríguez-Mayor, and José Miguel Márquez-Martinón. "Evaluation of the Tourism Climate Index in the Canary Islands." Sustainability 13, no. 13 (June 23, 2021): 7042. http://dx.doi.org/10.3390/su13137042.

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In this study, we performed a diagnostic and evolutive analysis of the bioclimatology of the Canary Islands, an Atlantic archipelago where the climate itself is a main feature promoting tourism. Among all the tourist-climate indices described in the literature, we evaluated the most widely used, which is the Tourism Climate Index (TCI) proposed by Mieczkowski (1985). Monthly mean TCI time series were calculated using meteorological data from the Spanish State Meteorological Agency database and the European Climate Assessment and Dataset. Our results show TCI values greater than 50 during almost every month in the period 1950–2018, with mean values over the entire time series between 70 and 80. According to the TCI classification scheme, these values correspond to a very good thermal comfort along all of the period. Our results also point to spring as the season with the best TCI, with maximum values around 80 for this index in April—excellent according to the TCI classification. However, we did not find a correlation between inbound arrivals and the TCI index, which might point to a lack of information available to tourists. This opens an opportunity for policymakers and tour operators to better publicize the best seasons for holidays in the islands.

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Hoang Thi Kieu, Oanh. "Assessment climate resource of Con Dao island (Vietnam) by using the tourism climate index." Journal of Science Natural Science 66, no. 1 (March 2021): 188–97. http://dx.doi.org/10.18173/2354-1059.2021-0022.

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This article assesses climatic conditions for tourism by using Tourism Climate Index - TCI, published by Mieczkowsk (1985). This is an experimental synthetic climatic index that evaluates simultaneously the influence of 7 climatic elements as maximum average temperature (oC), minimum average humidity (%), average temperature (oC), average humidity (%), the number of sunny hours, windy speed of Con Dao island. The results of TCI within 12 months in Con Dao island compare to “Classification of advantageous levels of climate for tourism” of TCI (Mieczkowsk, 1985) which shows the advantages of Con Dao for relaxation tourism all year round. The period from December to April is the most favourable time for tourism activities in Con Dao because the TCI index reaches from Good to Very good, while the suitable time is from May to November, due to rainfall and high speed of wind during the rainy season.

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Rutty, Michelle, Daniel Scott, Lindsay Matthews, Ravidya Burrowes, Adrian Trotman, Roché Mahon, and Amanda Charles. "An Inter-Comparison of the Holiday Climate Index (HCI:Beach) and the Tourism Climate Index (TCI) to Explain Canadian Tourism Arrivals to the Caribbean." Atmosphere 11, no. 4 (April 20, 2020): 412. http://dx.doi.org/10.3390/atmos11040412.

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Through an empirical investigation of the historical relationship between the destination climate and tourist arrivals in the Caribbean, this study presents the first revealed preference evaluation of a climate index informed by tourists’ stated climatic preferences for coastal-beach tourism (i.e., a sun-sand-surf or 3S travel market). The goal of this multi-organization collaboration was to examine the potential application of a newly designed climate index—the Holiday Climate Index (HCI):Beach—for three Caribbean destinations (Antigua and Barbuda, Barbados, Saint Lucia). This paper provides an overview of the evolution of climate indices, including the development of the (HCI):Beach. To test the validity of climate indices for a beach travel market, daily climate ratings based on outputs from the Tourism Climate Index and the HCI were correlated with monthly arrivals data from Canada (a key source market) at an island destination scale. The results underscore the strength of the new index, with each destination scoring consistently higher using the HCI:Beach, including a stronger relationship (R2) between index scores and tourist arrivals. These findings demonstrate the value of combining stated and revealed preference methodologies to predict tourism demand and highlight opportunities for future research.

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Siedlecki, Mariusz. "An evaluation of changes in the bioclimate of Łódź in the light of the tourism climate index." Turyzm/Tourism 25, no. 2 (February 7, 2017): 21–25. http://dx.doi.org/10.1515/tour-2015-0002.

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The paper presents basic information concerning bioclimatic conditions in Łódź based on the Tourism Climate Index (TCI). The index makes it possible to assess in a comprehensive manner, based on specified meteorological parameters, the climatic conditions affecting the development of tourism. The study uses measurements from the weather station, Łódź-Lublinek, taken in the years 1966-2014. The TCI values have a distinct annual pattern with the highest values recorded in summer. The summer season has the highest frequency of days with ‘very good’ or ‘excellent’ conditions for tourism. An assessment of the variability of bioclimatic conditions indicates an increase in the number of days with high TCI values pointing to ‘very good’ or ‘excellent’ conditions for tourism and recreation.

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Németh, Ákos. "Estimation of Tourism Climate in the Lake Balaton Region, Hungary." Journal of Environmental Geography 6, no. 1-2 (April 1, 2013): 49–55. http://dx.doi.org/10.2478/v10326-012-0006-0.

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Abstract Lake Balaton is one of the most important and best-known tourist destinations in Hungary. Although in the last few years, several efforts were implemented to increase the length of the tourist season, the highest visitor turnover occurs in the summer months. We mostly regard the Lake Balaton as a bathing place, despite of the fact that the region offers more and more tourism products. The beach tourism and other lakeside activities are highly dependent on weather and climate. In order to know that a region's climate what extent is suitable to the given tourism activities, the tourism climate potential must be determined. This study aims to illustrate observed changes of the tourism climate potential of Lake Balaton Region during the last half century, by using Tourism Climatic Index (TCI) and Climate-Tourism-Information-Scheme (CTIS). The analysis is based on the long-term measured datasets of Siófok synoptic station. Based on the TCI, the tourism climate potential of the examined region is barely changed over the past 50 years; significant changes can be detected only in February and June. By using the CTIS, smaller changes can also be detected. Such changes are: moderate improvement of the thermal comfort in spring and autumn, slight increase in sunny hours in the tourism season, as well as the sultriness becomes more frequent in the summer months. The results may represent useful background information to the policy decision-makers.

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Croce, Valeria. "Can tourism confidence index improve tourism demand forecasts?" Journal of Tourism Futures 2, no. 1 (March 14, 2016): 6–21. http://dx.doi.org/10.1108/jtf-12-2014-0026.

