Change in temperature extremes and its correlation with mean temperature in mainland China from 1960 to 2015

Abstract

Changes in temperature extremes can be linked to mean temperature changes and variability. This study aims to quantify observed trends in mean and extreme temperature values and to analyse the relationship between mean and extreme temperatures in mainland China, based on daily data from 1960 to 2015. This is the first analysis undertaken of the relationship between mean and extreme temperatures in mainland China. Based on the 95th and 99th percentiles of daily T max and the 5th and 1st percentiles of daily T min , warm days (TX95p), hot days (TX99p), cold nights (TN05p), and very cold nights (TN01p) were defined. The results showed the following: (1) large increasing tendencies of TX95p and TX99p nearly all occurred in locations where mean temperature had substantially increased, and large decreasing tendencies of TN05p were more probably at locations of warming in mainland China; (2) the rise of mean temperature significantly increased the frequency of TX95p and TX99p, and decreased the frequency of TN05p, which indicates a simple shift of the entire distribution towards a warmer climate and greater potential risk of heat waves in the future. The likelihood of occurrence of TX95p and TX99p increased by about 3 and 1 day, respectively, and the occurrence of TN05p was reduced by about 4 days with a mean temperature increase of 1 ∘ C, but the occurrence of TN01p was hardly affected, indicating increased variability of T min temperatures; and (3) the mean and extreme temperatures increased with the urbanization rate in China, and advanced phenologies and unaffected frequency of very cold nights (TN01p) could pose more potential risk of frost and freeze injury to crops in China in the future.

Evaluation of Historical CMIP6 Model Simulations of Seasonal Mean Temperature over Pakistan during 1970–2014

“…The significant cold extremes are warming faster than the warm extremes, over higher latitudes, and altitudes under polar amplification and snow-albedo feedback processes; land surface extremes warm faster than air temperature for the same period [18]. According to [12,[19][20][21], the mean temperature manifests the average change and trends in extremes of temperature, i.e., Tmax and Tmin. This link can be useful in understanding and predicting future trends of extreme weather events.…”

Modeling the Impacts of Urbanization on Summer Thermal Comfort: The Role of Urban Land Use and Anthropogenic Heat

“…Concurrent with this urban warming is an increase in extreme heat events across China, especially in recent decades (Chen & Li, 2017;Chen & Zhai, 2017;Fang et al, 2017;Ding et al, 2010;Wang et al, 2012). The 2013 summer was the hottest on record in east China, especially in the Yangtze River Delta (YRD; Sun et al, 2014).…”

Sunshine Duration Variability in Haihe River Basin, China, during 1966–2015

“…In this way, the greenhouse effect becomes stronger, resulting in a further increase in temperature. Additionally, urbanization processes in this area enhance the rise in temperatures [35,36]. Thus, though the annual mean temperature in the Haihe River basin is on the rise, the sunshine duration is decreasing.…”

“…Haihe River basin is located in Northern China (112-120 • E and [35][36][37][38][39][40][41][42][43] • N), including Beijing City, Tianjin City, most of Hebei province, northern Shandong province and Henan province, and a small part of Inner Mongolia and Liaoning province. It is bordered by the Bohai Sea in the east, the Yellow River in the south, the Shanxi plateau in the west and the Mongolia plateau in the north.…”