Abstract

In this study, the instability of extreme temperatures is defined as the degree of perturbation of the spatial and temporal distribution of extreme temperatures, which is to show the uncertainty of the intensity and occurrence of extreme temperatures in China. Based on identifying the extreme temperatures and by analyzing their variability, we refer to the entropy value in the entropy weight method to study the instability of extreme temperatures. The results show that TXx (annual maximum value of daily maximum temperature) and TNn (annual minimum value of daily minimum temperature) in China increased at 0.18 °C/10 year and 0.52 °C/10 year, respectively, from 1966 to 2015. The interannual data of TXx’ occurrence (CTXx) and TNn’ occurrence (CTNn), which are used to identify the timing of extreme temperatures, advance at 0.538 d/10 year and 1.02 d/10 year, respectively. In summary, extreme low-temperature changes are more sensitive to global warming. The results of extreme temperature instability show that the relative instability region of TXx is located in the middle and lower reaches of the Yangtze River basin, and the relative instability region of TNn is concentrated in the Yangtze River, Yellow River, Langtang River source area and parts of Tibet. The relative instability region of CTXx instability is distributed between 105° E and 120° E south of the 30° N latitude line, while the distribution of CTNn instability region is more scattered; the TXx’s instability intensity is higher than TNn’s, and CTXx’s instability intensity is higher than CTNn’s. We further investigate the factors affecting extreme climate instability. We also find that the increase in mean temperature and the change in the intensity of the El Niño phenomenon has significant effects on extreme temperature instability.

Highlights

  • The Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) shows that global surface temperatures are 1.09 [0.95 to 1.20] ◦C warmer in 2011–2020 than in 1850–1900, with a greater increase on land (1.59 [1.34 to 1.83] ◦C) than over the oceans (0.88 [0.68 to 1.01] ◦C), according to paleoclimate data, global surface temperatures have increased faster since 1970 than in any other 50-year period over at least the last 2000 years [1]

  • The main approaches to the topic include: (1) studies of the mean changes in climate elements based on annual or monthly time scales [7,8,9,10]; (2) studies of the spatial and temporal variability of extreme climate based on the definition of extreme climate indices [11,12,13,14]; (3) studies delineating climate zones based on the spatial and temporal variability of climate elements or extreme climate elements [15,16,17,18]; (4) predicting future climate change based on experimental data from the Coupled Model Comparison Project (CMIP) organized by the World Climate Research Program (WCRP) [19,20,21,22,23]

  • Based on the extreme temperature index calculation using data from 778 meteorological stations, we further investigated the spatial and temporal variation of the extreme climate index and the instability of the extreme temperature index in China from 1966 to 2015

Read more

Summary

Introduction

The Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) shows that global surface temperatures are 1.09 [0.95 to 1.20] ◦C warmer in 2011–2020 than in 1850–1900, with a greater increase on land (1.59 [1.34 to 1.83] ◦C) than over the oceans (0.88 [0.68 to 1.01] ◦C), according to paleoclimate data, global surface temperatures have increased faster (with high confidence) since 1970 than in any other 50-year period over at least the last 2000 years [1]. The main approaches to the topic include: (1) studies of the mean changes in climate elements based on annual or monthly time scales [7,8,9,10]; (2) studies of the spatial and temporal variability of extreme climate based on the definition of extreme climate indices [11,12,13,14]; (3) studies delineating climate zones based on the spatial and temporal variability of climate elements or extreme climate elements [15,16,17,18]; (4) predicting future climate change based on experimental data from the Coupled Model Comparison Project (CMIP) organized by the World Climate Research Program (WCRP) [19,20,21,22,23]. The instability of extreme climate elements on short time scales has considerable importance for socio-economic development. Studies on the instability of extreme temperature elements are often not available

Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call