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Purpose The link between confidence and economic decisions has been widely covered in the economic literature, yet it is still an unexplored field in tourism. The purpose of this paper is to address this gap, and investigate benefits in forecast accuracy that can be achieved by combining the UNWTO Tourism Confidence Index (TCI) with statistical forecasts. Design/methodology/approach Research is conducted in a real-life setting, using UNWTO unique data sets of tourism indicators. UNWTO TCI is pooled with statistical forecasts using three distinct approaches. Forecasts efficiency is assessed in terms of accuracy gains and capability to predict turning points in alternative scenarios, including one of the hardest crises the tourism sector ever experienced. Findings Results suggest that the TCI provides meaningful indications about the sign of future growth in international tourist arrivals, and point to an improvement of forecast accuracy, when the index is used in combination with statistical forecasts. Still, accuracy gains vary greatly across regions and can hardly be generalised. Findings provide meaningful directions to tourism practitioners on the use opportunity cost to produce short-term forecasts using both approaches. Practical implications Empirical evidence suggests that a confidence index should not be collected as input to improve their forecasts. It remains a valuable instrument to supplement official statistics, over which it has the advantage of being more frequently compiled and more rapidly accessible. It is also of particular importance to predict changes in the business climate and capture turning points in a timely fashion, which makes it an extremely valuable input for operational and strategic decisions. Originality/value The use of sentiment indexes as input to forecasting is an unexplored field in the tourism literature.

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ALDabbas, Ashraf, Zoltan Gal, and Buchman Attila. "Neural Network Estimation of Tourism Climatic Index (TCI) Based on Temperature-Humidity Index (THI)-Jordan Region Using Sensed Datasets." Carpathian Journal of Electronic and Computer Engineering 11, no. 2 (December 1, 2018): 50–55. http://dx.doi.org/10.2478/cjece-2018-0019.

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Abstract Jordan which is located in the heart of the world contains hundreds of historical and archaeological locations that have a supreme potential in enticing visitors. The impact of clime is important on many aspects of life such as the development of tourism and human health, tourists always wanted to choose the most convenient time and place that have appropriate weather circumstances. The goal of this study is to specify the preferable months (time) for tourism in Jordan regions. Neural network has been utilized to analyze several parameters of meteorologist (raining, temperature, speed of wind, moisture, sun radiation) by analyzing and specify tourism climatic index (TCI) and equiponderate it with THI index. The outcomes of this study shows that the finest time of the year to entice tourists is “ April” which is categorized as to be “extraordinary” for visitors. TCI outcomes indicates that conditions are not convenient for tourism from July to August because of high temperature.

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Roson, Roberto, and Martina Sartori. "Climate change, tourism and water resources in the Mediterranean." International Journal of Climate Change Strategies and Management 6, no. 2 (May 13, 2014): 212–28. http://dx.doi.org/10.1108/ijccsm-01-2013-0001.

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Purpose – This paper aims to present and discuss some quantitative results obtained in assessing the economic impact of variations in tourism flows, induced by climate change, for some Mediterranean countries. Design/methodology/approach – Estimates by a regional climate model are used to build a tourism climate index, which indicates the suitability of climate, in certain locations, for general outdoor activities. As climate change is expected to affect a number of variables like temperature, wind and precipitation, it will have consequences on the degree of attractiveness of touristic destinations. The authors estimate the macroeconomic consequences of changing tourism flows by means of a computable general equilibrium model. Findings – The authors found that more incoming tourists will increase income and welfare, but this phenomenon will also induce a change in the productive structure, with a decline in agriculture and manufacturing, partially compensated by an expansion of service industries. The authors found that, in most countries, the decline in agriculture entails a lower demand for water, counteracting the additional demand for water coming from tourists and bringing about a lower water consumption overall. Research limitations/implications – A great deal of uncertainty affects, in particular: estimates of future climate conditions, especially for variables different from temperature, the relationship between climate and tourist demand, and its interaction with socio-economic variables. This also depends on the reliability of the TCI index as an indicator of climate suitability for tourism, on its application to spatially and temporally aggregated data, on the degree of responsiveness of tourism demand to variations in the TCI. Furthermore, as the authors followed here a single region approach, the authors were not able to consider in the estimates the impact of climate change on the global tourism industry. Nonetheless, the authors believe that a quantitative analysis like the one presented here is not without scope. First, it provides an order of magnitude for the impact of climate change on tourism and the national economy. Second, it allows to assess systemic and second-order effects, which are especially relevant in this context and, moreover, appear to be sufficiently robust to alternative model specifications. In other words, the value added of this study does not lie in the specific figures obtained by numerical computations, but on the broader picture emerging from the overall exercise. Originality/value – To the authors' knowledge, this is the first study in which, by assessing higher tourism attractiveness into a general equilibrium framework, the effect described above is detected and highlighted.

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Sudiar, Nofi Yendri. "KENYAMANAN IKLIM LOKASI WISATA BERBASIS ALAM DI KAWASAN TROPIS." Agromet 33, no. 2 (December 18, 2019): 53–61. http://dx.doi.org/10.29244/j.agromet.33.2.53-61.

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This research reveals visitors perceptions of climate comfort in nature-based tourism areas in Ecopark Ancol, Bogor Botanical Gardens (KRB) and Cibodas Botanical Gardens (KRC). In addition to calculating the comfort score using the TCI and HCI methods and modifying their thermal aspects, a survey was also carried out in all three tourism areas simultaneously. The survey was conducted to collect data on climate comfort perceptions and the role of the weather on these comfort. A total of 793 respondents participated in this study. The majority of visitors stated that the weather affected the comfort of the climate during the tour. But weather conditions do not fully influence decisions in the selection of tourist visits. The level of perceived climate comfort for the three tourism sites namely Ecopark was perceived as neutral (57.3%), KRB was perceived as comfortable (60%) and KRC was perceived as comfortable (78.4%). While based on the score calculation approaching the survey results in Ecopark is TCI index modified in its thermal aspect with PET Tianjin (57.2). KRB is HCI without modification (59) and KRC is HCI modified by its thermal aspect with PET Tianjin (77.6). Statistically there are significant differences between sex, age, education level and topography. By understanding visitor perceptions, strategies and appropriate actions can be developed to increase comfort in the nature-based tourism industry.

