Abstract

Recently, NCAR (the National Center for Atmospheric Research) released the Community Earth System Model’s low-warming simulations, which provided long-term climate data for stabilization pathways at 1.5 °C and 2.0 °C above pre-industrial levels. Based on these data, six extreme low temperature indices—TXn (coldest day), TNn (coldest night), TX10p (cool days), TN10p (cool nights), CSDI (cold spell duration indicator), and DTR (diurnal temperature range)—were calculated to assess the changes in extreme low temperature over Northern China under 1.5 °C and 2.0 °C warmer future. The results indicate that compared to the preindustrial level, the whole of China will experience 0.32–0.46 °C higher minimum surface air temperature (SAT) warming than the global average, and the winter temperature increase in Northern China will be the most pronounced over the country. In almost all the regions of Northern China, especially Northeast and Northwest China, extreme low temperature events will occur with lower intensity, frequency, and duration. Compared with the present day, the intensity of low temperature events will decrease most in Northeast China, with TXn increasing by 1.9 °C/2.0 °C and TNn increasing by 2.0 °C/2.5 °C under 1.5 °C/2.0 °C global warming, respectively. The frequency of low temperature events will decrease relatively more in North China, with TX10p decreasing by 8 days/11 days and TN10p decreasing by 7 days/9 days under 1.5 °C/2.0 °C warming. CSDI will decrease most in Northwest China, with decreases of 7 days/10 days with 1.5 °C/2.0 °C warming. DTR will decrease in the Northwest and Northeast but increase in North China, with −0.9 °C/−2.0 °C in the Northwest, −0.4 °C/−1.5 °C in the Northeast, and 1.7 °C/2.0 °C in North China in the 1.5 °C/2.0 °C warming scenarios. For temperatures lower than the 5th percentile, the PRs (probability ratios) will be 0.68 and 0.55 of that of the present day under 1.5 °C and 2.0 °C warmer futures, respectively. Global warming of 2.0 °C instead of 1.5 °C will lead to extreme low temperature events decreasing by 6–56% in regard to intensity, frequency, and duration over Northern China, and the maximal values of decrease (24–56%) will be seen in Northeast China.

Highlights

  • During the past century, the global surface air temperature (SAT) has increased robustly, and anthropogenic forcing is the main cause of this increase [1]

  • Previous studies have shown that the temperature rise in China has been significantly larger than the global average [2], and China is one of the regions in the world most affected by climate change [3]

  • The frequency of extreme low temperature events in Northwest China showed a significant negative response to regional warming, and the response was stronger in Northern Xinjiang, Central and Southeastern Xinjiang, and most areas of Qinghai province [16]

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Summary

Introduction

The global surface air temperature (SAT) has increased robustly, and anthropogenic forcing is the main cause of this increase [1]. In October 2018, the IPCC published this Special Report It is well-known that extreme temperature change has a very close relationship with global warming. The frequency of extreme low temperature events in Northwest China showed a significant negative response to regional warming, and the response was stronger in Northern Xinjiang, Central and Southeastern Xinjiang, and most areas of Qinghai province [16]. We used NCAR Community Earth System Model (CESM) low-warming datasets to investigate the change of extreme low temperatures in Northern China under 1.5 ◦ C and. The changes in extreme low temperature events under 1.5 and 2.0 ◦ C warming over Northern China are discussed, and conclusions and discussions are provided in the last part of this paper The changes in extreme low temperature events under 1.5 and 2.0 ◦ C warming over Northern China are discussed in the third section, and conclusions and discussions are provided in the last part of this paper

Historical Data
Model Projection Data
Extreme Low Temperature Indices
Subregions of Northern China
Bias Correction
Probability Ratio
Avoided Impacts
Evaluation of Historical Simulation
Minimum
Changes
Regional
Regional mean changes changes in in TX10p
C scenario
Conclusions and Discussion
Full Text
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