Analysis of climate comfort differences in Guizhou Province based on CCI and OWCI

doi:10.11755/j.issn.1006-7639-2025-03-0385

Abstract

Abstract:

To explore the spatiotemporal evolution of climate comfort in Guizhou Province and support regional tourism development planning, this study utilized daily meteorological data from 77 national stations spanning from 1974 to 2023. Two evaluation models, the comprehensive comfort index (CCI) and the outdoor weather comfort index (OWCI), were employed in combination with the least squares method, Pearson correlation analysis, and Mann-Kendall (M-K) mutation test. The results indicate that both indices effectively capture the spatiotemporal characteristics of climate comfort across Guizhou. The CCI is more effective at reflecting long-term climate variability and incorporates clothing adjustment capacity, making it more suitable for annual-scale assessments. In contrast, the OWCI responds more responsive to environmental meteorological conditions change and performs better at the monthly scale. Climate comfort days showed a significant increase in March and November, and a significant decrease from June to September. The proportion of stations with a significant increasing trend in climate comfort days is highest in March, while the proportion of stations with a significant decreasing trend is highest in July and August. Overall, climate comfort is favorable in southern low-altitude areas from January to March and November to December, in western high-altitude regions from May to September, and across most of the province in April and October.

Key words: Guizhou, CCI, OWCI, climate comfort, temporal and spatial evolution

摘要：

为深入了解贵州省气候舒适度的时空演变特征，并为地方旅游产业发展规划提供科学依据，基于贵州省77个国家气象站1974—2023年逐日气象数据，采用综合舒适指数（Comprehensive Comfort Index，CCI）和室外天气舒适指数（Outdoor Weather Comfort Index，OWCI）评价模型，结合最小二乘法、皮尔逊相关分析与M-K突变检验等方法，分析了贵州省气候舒适日数的时空变化特征及其对环境变化的响应。结果表明，CCI与OWCI两种指数模型具有相似的时空变化特征，均能较好地反映贵州省气候舒适度，其中CCI可以更好地反映通过穿衣调节应对不舒适气候的能力，对年尺度气候变化响应更优，OWCI则对环境气象条件变化响应更迅速，在月尺度上表现更好。在气候变化和环境因素共同作用下，贵州省3月及11月的气候舒适日数显著增加，而6—9月则显著减少，其中3月气候舒适日数呈显著增加趋势的站点占比最高，7—8月呈显著减少趋势的站点最多。总体而言，贵州省1—3月及11—12月南部低海拔地区、5—9月西部高海拔地区、4月及10月大部分地区气候舒适度条件较好。

关键词: 贵州, 综合舒适指数, 室外天气舒适指数, 气候舒适度, 时空演变

CLC Number:

P468

REN Qingfeng, ZHANG Zhengqiang, WU Xinhao, XIE Qiang, AO Qin, LUO Haishun. Analysis of climate comfort differences in Guizhou Province based on CCI and OWCI[J]. Journal of Arid Meteorology, 2025, 43(3): 385-393.

任青峰, 张正强, 吴新豪, 谢强, 敖芹, 骆海顺. 基于CCI与OWCI的贵州省气候舒适度差异分析[J]. 干旱气象, 2025, 43(3): 385-393.

Figures/Tables 10

Fig.1 Distribution of meteorological stations and terrain of Guizhou Province

Fig.2 Multi-year monthly mean (a) and annual mean (b) climate comfortable days boxplots in Guizhou Province from 1974 to 2023

Tab.1 Trend in annual and monthly CCI and OWCI climate comfort days in Guizhou Province from 1974 to 2023 单位：d·(10 a)-1

	CCI	OWCI		CCI	OWCI
1月	0.6	0.1	8月	-0.7**	-0.8*
2月	0.9	0.7	9月	-0.4*	-0.6*
3月	1.0**	1.2**	10月	-0.1	-0.2
4月	0.0	-0.1	11月	0.5*	0.7*
5月	-0.1	-0.2	12月	0.4	-0.5
6月	-0.4*	-0.2	年	2.6**	-0.5
7月	-0.6*	-0.6*

Fig.3 The M-K test of annual CCI (a) and OWCI (b) climate comfort days in Guizhou Province from 1974 to 2023

Fig.4 The M-K test of monthly CCI climate comfort days in Guizhou Province from 1974 to 2023

Fig.5 The M-K test of monthly OWCI climate comfort days in Guizhou Province from 1974 to 2023

Fig.6 Spatial variation (the color shaded, Unit: d) and trends (symbols) of annual mean CCI (a) and OWCI (b) climate comfort days in Guizhou Province from 1974 to 2023

Fig.7 Spatial variation （the color shaded， Unit： d） and trends （symbols） of monthly CCI climate comfort days in Guizhou from 1974 to 2023

Fig.8 Spatial variation （the color shaded， Unit： d） and trends （symbols） of monthly OWCI climate comfort days in Guizhou Province from 1974 to 2023

Tab.2 Correlation coefficients of annual and monthly CCI and OWCI climate comfort days with longitude， latitude and elevation in Guizhou Province from 1974 to 2023

	经度		纬度		海拔高度
	CCI	OWCI	CCI	OWCI	CCI	OWCI
1月	0.115**	-0.069**	-0.273**	-0.409**	-0.393**	-0.120**
2月	0.148**	-0.008	-0.139**	-0.265**	-0.380**	-0.170**
3月	0.204**	0.049**	-0.045**	-0.159**	-0.424**	-0.246**
4月	0.151**	0.208**	0.204**	0.173**	-0.105**	-0.160**
5月	-0.269**	-0.256**	0.209**	0.143**	0.503**	0.490**
6月	-0.597**	-0.563**	-0.012	-0.069**	0.783**	0.752**
7月	-0.724**	-0.707**	-0.270**	-0.293**	0.866**	0.842**
8月	-0.699**	-0.696**	-0.264**	-0.285**	0.845**	0.831**
9月	-0.495**	-0.525**	-0.071**	-0.072**	0.665**	0.678**
10月	-0.008	0.202**	0.079**	0.053**	0.043**	-0.273**
11月	0.293**	0.309**	-0.029	-0.125**	-0.471**	-0.480**
12月	0.276**	0.166**	-0.176**	-0.374**	-0.520**	-0.341**
年	-0.636**	-0.635**	-0.378**	-0.502**	0.591**	0.632**

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