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Scott, Daniel, Michelle Rutty, Bas Amelung, and Mantao Tang. "An Inter-Comparison of the Holiday Climate Index (HCI) and the Tourism Climate Index (TCI) in Europe." Atmosphere 7, no. 6 (June 7, 2016): 80. http://dx.doi.org/10.3390/atmos7060080.

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Mihăilă, Dumitru, and Petruț Ionel Bistricean. "The Suitability of Moldova Climate for Balneary - Climatic Tourism and Outdoor Activities - A Study Based on the Tourism Climate Index." Present Environment and Sustainable Development 12, no. 1 (June 1, 2018): 263–82. http://dx.doi.org/10.2478/pesd-2018-0021.

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Abstract This study addresses a current issue concerning spatial and temporal analysis of Moldova's climate resources and is intended for the use of people involved in various tourism and related activities. For researchers in the field, the study will be a source of information, allowing comparison of the results obtained for other locations, and for practitioners an indispensable working tool. The motivation for the present study resides in the sparseness and ambiguity of the analysis of climate resources for tourism included in the assessment of the natural tourism potential of Romania. We aim to improve this approach by constructing for Moldova a statistically relevant, quantitative analysis of what climate offers the tourists. To achieve the proposed objectives, we used TCI and a climate database sufficiently detailed to capture climate patterns up to ten-days time intervals. We showed that in Moldova the May-September interval is the most favorable for developing all forms of tourism. We then customized the analysis at the level of each tourism resort. Our study is among the first in this region to use such analysis and provides clear research results to those involved in tourism to improve their decision-making process. The results are very important in supporting tourism in Moldova and will contribute to raising the economic potential of the region.

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Zhao, Junyuan, and Shengjie Wang. "Spatio-Temporal Evolution and Prediction of Tourism Comprehensive Climate Comfort in Henan Province, China." Atmosphere 12, no. 7 (June 27, 2021): 823. http://dx.doi.org/10.3390/atmos12070823.

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The tourism comprehensive climate comfort index (TCCI) was used to evaluate the tourism climate comfort in Henan Province in the last 61 years, and its future development trend is predicted. The results showed that the temporal variation of the TCCI had a “double peak” type (monthly variation), and an overall comfort improvement trend (interannual variation). The change of tourism climate comfort days was similar to the change of the index, especially in the months with a low comfort level. In space, the distribution of the TCCI gradually increased from northeast to southwest, and the area with a high comfort level also increased over time. Meanwhile, it also showed the spatial distribution of months with a low comfort level, which provides reliable information for tourists to use when choosing tourist destinations across all periods of the year. The TCCI was classified by hierarchical classification, and principal components were extracted to explore the main climate factors controlling different types of TCCIs and the relationship between them, and large-scale atmospheric–oceanic variability. According to the temporal change trend and correlation, the long-term change trend of tourism climate comfort was predicted, which will provide a scientific basis for tourism planners to choose tourist destinations.

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Kumar, Vinay. "Development of Precise Indices for Assessing the Potential Impacts of Climate Change." Atmosphere 11, no. 11 (November 15, 2020): 1231. http://dx.doi.org/10.3390/atmos11111231.

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The Special Issue on climate indices and climate change deals with various kinds of indices exits to assess weather and climate over a region. These indices might be based on local, regional, remote variables, which may affect and define the weather and climate of a region. Climate indices are the time series used to monitor the state of the climate and its relationship with other possible causes. With indices being myriad, it is challenging to choose which one is appropriate for a region of interest. However, the relationship between the indices and the climate of a region varies. El-Nino Southern Oscillation (Southern Oscillation Index, SOI/ENSO) is one of the most robust climate signals that stimulate rainfall, temperature, and hurricanes via teleconnections. SOI has a correlation of 0.5 over the Indonesian archipelago. Here, some of the well-known indices Holiday Climate Index (HCI), Tourism Climate Index (TCI), and Simple Diversity Index (SDI) are being reconnoitered to understand the holiday-tourism, end-of-the-day (EOD) judgment. The intrusion of dry air in the middle troposphere can create unstable weather, leading to heavy precipitation. The Special Issue seeks to encourage researchers to discover new indices in multidisciplinary department of atmospheric and physical sciences.

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Noome, Kirsten, and Jennifer M. Fitchett. "An assessment of the climatic suitability of Afriski Mountain Resort for outdoor tourism using the Tourism Climate Index (TCI)." Journal of Mountain Science 16, no. 11 (November 2019): 2453–69. http://dx.doi.org/10.1007/s11629-019-5725-z.

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Sudiar, Nofi Yendri, Yonny Koesmaryono, Perdinan Perdinan, and Hadi Susilo Arifin. "KARAKTERISTIK DAN KENYAMANAN IKLIM LOKASI WISATA BERBASIS ALAM DI ECO-PARK ANCOL, KEBUN RAYA BOGOR DAN KEBUN RAYA CIBODAS." EnviroScienteae 15, no. 2 (August 21, 2019): 240. http://dx.doi.org/10.20527/es.v15i2.6967.

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This research explores the characteristics and comfort of climate in nature-based tourism areas in Ancol Eco-Park (EPA) (3masl), Bogor Botanical Gardens (KRB)(260 masl) and Cibodas Botanical Gardens (KRC) (1340 masl). Climate characteristics use the Schmidt-Ferguson and Koppen classifications. Calculation of climate comfort scores using TCI and HCI methods and modifying the thermal aspects. In addition to surveys with questionnaires, measurements of temperature, humidity and wind speed were carried out in all three regions simultaneously. Climate classification according to Schmidt-Ferguson obtained by KRB is type A climate, EPA and KRC are type C climate. Classification according to Koppen, the three regions include the climate of the tropical rainforest namely EPA (Am), KRB and KRC (Af). The vegetation component dominates the three tourist areas with a percentage of over 60% of the tourist areas. The climate comfort index based on calculations results in a comfortable KRC area throughout the year while EPA and KRB are comfortable in the dry season. Comparison of comfort index based on calculations with visitor perceptions results in thermal aspects for the tropics needing to be modified. From 12:00-12:59 WIB to 13:00-13:59 WIB, the most uncomfortable hours of the day. Temperature intervals with comfortable categories are 25.2°C - 29.0°C or effective temperatures between 20.5°C - 24.6°C.

