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Related Experiment Video

Updated: Jul 17, 2026

Façade-Level Monitoring of CO2 Variability under Urban Heat Island Conditions using Low-Cost Sensor Data Loggers

Façade-Level Monitoring of CO₂ Variability under Urban Heat Island Conditions using Low-Cost Sensor Data Loggers

Published on: December 12, 2025

A High-Resolution, Long-Term, Comprehensive Climate Comfort Index Dataset for China (1961-2022).

Qun Liu¹, Lan Lin², Yayan Lu³

¹Fujian Provincial Key Laboratory for Subtropical Resources and Environment, School of Geographical Sciences, Fujian Normal University, Fuzhou, 350117, China.

Scientific Data

|July 15, 2026

Summary

A new comprehensive climate comfort index was developed for China, integrating multiple climate variables over 60 years. This high-resolution dataset aids in understanding climate change impacts on tourism and leisure activities.

Related Experiment Videos

Last Updated: Jul 17, 2026

Façade-Level Monitoring of CO2 Variability under Urban Heat Island Conditions using Low-Cost Sensor Data Loggers

Façade-Level Monitoring of CO₂ Variability under Urban Heat Island Conditions using Low-Cost Sensor Data Loggers

Published on: December 12, 2025

Area of Science:

Environmental Science
Climatology
Tourism Studies

Background:

Existing climate comfort studies often use single meteorological variables, limiting holistic perception.
There's a lack of long-term, high-spatial-resolution comprehensive climate comfort indices for detailed climate variability analysis.

Purpose of the Study:

To develop a long-term, high-spatial-resolution comprehensive climate comfort index for China.
To provide data for assessing climate change effects on human leisure and tourism.

Main Methods:

Utilized monthly gridded meteorological data (0.25°×0.25°) from 1961-2022.
Computed temperature-humidity, wind effect, and clothing indices.
Employed expert scoring, entropy weight, and Bayesian three-cornered hat methods for index generation and uncertainty quantification.

Main Results:

Generated a definitive composite climate comfort index for China spanning over six decades.
The dataset reveals spatial heterogeneity and seasonal dynamics of climate comfort.
Provides a novel resource for climate change impact assessments in tourism.

Conclusions:

The developed index offers a more holistic and detailed measure of climate comfort.
This long-term, high-resolution dataset is crucial for understanding climate change impacts on China's tourism sector.
The findings support data-driven strategies for climate change adaptation in leisure and tourism.