Analysis of Urban Heat Island Effect in Wuhan Urban Area Based on Prediction of Urban Underlying Surface Coverage Type Change

IF 2.1 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Advances in Meteorology Pub Date : 2024-04-22 DOI:10.1155/2024/4509221
Wanyi Zuo, Zhigang Ren, Xiaofang Shan, Zeng Zhou, Qinli Deng
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Abstract

The rapid development of urbanization makes the phenomenon of urban heat islands even more serious. Predicting the impact of land cover change on urban heat island has become one of the research hotspots. Taking Wuhan, China, as an example, this study simulated the land type change in 2020 through the Cellular Automata-Markov-Chain (CA-Markov) model. The urban heat island in 2020 was simulated and analyzed in conjunction with the Weather Research & Forecasting Model (WRF), and the simulation results of wind velocity and temperature were confirmed using weather station observation data. Based on this, the land cover and urban heat island of Wuhan in 2030 were predicted. The temperature was found to be well-fit by CA-Markov simulated land use data, with an average inaccuracy of about 2.5°C for weather stations. Wind speed had a poor fitting effect; the average error was roughly 2 m/s. The built-up area was the center of the high temperature area both before and after the prediction, the water was the low temperature area, and the peak heat island happened at night. According to the forecast results, there will be more built-up land in 2030, and there will be a greater intensity of heat islands than in 2020.
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基于城市下垫面覆盖类型变化预测的武汉城市地区热岛效应分析
城市化的快速发展使得城市热岛现象更加严重。预测土地覆被变化对城市热岛的影响已成为研究热点之一。本研究以中国武汉为例,通过细胞自动机-马尔可夫链(CA-Markov-Chain)模型模拟了 2020 年的土地类型变化。结合天气研究与预报模型(WRF)对 2020 年的城市热岛进行了模拟分析,并利用气象站观测数据对风速和温度的模拟结果进行了确认。在此基础上,预测了 2030 年武汉的土地覆被和城市热岛。通过 CA-Markov 模拟的土地利用数据发现,温度的拟合效果较好,气象站的平均误差约为 2.5°C。风速的拟合效果较差,平均误差约为 2 米/秒。预测前后,建成区均为高温区中心,水面为低温区,热岛峰值出现在夜间。根据预测结果,2030 年的建成区将比 2020 年更多,热岛强度将更大。
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来源期刊
Advances in Meteorology
Advances in Meteorology 地学天文-气象与大气科学
CiteScore
5.30
自引率
3.40%
发文量
80
审稿时长
>12 weeks
期刊介绍: Advances in Meteorology is a peer-reviewed, Open Access journal that publishes original research articles as well as review articles in all areas of meteorology and climatology. Topics covered include, but are not limited to, forecasting techniques and applications, meteorological modeling, data analysis, atmospheric chemistry and physics, climate change, satellite meteorology, marine meteorology, and forest meteorology.
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