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Tanana, Ariadna Belén, María Belén Ramos, Verónica Gil, and Alicia María Campo. "Confort climático y turismo. Estudio aplicado a diferentes niveles de resolución temporal en Puerto Iguazú, Argentina." Estudios Geográficos 82, no. 290 (June 22, 2021): e064. http://dx.doi.org/10.3989/estgeogr.202076.076.

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El clima es un factor que condiciona las prácticas turístico-recreativas en espacios al aire libre. El bienestar y confort térmico constituyen exigencias del visitante susceptibles de evaluarse mediante la faceta térmica del clima. Este trabajo se aplica a Puerto Iguazú, un destino de clima subtropical húmedo. El mismo está estructurado con base en dos objetivos, por un lado, comparar tres índices bioclimáticos: Complejo Termo-anemométrico (P), Complejo Termo-higrométrico (THI) y Humidex (H), versus un índice climático-turístico: Tourism Climate Index (TCI) a fin de establecer cuál ofrece un mejor ajuste a la realidad estudiada. Por otro, a fin de generar información con mayor grado de detalle, se busca conocer el comportamiento en resolución horaria del P y H. El cálculo de los índices a nivel mensual (P, THI, H y TCI) se realizó con base en las estadísticas climatológicas de la estación Iguazú Aero para el período 1981-2010, proporcionadas por el Servicio Meteorológico Nacional. Los índices P y H en resolución horaria se calcularon a partir de datos meteorológicos de la misma estación para el período 2001-2010, obtenidos del sitio Meteomanz.com. Los resultados obtenidos muestran que la componente termo-higrométrica es la de mayor peso en el destino analizado, lo cual es coherente con sus características climáticas. La aplicación de los índices permitió determinar los momentos del año y horas del día más benignas para la realización de prácticas turístico-recreativas al aire libre.

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Zhong, Linsheng, Hu Yu, and Yuxi Zeng. "Impact of climate change on Tibet tourism based on tourism climate index." Journal of Geographical Sciences 29, no. 12 (December 2019): 2085–100. http://dx.doi.org/10.1007/s11442-019-1706-y.

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Bento, Virgílio, Isabel Trigo, Célia Gouveia, and Carlos DaCamara. "Contribution of Land Surface Temperature (TCI) to Vegetation Health Index: A Comparative Study Using Clear Sky and All-Weather Climate Data Records." Remote Sensing 10, no. 9 (August 21, 2018): 1324. http://dx.doi.org/10.3390/rs10091324.

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The Vegetation Health Index (VHI) is widely used for monitoring drought using satellite data. VHI depends on vegetation state and thermal stress, respectively assessed via (i) the Vegetation Condition Index (VCI) that usually relies on information from the visible and near infra-red parts of the spectrum (in the form of Normalized Difference Vegetation Index, NDVI); and (ii) the Thermal Condition Index (TCI), based on top of atmosphere thermal infrared (TIR) brightness temperature or on TIR-derived Land Surface Temperature (LST). VHI is then estimated as a weighted average of VCI and TCI. However, the optimum weights of the two components are usually not known and VHI is usually estimated attributing a weight of 0.5 to both. Using a previously developed methodology for the Euro-Mediterranean region, we show that the multi-scalar drought index (SPEI) may be used to obtain optimal weights for VCI and TCI over the area covered by Meteosat satellites that includes Africa, Europe, and part of South America. The procedure is applied using clear-sky Meteosat Climate Data Records (CDRs) and all-sky LST derived by combining satellite and reanalysis data. Results obtained present a coherent spatial distribution of VCI and TCI weights when estimated using clear- and all-sky LST. This study paves the way for the development of a future VHI near-real time operational product for drought monitoring based on information from Meteosat satellites.

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Mihăilă, Dumitru, Adrian Piticar, Andrei-Emil Briciu, Petruţ-Ionel Bistricean, Liliana Gina Lazurca, and Anatolie Puţuntică. "Changes in bioclimatic indices in the Republic of Moldova (1960–2012): consequences for tourism." Boletín de la Asociación de Geógrafos Españoles, no. 77 (June 13, 2018): 521–48. http://dx.doi.org/10.21138/bage.2550.

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El presente estudio incluye el análisis diagnóstico y evolutivo del bioclima de la República de Moldavia según Wind Chill Index (WCI) y Cooling Power (CP). Entre 1960 y 2012, el bioclima de la temporada fría (octubre-marzo) presentó una tendencia de calentamiento gradual, evidenciada por la baja de los valores de WCI. Durante la temporada cálida, el bioclima de la República de Moldovia registró un calentamiento gradual, evidenciado por la baja de los valores de CP. Los valores del índice CP han sido analizados según los valores del Índice Climático turístico (TCI), útil para planificar actividades turísticas de cualquier tipo. Los valores actuales de TCI y los anticipados para el futuro indican un clima favorecedor para todo tipo o toda clase de turismo en la República Moldavia.

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Chung, Il-Ung, Chang-Mook Lim, and Jae-Seung Yoon. "Change of Tourism Climate Resources in Gangwon-do Based on the Tourism Climate Index." Journal of Climate Research 8, no. 3 (September 30, 2013): 237–51. http://dx.doi.org/10.14383/cri.2013.8.3.237.

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Fang, Yan, and Jie Yin. "National Assessment of Climate Resources for Tourism Seasonality in China Using the Tourism Climate Index." Atmosphere 6, no. 2 (January 26, 2015): 183–94. http://dx.doi.org/10.3390/atmos6020183.

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Khaledi, Chakavak Khajeh Amiri. "A Case Study of Evaluation and Distribution of Tourism Climate by Using TCI: Baluchestan Region of Iran." Open Journal of Geology 07, no. 08 (2017): 1227–37. http://dx.doi.org/10.4236/ojg.2017.78082.

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Yu, Dan-Dan, Shan Li, and Zhong-Yang Guo. "Evaluating the Tourist Climate Comfortable Period of China in a Changing Climate." Advances in Meteorology 2020 (July 25, 2020): 1–11. http://dx.doi.org/10.1155/2020/8886316.

