Study on the Changes of Extreme Temperature in the Southwest of Zhejiang Province during the Period of 1953-2022

Under the background of global warming, extreme temperature occurs frequently around the globe, which has a significant and direct impact on social and economic system. Liuchun Lake is an important ecotourism scenic region in Longyou in the southwest of Zhejiang province, it is very important for the local economic development. Based on the daily mean temperature, maximum and minimum temperature from 15 stations, the 13 extreme temperature indices as defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) were calculated, and the characteristics of extreme temperature in the southwest of Zhejiang province were analyzed. The results showed that: 1) The Warmest day (TXx) and Warmest night (TNx) increased at most of the stations, while the coldest day (TXn) and the coldest night (TNn) basically significantly increased at all the stations;2) The number of frost days (FD0) showed decreased trend, and all the stations passed the 99% significant level, the number of ice days (ID0) also was on downward trend, but it is not significant at all most of the stations, however, both the number of summer days (SU25) and tropical nights (TR20) were on upward trend, and all the stations passed the significant level (p < 0.1);3) Both the number of cold days (TX10P) and cold nights (TN10P) showed a declined trend, while the number of warm days (TX90P) and warm night (TN90P) had an upward trend, especially TN90P had significant increase at all the stations. This implies that the cold events declined and warm events increased in the southwest regions of Zhejiang from 1953 to 2022.

Comparison of Daily Extreme Temperatures over Eastern China and South Korea between 1996–2005

This paper examined the decadal mean, seasonal cycle, and interannual variations of mean and extreme temperatures using daily temperature and relative humidity data from 589 stations over eastern China and South Korea between 1996-2005. The results show that the decadal mean Tm （mean daily mean temperature） and the TNn （minimum daily minimum temperature） increase from north to south; the opposite spatial gradient is found in the DTR （diurnal temperature range）; the value of the DTR over South Korea is in- between that over North China and the mid-low Yangtze River valley; the TXx （maximum daily maximum temperature） has a unique spatial distribution, with the largest value over eastern China. The highest standard deviation （STD） is located over northern China and the TNn has the largest area coverage of the high STD. The peak of the seasonal cycle for the Tm, TXx and TNn over South Korea （August） occurs one month later than that over eastern China （July）. The seasonal cycle of the DTR has two peaks （April and October）; the value in the middle-lower reaches of the Yangtze River valley is larger than that in South Korea during July and August owing to the seasonal northward jump of the major monsoon rain band. The interannual variations of summertime temperature indices including the Tin, TXx, and DTR over South Korea are consistent （opposite） to that over northern （southern） China. For the wintertime temperature indices however, the variation over South Korea is consistent with that over eastern China.

Quantile Trends in Temperature Extremes in China

A number of recent studies have examined trends in extreme temperature indices using a linear regression model based on ordinary least-squares. In this study, quantile regression was, for the first time, applied to examine the trends not only in the mean but also in all parts of the distribution of several extreme temperature indices in China for the period 1960–2008. For China as a whole, the slopes in almost all the quantiles of the distribution showed a notable increase in the numbers of warm days and warm nights, and a significant decrease in the number of cool nights. These changes became much faster as the quantile increased. However, although the number of cool days exhibited a significant decrease in the mean trend estimated by classical linear regression, there was no obvious trend in the upper and lower quantiles. This finding suggests that examining the trends in different parts of the distribution of the time-series is of great importance. The spatial distribution of the trend in the 90 th quantile indicated that there was a pronounced increase in the numbers of warm days and warm nights, and a decrease in the number of cool nights for most of China, but especially in the northern and western parts of China, while there was no significant change for the number of cool days at almost all the stations.

Statistical Downscaling of Summer Temperature Extremes in Northern China

Two approaches of statistical downscaling were applied to indices of temperature extremes based on percentiles of daily maximum and minimum temperature observations at Beijing station in summer during 1960-2008. One was to downscale daily maximum and minimum temperatures by using EOF analysis and stepwise linear regression at first, then to calculate the indices of extremes; the other was to directly downseale the percentile-based indices by using seasonal large-scale temperature and geo-potential height records. The cross-validation results showed that the latter approach has a better performance than the former. Then, the latter approach was applied to 48 meteorological stations in northern China. The cross- validation results for all 48 stations showed close correlation between the percentile-based indices and the seasonal large-scale variables. Finally, future scenarios of indices of temperature extremes in northern China were projected by applying the statistical downsealing to Hadley Centre Coupled Model Version 3 （HadCM3） simulations under the Representative Concentration Pathways 4.5 （RCP 4.5） scenario of the Fifth Coupled Model Inter-comparison Project （CMIP5）. The results showed that the 90th percentile of daily maximum temperatures will increase by about 1.5℃, and the 10th of daily minimum temperatures will increase by about 2℃ during the period 2011- 35 relative to 1980-99.

Influences of the 11-yr Sunspot Cycle and Polar Vortex Oscillation on Observed Winter Temperature Variations in China

Using the NCEP-2 reanalysis data in 1979-2015, we analyze variations in the coupled stratosphere-troposphere system and attribute them to the polar vortex oscillation(PVO) and the 11-yr sunspot cycle(SC). Subsequently, influences of PVO and SC on the near-ground temperature and extreme temperatures are diagnosed based on observations at 2419 surface stations in China over the same period. Empirical Orthogonal Function(EOF) analysis of geopotential height(GH) anomalies indicates that the first and second EOF modes together can explain nearly 50% of the total variance and they have different driving sources, active periods, and regions. The first EOF mode mainly represents variation characteristics of the polar vortex, and its active periods appear in late winter. It is found that a weakened polar vortex(larger amplitude in the positive time series of the first mode) corresponds to lower daily mean, minimum, and maximum temperatures and more frequent cold nights and days. This cooling effect mainly occur in northeastern China. The second EOF mode is closely related to the SC, and its major active periods are late autumn and early winter. The results reveal that strong solar activity(larger amplitude in the positive time series of the second mode) leads to cooling effects in northern China through accelerating seasonal transformation of the stratospheric circulation and enhancing intensity of the subtropical westerly jet in the upper troposphere and lower stratosphere. The near-ground temperature is lower than usual, especially for daily mean and minimum temperatures. The number of warm nights and days is significantly reduced, and cold nights and days become more frequent. Therefore,the first and second EOF mode time series of GH anomalies can be used as indices of PVO and solar activity, respectively; and can provide indications of winter cooling processes in China.