中国东部气温极端特性及其气候特征

doi:10.13249/j.cnki.sgs.2019.08.016

摘要/Abstract

摘要：

基于百分位等统计方法构建极端气候指数,分析中国东部气温极端特性变化的时空格局和趋势特征,探讨其与全球变暖和区域气候变率的关联性。结果表明,近60 a来,中国东部长期增暖趋势明显,高纬度北方地区和冬、春季节气温对全球变暖响应最为显著;相比于日最低气温,日最高气温上升趋势不明显,黄河与长江之间部分地区日最高温度出现下降趋势。全域日较差总体亦呈减小趋势;与日气温极值的平均状况和气候趋势相一致,极端低温事件强度下降趋势明显,黄河以北及东南沿海地区减弱显著。极端高温事件强度增加趋势并不明显,黄淮地区出现减小趋势;年霜冻日数和冰冻日数以及寒潮持续期的长期变化趋势以减少为主。高温热浪的持续期则以增加为主;中国东部极端气温事件频次与强度的演变格局存在同向一致性。极端低温影响指数的分布呈现北部大于南部、内陆大于沿海地区的特征,全域以一致性下降趋势为主,特别是东部沿海降低最为明显。另外,春季极端低温的影响指数大于冬季,且未有明显减小趋势。极端高温的影响指数增强趋势不明显,地区差异较大,指数的大值区影响增强的趋势显著。相比于强度,极端气温事件频次对全球气候变化的响应更为敏感。同时,副热带高压、南极涛动和北极涛动等区域性气候变率可能是调控中国东部极端气温事件形成和演化的重要因素。

关键词: 高温热浪, 低温寒潮, 致灾因子危险性, 全球气候变化, 中国东部

Abstract:

:Based on percentile and other statistical methods, the climate index was built to analyze the extreme peculiarities of temperature, its space-time evolution and the regional differences in the eastern China (ECM excluding Hongkong Macao and Taiwan), and the associations with the global and regional climatic and oceanic variabilities were discussed. The results show that, in the past 60 years, the long-term warming trend in the ECM is obvious. Due to the influence of latitude and seasons, the response to global warming is most obvious in the northern regions with high latitude and in winter and spring seasons. Compared with the daily minimum temperature, the daily maximum temperature did not distinctly increase especially in the central region between the Yellow River and the Yangtze River. As a result, the diurnal temperature range also showed a decreasing trend overall. In consistent with the average temperature extremes and climatic regioons, the intensity of extreme cold events (ECE) decreased significantly, especially in the north of the Yellow River and southeast coastal areas. However, the long-term trend of the intensity of extreme high temperature events (EHTE) is not obvious, especially in Huanghuai area where the decrease trend dominated. Long-term trends of annual frost and ice days and the cold wave duration experienced a reduce, while the heat wave duration gives priority to increase. The spatial pattern of the intensity and frequency of the extreme events were well consistency, and the response to global changes is remarkable. The impaction index of the ECE possessed greater values in northern region and inland, while lower in the southern regions and coastal areas. The corresponding long-term trend is decline with regional uniformity, especially in the eastern coastal areas. Meanwhile, the impaction index of the ECE in spring is higher than that in winter, and its decline trend is not obvious. The long-term increase trend of impact index of the EHTE was smaller and regional differences are significant. Moreover, the climatic trend in the areas with large values of impaction index was mainly enhanced, while that in the areas with smaller values most significantly weakened. Overall, the frequency of regional extreme temperature events is more sensitive to global climate change than the intensity. The analysis further shows that, the subtropical high, Antarctic and Arctic oscillations may be important factors influencing the formation and evolution of extreme temperature events in the EC.

Key words: heat wave, cold wave, hazard of disaster-inducing factors, global climate change, the eastern China

中图分类号:

P466

齐庆华,蔡榕硕,郭海峡. 中国东部气温极端特性及其气候特征[J]. 地理科学, 2019, 39(8): 1340-1350.

Qi Qinghua,Cai Rongshuo,Guo Haixia. The Climatic Variations of Temperature Extremes in the Eastern of China[J]. SCIENTIA GEOGRAPHICA SINICA, 2019, 39(8): 1340-1350.

