Detection of anthropogenic influence on the intensity of extreme temperatures in China

Abstract

ABSTRACT:The anthropogenic (ANT) influence on the intensity of temperature extremes in China is detected over the period 1958-2012 using the newest homogenized daily observation data set and multi-model simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We applied an optimal fingerprinting method to compare spatial-temporal changes in the intensity of temperature extremes, including annual maxima of daily maximum and daily minimum temperatures (warmest day and night, TXx and TNx) and annual minima of daily maximum and daily minimum temperatures (coldest day and night, TXn and TNn). For China as a whole, the results show that the ANT influence can be robustly detected in all four extreme indices. The ANT signal is also clearly separable from the response to natural-only (NAT) forcing in the two-signal analyses. The NAT signal was detectable for the warmest night TNx but not for other indices. At smaller regional scales for Eastern and Western China, the ANT signals were also clearly detected in the changes of temperature extremes. With the use of more observational data and multi-model simulations, this study updates a previous work and confirms that the human influence can be robustly detected in the changes of extreme temperature intensity in China.

Observed changes in temperature extremes over Asia and their attribution

“…The model-simulated response for TNx appears to be consistent with the observed values across all subregions. Overall, our results support those of previous studies, which demonstrated that models underestimate the changes in TNn and TXn, there is good consistency between the model-simulated and observed values of TNx, and models overestimate the changes in TXx (Zwiers et al 2011;Yin et al 2016;Kim et al 2016). Detection becomes more difficult at low latitudes, perhaps because the region containing available data is too small.…”

“…Donat et al (2014 found increasing number of warm days and nights, higher extreme temperature values, shorter cold spell durations and fewer cold days and nights in the Arab regions since the mid-1950s. Increases in warm extremes and decreases in cold extremes have also been observed in Chinese temperature data (You et al 2008(You et al , 2009Yin et al 2016;Lu et al 2016).…”

“…The Chinese data were homogenized using RHtests (Wang and Feng 2010) in the NMIC (Cao et al 2016). This dataset has been extensively analyzed in several recent studies (Sun et al 2014;Yin et al 2016;Cao et al 2016). The quality and homogeneity of the data from the non-Chinese stations were checked preliminarily at the workshop.…”

“…This is typically accomplished using detection and attribution analysis, in which observations are compared with the simulated responses of climate models to natural and external forcings. Evidence of anthropogenic influence through the emission of greenhouse gases and aerosols, and sometimes evidence of influence from natural external forcings, can be clearly detected in the magnitudes of extreme temperatures, such as the highest annual values of daily maximum and minimum temperatures (TXx and TNx, respectively) and annual lowest daily maximum and minimum temperatures (TXn and TNn, respectively), on both global and regional scales (e.g., Christidis et al 2005;Zwiers et al 2011;Wen et al 2013;Yin et al 2016;Kim et al 2016). In general, climate models can accurately simulate the observed changes in the warmest night-time temperatures, but they underestimate the observed changes in the coldest temperatures (e.g., Kim et al 2016).…”

Anthropogenic Influence on the Eastern China 2016 Super Cold Surge

“…It has decreased due to anthropogenic influence. This is consistent with earlier findings of Yin et al (2016) and Lu et al (2016), who found that cold extremes in China have decreased due to anthropogenic influence. The recent super cold surge of Eastern China that occurred 21-25 January 2016 would have been much stronger if there was no human-induced warming.…”