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The evaluation of climate comfort for tourism can provide information for tourists selecting destinations and tourism operators. Understanding how climate conditions for tourism evolve is increasingly important for strategic tourism planning, particularly in rapidly developing tourism markets like China in a changing climate. Multidimensional climate indices are needed to evaluate climate for tourism, and previous studies in China have used the much criticized “climate index” with low resolution climate data. This study uses the Holiday Climate Index (HCI) and daily data from 775 weather stations to examine interregional differences in the tourist climate comfortable period (TCCP) across China and summarizes the spatiotemporal evolution of TCCP from 1981 to 2010 in a changing climate. Overall, most areas in China have an “excellent” climate for tourism, such that tourists may visit anytime with many choices available. The TCCP in most regions shows an increasing trend, and China benefits more from positive effects of climate change in climatic conditions for tourism, especially in spring and autumn. These results can provide some scientific evidence for understanding human settlement environmental constructions and further contribute in improving local or regional resilience responding to global climate change.

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Wang, Keyi, Tiejian Li, and Jiahua Wei. "Exploring Drought Conditions in the Three River Headwaters Region from 2002 to 2011 Using Multiple Drought Indices." Water 11, no. 2 (January 23, 2019): 190. http://dx.doi.org/10.3390/w11020190.

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The Three River Headwaters Region (TRHR) has great uncertainty on drought conditions under climate change. The aim of this study is to compare the drought conditions detected by multiple drought indices across the TRHR. We applied four single drought indices, i.e., Precipitation Condition Index (PCI), Temperature Condition Index (TCI), Soil Moisture Condition Index (SMCI), and Vegetation Condition Index (VCI), and two combined drought indices, i.e., Combined Meteorological Drought Index (CMDI) and Combined Vegetation drought index (CVDI), to explore the drought conditions across the TRHR. Three in situ drought indices, Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Non-Parametric Index (SNPI) were used to evaluate the performances of multiple drought indices. The results include various drought conditions detected by multiple drought indices, as well as a comparative study among different drought indices. Through the comparative study, we found that PCI was a desirable single index to monitor meteorological drought. TCI was suitable for monitoring agricultural/vegetation drought. SMCI and VCI should be avoided for monitoring drought in this region. CMDI was an appropriate meteorological drought index, and CVDI was a promising indicator in monitoring agricultural/vegetation drought.

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Olya, Hossein G. T., and Habib Alipour. "Risk assessment of precipitation and the tourism climate index." Tourism Management 50 (October 2015): 73–80. http://dx.doi.org/10.1016/j.tourman.2015.01.010.

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Bakhtiari, Arshin, and Bahram Bakhtiari. "Three-dimensional Analysis of Tourism Climate Index Across Iran." geographical researches quarterly journal 32, no. 4 (March 1, 2018): 158–74. http://dx.doi.org/10.29252/geores.32.4.158.

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Nguyen, Thu-Nhung, Hoang-Hai Pham, Van-Manh Pham, and Manh-Ha Nguyen. "Tourism climate index on the Co To islands of Quang Ninh province, Vietnam." Tạp chí Khoa học và Công nghệ biển 20, no. 3 (July 8, 2020): 255–66. http://dx.doi.org/10.15625/1859-3097/20/3/15250.

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Tourism is one of the spearhead economic sectors of every country in the world and sensitive to weather conditions. The climate is one of the most important factors for each destination for vacation and recreation. Almost the measures are primarily based on particular local weather and climate, and part of them deals with energy balance estimation to assess thermal comfort. Tourism climate indicator developed by Mieczkowski (1985) incorporates 7 climate variables (average temperature, maximum temperature, average humidity, minimum humidity, precipitation, number of sunny hours, wind speed) relevant to general tourism activities is used to assess potential impacts of climate change on tourism climate resources of Co To islands in the Tonkin Gulf of Vietnam. The monthly tourism climate indicator classification results show that the tourism potentials of Co To islands range from unfavorable (30–39) to very good (70–79) in March, April, November and December. Daily tourism climate indicator classification results indicate that tourism potentials are from extremely unfavorable (20–29) to excellent (80–89). The days at very good to excellent for travel are on 2nd, 3rd, 5–7th of January; 6–8th and 20–28th of February; 1st–8th, 12–17th and 20–28th of March; 1st–2nd,4–13th, 15–18th of April; 21st–24th of September; 1st–4th, 6th, 8–10th, 12th, 13th of November; 1st–26th of December. These findings are important for future research in assessing current and future climate suitability for sustainable tourism development.

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Park, Changyong. "A Study on the Changes of Tourism Climate Conditions Using Korea Tourism Climate Index (KTCI) of South Korea." Journal of Climate Research 10, no. 3 (September 30, 2015): 231–45. http://dx.doi.org/10.14383/cri.2015.10.3.231.

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Li, Hengyun, Carey Goh, Kam Hung, and Jason Li Chen. "Relative Climate Index and Its Effect on Seasonal Tourism Demand." Journal of Travel Research 57, no. 2 (January 23, 2017): 178–92. http://dx.doi.org/10.1177/0047287516687409.

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This study proposes a relative climate index based on the push and pull theory to assess the effects of relative climate variability on seasonal tourism demand. The relative climate index measures the climatic comfort of a destination relative to that of the tourist origin. Using the proposed approach, the effects of the relative climate comfort on seasonal tourism demand are empirically tested based on a quarterly panel data set of visitor arrivals from Hong Kong to 13 major Chinese cities. The intra-annual seasonality and interannual variability are both tested in the model. The results indicate that the intra-annual relative climate positively influences tourism demand in Mainland regions, where the climate is significantly different from that of Hong Kong.

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Ma, Siyao, Christopher A. Craig, and Song Feng. "The Camping Climate Index (CCI): The development, validation, and application of a camping-sector tourism climate index." Tourism Management 80 (October 2020): 104105. http://dx.doi.org/10.1016/j.tourman.2020.104105.

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Perch-Nielsen, Sabine L., Bas Amelung, and Reto Knutti. "Future climate resources for tourism in Europe based on the daily Tourism Climatic Index." Climatic Change 103, no. 3-4 (January 14, 2010): 363–81. http://dx.doi.org/10.1007/s10584-009-9772-2.

