ArticleInternational journal of biometeorology2021
Development of a data-driven weather index for beach parks tourism.
Article in International journal of biometeorology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Projected climate suitability for Hungarian tourism in the 21st century: application of the Holiday Climate Index and modified Tourism Climate Index.International journal of biometeorology · 2025Article
- Quantifying climatic suitability for tourism in Southwest Indian Ocean Tropical Islands: Applying the Holiday Climate Index to Réunion Island.International journal of biometeorology · 2024Article
- Insights into climate change dynamics: A tourism climate index-based evaluation of Gilgit-Baltistan, Pakistan.Heliyon · 2024Article
- Comparing future climatic suitability to shoreline loss for recreational beach use: a case study of five Japanese beaches.Regional environmental change · 2022Article
- Tourism climatology: past, present, and future.International journal of biometeorology · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The complexity of the human-environment interface predicates the need for tools and techniques that can enable the effective translation of weather and climate products into decision-relevant information. Indices are a category of such tools that may be used to simplify multi-faceted climate information for economic and other decision-making. Climate indices for tourism have been popularized in the literature over the past three decades, but despite their prevalence, these indices have a number of limitations, including coarse temporal resolution, subjective rating and weighting schemes, and lack of empirical validation. This paper critically assesses the design of the tourism climate index, the holiday climate index-beach, and a new, mathematically optimized index developed for the unique contextual realities of Great Lakes beach tourism. This new methodology combines the use of expert knowledge, stated visitor preferences, and mathematical optimization to develop an index that assigns daily weather scores based on four weather sub-indices (thermal comfort, wind speed, precipitation, and cloud cover). These daily scores are then averaged to the monthly level and correlated to visitation data at two beach parks in Ontario (Canada). This optimized index demonstrates a strong fit (R
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Registered trials
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