Change in extreme temperature event frequency over mainland China, 1961−2008

Abstract

Based on homogeneity-adjusted daily temperature data from national stations, the spatial and temporal change in extreme temperature events in mainland China have been analyzed for the period 1961−2008. The analysis shows that the numbers of frost days and ice days were significantly reduced, with the most significant reduction generally in northern China for ice days but more extensively across the country for frost days. Summer days and tropical nights significantly increased along the middle and lower reaches of the Yangtze River and in southern Southwest China.The maximum values of T max (TXx) and T min (TNx) and the minimum values of T max (TXn) and T min (TNn) generally rose, and TXx and TNx significantly increased in northern China, while TXn and TNn significantly increased across the whole country. A significant reduction at a rate of −8. ) occurred for warm nights (days). The reduction of cool nights and cool days occurred mainly in winter, but the increase of warm days and warm nights occurred mostly in autumn and summer. Extreme cold indices were reduced, mainly after the mid-1980s, while extreme warm indices increased remarkably after the mid-1990s. The analysis also shows that, for North China, the urbanization effect on the series of extreme temperature indices was statistically significant for the negative trends of frost days, diurnal temperature range, cool nights and cool days, and for the positive trends of summer days, tropical nights, TNx, TNn, and warm nights.

Tempo-spatial characteristics of sub-daily temperature trends in mainland China

“…These generally showed more significant warming at night than by day in terms of larger changes in minimum temperature than in maximum temperature (Zhai and Pan 2003;Qian and Lin 2004;Zhou and Ren 2011;You et al 2012), leading to large decreases in DTR, cold nights frequency and frost days (Yan et al 2002;Gong and Han 2004;Alexander et al 2006;Choi et al 2009;Zhang et al 2011b), and more significant warming in winter over northern China (Ren et al 2005a(Ren et al , b, 2012Ding et al 2006). Our analysis indicates, however, that the temperature change patterns over mainland China since the 1990s have been substantially different, with a marked slowdown of nighttime warming and an accelerated increase of daytime temperature.…”

On trend estimation and significance testing for non-Gaussian and serially dependent data: quantifying the urbanization effect on trends in hot extremes in the megacity of Shanghai

“…For the OLS trend, these two calculations are the same; but for the WS2001 and EEMD trend, they are different, as will be shown later in this study. The urbanization contribution (C u ) is defined as the proportion that the urbanization effect accounts for the trends in the temperature series at Xujiahui station (T u ), which is the same as in Ren et al (2008), Zhou and Ren (2011), and Ren and Zhou (2014). The detailed formulas are as follows:…”

“…For the linear trend estimation itself, the ordinary least squares fit can give a substantially biased estimation of the urbanization contribution for some of the non-Gaussian extreme indices. temperature extremes can be even greater (Zhou and Ren 2011); for example, around 48 % of the annual warm nights increasing trend was estimated to derive from urbanization. Quantifying the urbanization effect on trends in climate extremes and adjusting this urbanization bias in China are therefore important for the detection and attribution of other human influences, such as greenhouse gas forcing, on trends in climate extremes or on the risks of an extreme event.…”

Effect of data homogenization on estimate of temperature trend: a case of Huairou station in Beijing Municipality

“…One is the understanding of the different trends of Tmin and Tmax in continents. The "asymmetry" in increases of Tmin and Tmax series and the resulting decline of the Diurnal Temperature Range (DTR) were reported for many regions (e.g., Karl et al 1993;Xie and Cao 1996;Zhai and Pan 2003;Qian and Lin 2004;Choi et al 2009;Zhou and Ren 2011). The changes were related to the increase in cloud coverage and precipitation worldwide and aerosols over some regions (Dai et al 1999;Easterling et al 2000).…”