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Joksimovic, Marko, Mirjana Gajic, and Rajko Golic. "Tourism climatic index in the valorisation of climate in tourist centers of Montenegro." Glasnik Srpskog geografskog drustva 93, no. 1 (2013): 15–34. http://dx.doi.org/10.2298/gsgd1301015j.

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Climate is one of the main factors for the development of recreational forms of tourism in Montenegro. It affects the temporal arrangement and spatial distribution of tourists throughout the year. It determines the context of the environment in which the activities of tourists take place and represents the tourism resources. It is important for the planning and construction of tourism facilities and infrastructure, as well as the organization of tourism activities. This paper presents the tourism climatic index as a bioclimatic indicator for determining the conditions suitable for recreational tourism throughout the year. Research results according to the case study indicate the comparative advantages and also the lack of climate as the resource in tourism of Montenegro. There is an apparent underutilization of periods with climate conditions that work in favour of recreational forms of tourism. The uneven spatial and temporal arrangement of suitable climatic conditions in the tourist centres is the factor of the formation of seasonality of tourism trends. However, the results of linear correlation of tourism climatic index and monthly visits point to the incompatibility of potentials with capacity utilization.

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MAHMOUD, Dalia, Gamil GAMAL, and Tarek ABOU EL SEOUD. "THE POTENTIAL IMPACT OF CLIMATE CHANGE ON HURGHADA CITY, EGYPT, USING TOURISM CLIMATE INDEX." GeoJournal of Tourism and Geosites 25, no. 2 (July 31, 2019): 496–508. http://dx.doi.org/10.30892/gtg.25218-376.

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Rahman, Atiqur, Leonid Roytman, Mitch Goldberg, and Felix Kogan. "Comparative Analysis on Applicability of Satellite and Meteorological Data for Prediction of Malaria in Endemic Area in Bangladesh." Journal of Tropical Medicine 2010 (2010): 1–8. http://dx.doi.org/10.1155/2010/914094.

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Relationships between yearly malaria incidence and (1) climate data from weather station and (2) satellite-based vegetation health (VH) indices were investigated for prediction of malaria vector activities in Bangladesh. Correlation analysis of percent of malaria cases with Advanced Very High Resolution Radiometer- (AVHRR-) based VH indices represented by the vegetation condition index (VCI—moisture condition) and the temperature condition index (TCI—estimates thermal condition) and with rainfall, relative humidity, and temperature from ground-based meteorological stations. Results show that climate data from weather stations are poorly correlated and are not applicable to estimate prevalence in Bangladesh. The study also has shown that AVHRR-based vegetation health (VH) indices are highly applicable for malaria trend assessment and also for the estimation of the total number of malaria cases in Bangladesh for the period of 1992–2001.

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de Freitas, C. R., Daniel Scott, and Geoff McBoyle. "A second generation climate index for tourism (CIT): specification and verification." International Journal of Biometeorology 52, no. 5 (December 20, 2007): 399–407. http://dx.doi.org/10.1007/s00484-007-0134-3.

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Perch-Nielsen, Sabine L. "The vulnerability of beach tourism to climate change—an index approach." Climatic Change 100, no. 3-4 (September 24, 2009): 579–606. http://dx.doi.org/10.1007/s10584-009-9692-1.

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Özşahin, Emre, Çağlar Kıvanç Kaymaz, and Leman Albayrak. "Analysis of the bioclimatical comfortable conditions of Artvin province and its importance in tourismArtvin ilinin biyoklimatik konfor şartlarının analizi ve turizm bakımından önemi." International Journal of Human Sciences 12, no. 2 (November 10, 2015): 1050. http://dx.doi.org/10.14687/ijhs.v12i2.3361.

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Tourism climatology is a popular field of study that deals with the relationship between tourism and climate through approaches such as applied climatology and human biometeorology. One of the subjects studied most in this field is the evaluation of bioclimatic comfort conditions. In recent years, inferences of this sort have been able to be made easily by use of certain indices. This study aims at evaluating and analyzing the bioclimatic comfort conditions of Artvin province by use of GIS. Within the scope of the research aim, monthly values belonging to SET*, PET, PMV, TCI, THI and SSI indices were calculated by use of meteorological data. SET*, PET, and PMV indices were determined via RayMan 1.2 while TCI, THI, and SSI indices were ascertained through Microsoft Excel 2013 supported analyses of various formulas. The obtained values were analyzed through GIS techniques. Also, statistical methods were utilized to make the research findings more meaningful. All in all, the province was seen to have comfortable conditions. This is because; the comfortable (1) class (68.9%) covers a wider area than uncomfortable (0) class (31.1%) in the province. Bioclimatic comfort classes are shaped by geographical position, elevation, and topography in Artvin province. Valleys with an elevation of less than 2000 m and coastal area are comfortable while mountainous areas (Rize, Kaçkar, Karçal, and Yalnızçam mounts) with a higher elevation are uncomfortable. The results of one-way analysis of variance (one-sample t-test) show that bioclimatic conditions have not been taken into consideration much during the planning of tourism accommodation facilities set up in Artvin province. This study evidences that GIS techniques are efficient in research on tourism climatology or bioclimatology and thus they may be used widely. ÖzetTurizm klimatolojisi, uygulamalı klimatoloji ile insan biyometeorolojisi gibi yaklaşımlarla turizm ve iklim arasındaki ilişkiyi inceleyen popüler bir çalışma sahasıdır. Bu sahada çalışılan öncelikli konulardan birisi de biyoklimatik konfor şartlarının değerlendirilmesidir. Son yıllarda bu tür çıkarımlar CBS (Coğrafi Bilgi Sistemleri) destekli olarak bazı indisler yardımıyla kolayca yapılabilmektedir. Bu çalışmada CBS kullanılarak Artvin ilinin biyoklimatik konfor şartlarının değerlendirilmesi ve analizinin yapılması amaçlanmıştır. Çalışma amacı kapsamında meteorolojik veriler kullanılarak SET*, PET, PMV, TCI, THI ve SSI indislerine ait aylık değerler hesaplanmıştır. SET*, PET ve PMV RayMan 1.2 yazılımı, TCI, THI ve SSI ise çeşitli formüllerin Microsoft Excel 2013 destekli çözümlenmesiyle saptanmıştır. Ulaşılan değerler CBS teknikleriyle analiz edilmiştir. Ayrıca çalışma bulgularını daha anlamlı kılmak amacıyla istatistiksel analiz yöntemlerinden de faydalanılmıştır. Sonuçta ilin konforlu şartlar taşıdığı saptanmıştır. Zira ilde konforlu (1) sınıf (% 68,9) konforsuz (0) sınıfa (% 31,1) oranla daha fazla alan kaplamaktadır. Diğer yandan ildeki biyoklimatik konfor sınıflarının coğrafi konum, yükseklik ve topoğrafik şartlara göre şekillendiği tespit edilmiştir. Bu bağlamda 2000 m yükselti basamağının altındaki vadiler ile kıyı sahası konforlu, üzerindeki dağlık kesimler (Rize, Kaçkar, Karçal ve Yalnızçam dağları) ise konforsuz özelliklere sahiptir. Ayrıca tek yönlü varyans analizi (tek örneklem t-testi) sonuçlarına göre Artvin ilinde yapılmış turizm konaklama tesislerinin planlamalarında biyoklimatik koşulların çok fazla dikkate alınmadığı da belirlenmiştir. Bu çalışma sayesinde turizm klimatolojisine veya biyoklimatolojiye yönelik araştırmalarda CBS tekniklerinin verimli olduğu ve yaygın bir şekilde kullanılabileceğini bir kez daha somut olarak anlaşılmıştır.

