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Projection the Risk of Winter Extreme Cold Spells in China Based on Statistical Modelling Under Global Warming of 1.5°C and 2.0°C
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DOI：10.1002/joc.70503.png)
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Abstract
En 中文
This study used the observed daily minimum temperature from 1995 to 2014 in China, combined with simulations from 21 models from CMIP6, to define and extract characteristic indicators of cold spells from a process-oriented perspective. A method using probability distribution (Cold Spell Model, CSM) is constructed based on extreme value theory, which can effectively characterise the intensity, frequency and duration of cold spells. Results demonstrate that the intensity of extreme cold spells decreases from north to south across China. Northern China typically experiences low-frequency, longer-duration and extreme cold spells, whereas southern China is characterised by shorter-duration events. A cumulative probability distribution transformation method is applied to correct biases in model simulations, showing that bias correction simulation has better performance over the raw simulations. Based on the corrected projections, the extreme cold spells in China are expected to become shorter, less frequent and generally less intense under future warming, with more pronounced changes under the 2.0°C warming compared to 1.5°C warming. However, notable spatial variations exist: the intensity of cold spells decreases in most eastern regions but increases in western regions. The average annual frequency of cold spells generally declines, with more significant changes observed on the Qinghai-Tibet Plateau. Furthermore, the duration of cold spells shortens significantly across most regions. Future cold spell risks in China will generally decrease across most return periods. However, risks are projected to increase for low-frequency (once per year) and short-duration (1-day) extreme events in certain regions, while risks for high-frequency and long-duration events significantly decline. An additional 0.5°C of warming further reduces the probability of cold spells.
Keywords:
bias correction
extreme cold spells
extreme value model
global warming
probability risk
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