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气象:2019,45(6):854-861
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影响杭州人体舒适度的城市因素分析
高超,申双和,蒋烨林,彭擎
(南京信息工程大学应用气象学院,南京 210044; 气象灾害预报预警与评估协同创新中心,南京 210044; 广德县气象局,安徽宣城 242200; 江苏省农业气象重点实验室,南京 210044)
Analysis of Urban Factors Impacting Human Comfort Degree in Hangzhou
GAO Chao,SHEN Shuanghe,JIANG Yelin,PENG Qing
(School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing 210044; Guangde Meteorology Station of Anhui Province, Xuancheng 242200; Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing 210044)
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投稿时间:2018-10-03    修订日期:2019-04-25
中文摘要: 城市的热环境与城市因子之间有某种必然的联系,为了研究两者之间的关系,本文以人体舒适度为研究视角,分析影响人体舒适度变化的主要城市因子。该研究首先采用了热气候指数法计算1980—2017年杭州夏季高温不舒适日数,并统计其变化趋势。运用熵权优化的灰色关联度模型,确立各影响因子的权重,分析城市化因子与高温不舒适日数之间的关联关系。结果表明:(1)38年来,杭州高温不舒适日数的平均为30.6 d,气候倾向率为6.87 d·(10 a)-1,呈现显著上升趋势。年代际变化特征表明,高温不舒适日数主要集中在7、8月,并在1992—1993年高温不舒适日数发生由少到多的突变。(2)灰关联熵结果显示,在十二个指标因子中,第二产业占地区生产总值比重所占权重最大,公路客运量所占权重占第二位,所占权重最小的是人口密度。(3)公路客运量和第二产业占地区生产总值比重与高温不舒适日数的关联度均成强度相关联,而园林绿地面积、建成区绿化覆盖面积、人口密度等剩下的十个因子均成中度相关联。综上所述,灰色理论在多因子关联系统预测中具有优越性,能够有效分析影响高温不舒适日数的主要城市因子,在实际应用中具有一定价值。
Abstract:There is a certain necessary connection between urban thermal environment and urban factors. In order to study the connection, this paper analyzes the main urban factors impacting human comfort degree from the perspective of human comfort degree. We adopt the way of thermal climatic index to calculate the uncomfortable days with high temperatures in Hangzhou from 1980 to 2017, and sum the change trend. By means of gray relational analysis of entropy-based optimization, we determine the weights of different factors and analyze the connection between urban factors and uncomfortable days with high temperature. The results are as follows. First, over the past 38 years, the average uncomfortable days with high temperature in Hangzhou are 30.6 d, and the climate tendency rate is 6.87 d·(10 a)-1, showing a significant upward trend. The interdecadal variation changes dramatically. The uncomfortably days with high temperature mostly appear in July and August and notably the uncomfortable days with high temperature appear more frequently from 1992 to 1993. Second, according to the results of gray relational analysis of entropy-based optimization, among 12 index factors, the weight of the occupying areas of secondary industry is the biggest, with highway passenger volume standing the next. Population density accounts for the smallest proportion.Third, highway passenger volume and the weight of occupying areas of secondary areas strongly correlate with days with high temperature, while the other ten factors such as garden area, green coverage area of built-up area, and population density correlate with days with high temperature moderately. In conclusion, gray relational analysis has advantages in the prediction of multiple factor connection. It can effectively analyze the main urban factors impacting days with high temperatures and has some values in application.
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基金项目:公益性行业(气象)科研专项(GYHY201506018)资助
引用文本:
高超,申双和,蒋烨林,彭擎,2019.影响杭州人体舒适度的城市因素分析[J].气象,45(6):854-861.
GAO Chao,SHEN Shuanghe,JIANG Yelin,PENG Qing,2019.Analysis of Urban Factors Impacting Human Comfort Degree in Hangzhou[J].Meteor Mon,45(6):854-861.