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Hwang, Yun, Hyung Kim, and Cheon Yu. "The Empirical Test on the Impact of Climate Volatility on Tourism Demand: A Case of Japanese Tourists Visiting Korea." Sustainability 10, no. 10 (October 6, 2018): 3569. http://dx.doi.org/10.3390/su10103569.

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As climate is not only a valuable tourism resource but also a factor influencing travel experience, estimating climate volatility has implications for sustainable development of the tourism industry. This study develops the Climate Volatility Index (CVI) using a Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model and estimates the relationship between CVI and Japanese tourism demand in Korea, using a tourism demand model based on monthly data from January 2000 to December 2013. Possible time lags and multicollinearity among variables are considered for the model specification. The results show that an increase in climate volatility leads to a decrease in tourism demand.

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Kim, Sang-Tae, Kwang-Min Yoo, Hyun-Jung Kim, and Nam-Jo Kim. "Effect of Climate on the Number of Visitors to National Parks Using Korea Tourism Climate Index." Journal of Tourism and Leisure Research 31, no. 5 (May 31, 2019): 5–19. http://dx.doi.org/10.31336/jtlr.2019.5.31.5.5.

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Yu, Gongmei, Zvi Schwartz, and John E. Walsh. "A weather-resolving index for assessing the impact of climate change on tourism related climate resources." Climatic Change 95, no. 3-4 (April 10, 2009): 551–73. http://dx.doi.org/10.1007/s10584-009-9565-7.

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Ying, Zhang. "Analysis and Evaluation of Tourism Climate Resources in Turpan Region." Advanced Materials Research 869-870 (December 2013): 80–83. http://dx.doi.org/10.4028/www.scientific.net/amr.869-870.80.

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The article analyzes Turpan average temperature, relative humidity and wind speed the change characteristics of the climate elements and their travel to the comfort of climate influence mechanism and gets the conclusion: temperature, relative humidity, wind speed of Xinjiang tourism is the effect of climate comfort of main elements of sunshine. So from the average temperature, relative humidity, wind speed on average three climate elements start, select the suitable for Turpan tourism climate comfort evaluation index of the grain, and puts forward some concrete methods of tourism scenic area as part of the site, focus on the discussion were in Xinjiang tourism climate comfort of the temporal and spatial distribution of feature, make pleasant climate degrees in time and space more comparability. For the development of tourism resources, tourist season choice more objective and scientific guidance and practical. For the comfort of the climate in Turpan, it can arrange for the tour operator for tourism activities, visitors to choose the proper place and time travel and tourism destination development planning to provide the necessary guidance. It can also for the further development of the tourism industry in Turpan development space and offer scientific basis.

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Roshan, Gholamreza, Robabe Yousefi, and Jennifer M. Fitchett. "Long-term trends in tourism climate index scores for 40 stations across Iran: the role of climate change and influence on tourism sustainability." International Journal of Biometeorology 60, no. 1 (May 9, 2015): 33–52. http://dx.doi.org/10.1007/s00484-015-1003-0.

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Alahacoon, Niranga, Mahesh Edirisinghe, and Manjula Ranagalage. "Satellite-Based Meteorological and Agricultural Drought Monitoring for Agricultural Sustainability in Sri Lanka." Sustainability 13, no. 6 (March 19, 2021): 3427. http://dx.doi.org/10.3390/su13063427.

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For Sri Lanka, as an agricultural country, a methodical drought monitoring mechanism, including spatial and temporal variations, may significantly contribute to its agricultural sustainability. Investigating long-term meteorological and agricultural drought occurrences in Sri Lanka and assessing drought hazard at the district level are the main objectives of the study. Standardized Precipitation Index (SPI), Rainfall Anomaly Index (RAI), and Vegetation Health Index (VHI) were used as drought indicators to investigate the spatial and temporal distribution of agriculture and meteorological droughts. Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data from 1989 to 2019 was used to calculate SPI and RAI. MOD13A1 and MOD11A2 data from Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 to 2019, were used to generate the Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). Agricultural drought monitoring was done using VHI and generated using the spatial integration of VCI and TCI. Thus, various spatial data analysis techniques were extensively employed for vector and raster data integration and analysis. A methodology has been developed for the drought declaration of the country using the VHI-derived drought area percentage. Accordingly, for a particular year, if the country-wide annual extreme and severe drought area percentage based on VHI drought classes is ≥30%, it can be declared as a drought year. Moreover, administrative districts of Sri Lanka were classified into four hazard classes, No drought, Low drought, Moderate drought, and High drought, using the natural-beak classification scheme for both agricultural and meteorological droughts. The findings of this study can be used effectively by the relevant decision-makers for drought risk management (DRM), resilience, sustainable agriculture, and policymaking.

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Zang, Yaqiong, Junhu Dai, Zexing Tao, Huanjiong Wang, and Quansheng Ge. "Effects of Climate Change on the Season of Botanical Tourism: A Case Study in Beijing." Advances in Meteorology 2020 (July 17, 2020): 1–11. http://dx.doi.org/10.1155/2020/8527860.

