scholarly journals Climate Comfort Analysis for Tourism in Samosir District

2019 ◽  
Vol 94 ◽  
pp. 05001
Author(s):  
Adhityo Haryadi ◽  
Eko Kusratmoko ◽  
Asep Karsidi
Keyword(s):  
Climatic Conditions ◽  
Climate Index ◽  
Tourist Destinations ◽  
Lake Region ◽  
Tourism Climate Index ◽  
Tourism Activity ◽  
Tourism Potential ◽  
Tourism Climate ◽  
North Sumatra ◽  
Climate Comfort

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.

scholarly journals Investigation of climate change impacts on tourism climate comfort in Iran

2018 ◽  
Vol 20 (2) ◽  
pp. 291-303 ◽  
Keyword(s):  
Climate Change ◽  
Linear Regression ◽  
Spatial Resolution ◽  
Climate Change Impacts ◽  
Climate Index ◽  
Covered Area ◽  
Non Linear ◽  
Tourism Climate Index ◽  
Tourism Climate ◽  
Climate Comfort

In this study, Mieczkowski's Tourism Climate Index (TCI) was used for Iran to investigate the climate change impacts on outdoor human comfort. The long-term data covering a network of 153 stations were used to compute TCI under baseline conditions (1981–2015) and a climate change scenario (HadCM3-A1B) for 2016-2045. In this study LARS-WG was used for downscaling of large spatial resolution GCM outputs to a finer spatial resolution. User-friendly and multi-platform software which is called ITCIC (Iran Tourism Climate Index Calculator) was designed to calculate TCI. The spatial distribution of TCI for baseline and climate change conditions was investigated and the covered area by each TCI class was calculated by using ArcGIS 10. The annual distributions of TCI were investigated based on Scott and McBoyle (2001) Models. Also, a suite of multiple linear and non-linear regression models was used to determine the relationship between TCI, latitudes, longitudes and elevations of regions. Root mean square error (RMSE), mean error (ME), mean absolute relative error (MARE) and coefficient of determination (R2) were used to evaluate the modeling accuracy. The best time and regions for outdoor activities in the base and future periods were determined. Comparison of the covered area by each TCI class in the base and future periods showed that the climate change occurrence was led to improving climate comfort. The results of error evaluation criteria showed that non-linear regression was appropriate for all month except January and October.

Assessment climate resource of Con Dao island (Vietnam) by using the tourism climate index

2021 ◽  
Vol 66 (1) ◽  
pp. 188-197
Author(s):  
Oanh Hoang Thi Kieu
Keyword(s):  
Rainy Season ◽  
High Speed ◽  
Climatic Conditions ◽  
Climate Index ◽  
Climatic Index ◽  
Average Temperature ◽  
Tourism Climate Index ◽  
Tourism Climate ◽  
Climatic Elements

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.

scholarly journals An evaluation of changes in the bioclimate of Łódź in the light of the tourism climate index

Turyzm ◽  
2017 ◽  
Vol 25 (2) ◽  
pp. 21-25
Author(s):  
Mariusz Siedlecki
Keyword(s):  
Meteorological Parameters ◽  
Climatic Conditions ◽  
Summer Season ◽  
Climate Index ◽  
Weather Station ◽  
Basic Information ◽  
Tourism Climate Index ◽  
Comprehensive Manner ◽  
Bioclimatic Conditions ◽  
Tourism Climate

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.

scholarly journals ANALISIS INDEKS KENYAMANAN IKLIM (Studi Kasus: Taman Wisata Jatim Park 2 dan Karangkates)

2019 ◽  
Author(s):  
RIDWAN FAIZAL ASEP KURNIA
Keyword(s):  
Climate Index ◽  
Climate Condition ◽  
Economic Sectors ◽  
High Rainfall ◽  
Tropical Area ◽  
Tourism Sector ◽  
Tourism Climate Index ◽  
Humidity Index ◽  
Tourism Activity ◽  
Tourism Climate

Tourism sector is one of the main economic sectors in many countries including Indonesia. Climate comfortability is one of key element that should be considered at tourist destination as climate condition can determine tourism activity. This research is proposed to analyze the comfortability level of Jatim Park 2 and Karangkates Park based on three comfortability indexes, namely: Tourism Climate Index (TCI), Holiday Climate Index (HCI) and Temperature Humidity Index (THI). The analysis is specifically emphasized to evaluate the sensitivity of each method. The results based on TCI and HCI showed that Jatim Park 2 is more comfort than Karangkates Park. Meanwhile, the THI showed that both parks can be classified into good climate comfortability. Seasonally, the HCI showed that comfortable climate condition in the study area occurs in dry season. The sensitivity test for HCI and TCI suggested that HCI is considered better to be applied in the tropical area which has relatively high rainfall and temperature. While, TCI is sensitive to the application of determined rainfall rating. Thus, the TCI should be carefully applied for a region which has relatively high rainfall and temperature, and the rainfall rating may need to be adjusted accordingly.

scholarly journals The Suitability of Moldova Climate for Balneary - Climatic Tourism and Outdoor Activities - A Study Based on the Tourism Climate Index

2018 ◽  
Vol 12 (1) ◽  
pp. 263-282 ◽  
Author(s):  
Dumitru Mihăilă ◽  
Petruț Ionel Bistricean
Keyword(s):  
Temporal Analysis ◽  
Climate Index ◽  
Time Intervals ◽  
Spatial And Temporal Analysis ◽  
Tourism Climate Index ◽  
Tourism Potential ◽  
Tourism Climate ◽  
Comparison Of The Results ◽  
Source Of Information ◽  
A Current

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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