Impacts of Urbanization on Extreme Climate Events in Sichuan-Chongqing Region

Abstract

Based on daily precipitation and temperature data as well as population, gross domestic product (GDP), land use and land cover change (LUCC), night lighting remote sensing data of 46 meteorological stations in Sichuan and Chongqing Region from 1971 to 2020, 21 extreme climate indices are calculated using RClimDex software, and the interannual variation trends of these indices are analyzed using linear trend method. The Mann-Kendall nonparametric method is used to test the significance levels of all indices. These meteorological stations are categorified to further investigate the impact of urbanization on extreme climate indices, especially the impact of urbanization on extreme climate events in Sichuan and Chongqing. It's found that the monthly maximum value of daily maximum temperature (TXx), maximum value of daily minimum temperature (TNx), minimum value of daily maximum temperature (TXn), minimum value of daily minimum temperature (TNn), summer days (SU25), occurrence of hot nights(TR20), warm nights (TN90P) and warm days (TX90P) all show an increasing trend in the last 50 years, while the frost days (FD0), cold nights (TN10P) and cold days (TX10P) show a decreasing trend, and the changes are all significant. The annual total precipitation in wet days (PRCPTOT), very heavy precipitation days (R25mm), very wet days (R95P), extremely wet days (R99P) and simple precipitation intensity index (SDII), which represent the extreme precipitation and the intensity of extreme precipitation, all show an increasing trend, indicating that the extreme high temperature and extreme precipitation in Sichuan and Chongqing Region have been increasing. The extreme indices show an increasing trend in all three types of meteorological sites. The increasing trend of TXx, TNx, TR20, TX90P and daily temperature range (DTR) are most obvious in urban stations, and FD0, TN10P, TX10P and DTR are most obvious in rural stations. Urbanization has basically no effects on TXx and TN90P at rural-urban sites, but has a greater effect on the monthly TXn, TNn, FD0, TR20 and DTR at rural and urban sites, as well as the number of TN10P and TN90P at urban sites. In Sichuan and Chongqing Region, among the rural sites, all indices show a significant increasing trend except for the monthly maximum 1-day precipitation (RX1DAY), monthly maximum 5-day precipitation (RX5DAY) and consecutive wet days (CWD), which show a non-significant decreasing trend. The influence of urbanization causes a decreasing trend in the number of heavy precipitation days (R10mm), R25mm, RX1DAY, RX5DAY, R95P and PRCPTOT in urban-rural and urban sites, and causes an increasing trend in SDII and CWD. The urbanization effects contribute 100.00% to R10mm, RX1DAY, RX5DAY, R95P and PRCPTOT for both urban-rural and urban sites.

Keywords

• extreme temperature index
• extreme precipitation index
• urbanization impact
• contribution rate of urbanization impact