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Climate change could affect botanical tourism by altering the plant phenology (e.g., flowering and leaf coloring date) and the physical comfort of tourists. To date, few studies have simultaneously considered the influence of plant phenology and physical comfort on the travel suitability of botanical tourism. Taking Beijing as an example, this study used phenological data of 73 species from 1963 to 2017 to construct a phenological ornamental index (POI) according to the flowering and leaf coloring date of ornamental plant. The climate comfort index (CCI) of tourism was calculated by using meteorological data of the corresponding periods. Finally, the travel suitability index (TSI) was constructed by integrating the two indices (POI and CCI). The POI showed that the best period for spring flower viewing was from April 4 to May 10, while the best period for autumn leaves viewing was from October 11 to November 6 on average. According to the variation of the CCI within the year, the most comfortable period for spring tourism was matched with the best period for spring flower viewing (April 4 to June 1), but the most comfortable period for autumn tourism (September 4 to October 19) was earlier than the best period for autumn leaves viewing. The TSI indicated that the best periods for spring and autumn botanical tourism were April 7 to May 10 and October 10 to November 7, respectively. Based on the climate data under different scenarios (representative concentration pathways 4.5 and 8.5), we simulated the climate and phenological suitability for botanical tourism in the next thirty years. The results showed that the best period for spring botanical tourism during 2040–2050 was earlier and the period for autumn botanical tourism was later than that in the past 55 years. Meanwhile, the duration would shorten by 2–7 days for both seasons. This study provided a reference for assessing the impact of global climate change on the best season of botanical tourism.

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KUBOKAWA, Hiroyasu, Tsuyoshi INOUE, and Masaki SATOH. "Evaluation of the Tourism Climate Index over Japan in a Future Climate Using a Statistical Downscaling Method." Journal of the Meteorological Society of Japan. Ser. II 92, no. 1 (2014): 37–54. http://dx.doi.org/10.2151/jmsj.2014-103.

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Soler, Ismael P., German Gemar, and Marisol B. Correia. "The climate index-length of stay nexus." Journal of Sustainable Tourism 28, no. 9 (March 2, 2020): 1272–89. http://dx.doi.org/10.1080/09669582.2020.1734603.

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Ghafourizade, Mohammad, Mohammed Saligheh, and Mohammed Hossein Nasserzadeh. "Climatic Comfort Potentials in the View of Tourism in Ilam Province Using Equivalent Temperature Index (ETI) and Discomfort Index (DI)." Journal of Social Sciences Research, no. 511 (November 2, 2019): 1530–38. http://dx.doi.org/10.32861/jssr.511.1530.1538.

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The purpose of present research is to assess Ilam provincial climate in the view of tourism using Equivalent Temperature Index Discomfort Index. In this regard, it was used dataset of National Meteorology Organization and statistics of General planning and management Department, Ilam provincial stations (& stations) from the date of their opening to the end of 2016. Then, collected data were considered by two respective indices. Discomfort Index will calculate the rate of human discomfort in relation to thermal factor using air temperature, relative humidity (RH) and wind rate. Equivalent Temperature Index will assess common effects of temperature on living organism in relation to air temperature and evaporation. Results obtained from Ilam provincial tourism climate by means of Equivalent Temperature Index showed that the lowest and highest annual scores were related to Ilam and Dehloran cities, respectively. Results of Discomfort Index (DI) showed that the lowest and highest DI scores related to Ilam city in January and Dehloran city in July were 614 and 28.8, respectively. Based on obtained results, Ilam province had two different spatial and temporal spans for tourism. Tow that, in regard to tourist attraction, if northern region has optimal conditions in one season, at the same time, there is no optimal conditions in southern regions.

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Lopez, Carlos, and Valentina Davydova. "Tourism Climate Index in Puerto Vallarta as a useful tool in the prevention of diseases related to climate." ISEE Conference Abstracts 2013, no. 1 (September 19, 2013): 3526. http://dx.doi.org/10.1289/isee.2013.p-1-12-32.

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Qu, Carolyn, Xianjun Hao, and John J. Qu. "Monitoring Extreme Agricultural Drought over the Horn of Africa (HOA) Using Remote Sensing Measurements." Remote Sensing 11, no. 8 (April 13, 2019): 902. http://dx.doi.org/10.3390/rs11080902.

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The Horn of Africa ((HOA), including Djibouti, Eritrea, Ethiopia, and Somalia) has been slammed by extreme drought within the past years, and has become one of the most food-insecure regions in the world. Millions of people in the HOA are undernourished and are at risk of famine. Meanwhile, global climate change continues to cause more extreme weather and climate events, such as drought and heat waves, which have significant impacts on crop production and food security. This study aimed to investigate extreme drought in the Horn of Africa region, using satellite remote sensing data products from the Moderate Resolution Imaging Spectroradiometer (MODIS), a key instrument onboard the National Aeronautics and Space Administration (NASA) satellites Terra and Aqua, as well as Tropical Rainfall Measuring Mission (TRMM) precipitation data products. Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI) data from 2000 to 2017 were derived from the MODIS measurements and analyzed for assessments of the temporal trend of vegetation health and the impacts of extreme drought events. The results demonstrated the severity of vegetation stress and extreme drought during the past decades. From 1998 to 2017, monthly precipitation over major crop growth seasons decreased significantly. From 2001 to 2017, the mean VHI anomaly of HOA cropland decreased significantly, at a trend of −0.2364 ± 0.1446/year, and the mean TCI anomaly decreased at a trend of −0.2315 ± 0.2009/year. This indicated a deterioration of cropland due to drought conditions in the HOA. During most of the crop growth seasons in 2015 and 2016, the VHI values were below the 10-year (2001–2010) average: This was caused by extreme drought during the 2015–2016 El Niño event, one of the strongest El Niño events in recorded history. In addition, monthly VHI anomalies demonstrated a high correlation with monthly rainfall anomalies in July and August (the growth season of major crops in the HOA), and the trough points of the monthly rainfall and VHI anomaly time series of July and August were consistent with the timing of drought events and El Niño events.

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Journal articles on the topic 'Climate Index for Tourism (TCI)'

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