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参考文献 20

[1]	IPCC. Climate Change 2013: The physical science basic contribution of working group 1 to the fifth assessment report of the intergovernmental panel on climate change[M]. Cambridge, United Kingdom and New York, USA: Cambridge University Press, 2013.
[2]	秦大河 . 中国极端气候事件和灾害风险管理及适应国家评估报告[M]. 北京: 科学出版社, 2015.
	[ Qin Dahe. China national assessment report on risk management and adaptation of climate extremes and disasters. Beijing: Science Press, 2015.]
[3]	《第三次气候变化国家评估报告》编写委员会. 第三次气候变化国家评估报告[M]. 北京: 科学出版社, 2015.
	[ Editorial Committee of the Third National Assessment Report on Climate Change. The third national assessment report on climate change. Beijing: Science Press, 2015.]
[4]	徐金芳, 邓振镛, 陈敏 . 中国高温热浪危害特征的研究综述[J]. 干旱气象, 2009,27(2):163-167. doi: 10.3969/j.issn.1006-7639.2009.02.012
	[ Xu Jinfang, Deng Zhenyong, Chen Min . A summary of studying on characteristics of high temperature and heat wave damage in China. Arid Meteorology, 2009,27(2):163-167.] doi: 10.3969/j.issn.1006-7639.2009.02.012
[5]	孙宇 . 夏季不同下垫面最高气温变化特征及影响因子[J].江西农业, 2016(13):55-56.
	[ Sun Yu . The variation characteristics and influencing factors of the maximum temperature of different underlying surfaces in summer. Jiangxi Agriculture, 2016(13):55-56.]
[6]	谢志清, 杜银, 曾燕 , 等. 长江三角洲城市集群化发展对极端高温事件空间格局的影响[J].科学通报 2017(z1):233-244.
	[ Xie Zhiqing, Du Yin, Zeng Yan , et al. Impact of urban clusters on spatial pattern of extreme high temperature events over Yangtze River Delta. Chinese Science Bulletin, 2017(z1):233-244.]
[7]	龚志强, 王晓娟, 崔冬林 , 等. 区域性极端低温事件的识别及其变化特征[J]. 应用气象学报, 2012,23(2):195-204.
	[ Gong Zhiqiang, Wang Xiaojuan, Cui Donglin et al. The identification and changing characteristics of regional low temperature extreme events. Quarterly Journal of Applied Meteorology, 2012,23(2):195-204.]
[8]	钱维宏, 符娇兰, 张玮玮 , 等. 近40 年中国平均气候与极值气候变化的概述[J]. 地球科学进展, 2007,22(7):673-684.
	[ Qian Weihong, Fu Jiaolan, Zhang Weiwei , et al. Changes in mean climate and extreme climate in China during the last 40 years. Advances in Earth Science, 2007,22(7):673-684.]
[9]	丁裕国, 江志红 . 极端气候研究方法导论(诊断及模拟与预测[M]. 北京: 气象出版社, 2009.
	[ Ding Yuguo, Jiang Zhihong. Introduction to extreme climate research methods (diagnosis and simulation and prediction. Beijing: Meteorological Press, 2009.]
[10]	Yan Z, Jones P D, Davies T D , et al. Trends of extreme temperatures in Europe and China based on daily observations[J]. Climatic Change, 2002,53(1-3):355-392.
[11]	翟盘茂, 刘静 . 气候变暖背景下的极端天气气候事件与防灾减灾[J]. 中国工程科学, 2012,14(9):55-63.
	[ Zhai Panmao, Liu Jing . Extreme weather/climate events and disaster prevention and mitigation under global warming background. Engineering Science, 2012,14(9):55-63.]
[12]	Jones P D, Horton E B, Folland C K et al. The use of indices to identify changes in climatic extremes[J]. Climatic Change, 1999,42(1):131-149.
[13]	IPCC. Managing the risks of extreme events and disasters to advance climate change adaptation[M]. Cambridge, UK, and New York, NY, USA: Cambridge University Press, 2012.
[14]	齐庆华, 蔡榕硕 . 21世纪海上丝绸之路海表温度异常与气候变率的相关性初探[J]. 海洋开发与管理, 2017,34(4):41-49.
	[ Qi Qinghua, Cai Rongshuo . Spatio-temporal change of sea surface temperature anomalies in seas of 21st century maritime silk road and its net correlation to climate variability. Ocean Development and Management, 2017,34(4):41-49.]
[15]	齐庆华, 蔡榕硕 . 中国大陆东部相对湿度变化与海陆热力差异的关联性初探[J].高原气象, 2017(6):1587-1594.
	[ Qi Qinghua, Cai Rongshuo . The variation of relative humidity in the east of Chinese mainland and its association with Sea-Land thermal contrast. Plateau Meteorology, 2017(6):1587-1594.]
[16]	Zhai P, Pan X . Trends in temperature extremes during 1951-1999 in China[J]. Geophysical Research Letters, 2003,30(17):169-172.
[17]	Li Q, Yang S, Xu W et al. China experiencing the recent warming hiatus[J]. Geophysical Research Letters, 2015,42(3):889-898.
[18]	Shen X, Liu B, Lu X . Weak cooling of cold extremes versus continued warming of hot extremes in China during the recent global surface warming hiatus[J]. Journal of Geophysical Research: Atmospheres, 2018,123:1-15.
[19]	齐庆华, 蔡榕硕 . 中国近海海表温度变化的极端特性及其气候特征研究[J]. 海洋学报, 2019,41(7):36-51.
	[ Qi Qinghua, Cai Rongshuo . Analysis on climate characteristics of sea surface temperature extremes in coastal China seas. Haiyang Xuebao, 2019,41(7):36-51.]
[20]	齐庆华 . 基于国家海洋治理和全球气候变化的我国海洋灾害防治[J]. 海洋开发与管理, 2019,36(2):17-23.
	[ Qi Qinghua . Marine disaster prevention in China based on national marine governance and global climate Change. Ocean Development and management, 2019,36(2):17-23.]

极端天气气候事件（指标）	指数类型	指数名称	单位
气温	极值与平均状况	最高气温的气候平均态	℃
		最低气温的气候平均态	℃
		日均气温的气候平均态	℃
	极端特性（强度）	日较差	℃
		超过第90百分位的最高气温均值	℃
		低于第10百分位的最低气温均值	℃
	极端特性（持续性）	霜冻日数	d
		冰冻日数	d
		寒潮持续期	d
		热浪持续期	d
	影响指数（累积频次）	极端低温日数的占比	%
	影响指数（累积频次）	极端高温日数的占比	%