Impact of urbanization on extreme temperature events in Sichuan Province of China based on RS and GIS techniques

Jingkun Yang; Xiehui Li; Kaiyi Wu

doi:10.1117/12.2667478

10 February 2023 Impact of urbanization on extreme temperature events in Sichuan Province of China based on RS and GIS techniques

Jingkun Yang, Xiehui Li, Kaiyi Wu

Author Affiliations +

Proceedings Volume 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022); 125520D (2023) https://doi.org/10.1117/12.2667478
Event: International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 2022, Kunming, China

Abstract

By using daily temperatures of 36 meteorological stations from 1980 to 2020 in Sichuan Province, remote sensing data of DMSP (Defense Meteorological Satellite Program) night light and land use, as well as spatial distribution gridded data of GDP (Gross Domestic Product) and population, we calculated 16 ETIs (Extreme Temperature Indices). With the aid of comprehensive methods of K-means and hierarchical clustering, meteorological stations were divided into urban, suburban, and rural stations. The change trends of extreme temperature events and the effects of urbanization in Sichuan Province were analyzed. The results demonstrated that extreme high temperature events showed an overall increasing trend, while extreme low temperature events showed a decreasing trend. DTR (Diurnal temperature range) and GSL (Crop growing season) indices resulted in an overall upward trend. Due to the complex topography and climate diversity, and with the continuous acceleration of urbanization in the past 40 years, extreme high temperature events in urban and suburban stations were significantly higher as compared to rural stations. However, in these stations, the decreasing trend of extreme low temperature events was more significant as compared to the others. In urban and suburban stations, urbanization significantly impacted the change trends of TXx (Max Tmax), TXn (Min Tmax), TNn (Min Tmin), ID0 (Ice days), TR20 (Tropical nights), DTR, and GSL. In addition, the contribution rates of urbanization were all more than 50%, with little impact on the change trends of TNx (Max Tmin), FD0 (Frost days), TN10P (Cool nights), TX10P (Cool days), TN90P (Warm nights), and TX90P (Warm days). Moreover, no effect on SU25 (Summer days), WSDI (Warm spell duration indicator) and CSDI (Cold spell duration indicator) change trends were found.

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Jingkun Yang, Xiehui Li, and Kaiyi Wu "Impact of urbanization on extreme temperature events in Sichuan Province of China based on RS and GIS techniques", Proc. SPIE 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 125520D (10 February 2023); https://doi.org/10.1117/12.2667478

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KEYWORDS

Climatology

Temperature metrology

Remote sensing

Meteorology

Environmental sensing

Climate change

Geographic information systems

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