基于再分析资料的近百年中国极端冷事件的变化

doi:10.12006/j.issn.1673-1719.2022.237

摘要/Abstract

摘要：

全球变暖背景下，中国区域极端冷事件发生明显变化。由于观测资料的限制，近百年极端事件变化特征的研究还较少。通过对比观测资料和两套百年尺度的再分析资料计算得到的13个极端冷事件指数，对中国区域极端冷事件变化特征的分析表明：同全球变暖一致，20世纪早期以来，中国极端冷事件的强度、频率、持续时间均呈减小趋势，基于过冷系数定义的寒流次数、持续日数均呈现减少趋势，采暖度日数减小，反映我国供暖能源需求呈减少趋势。1951年以后极端冷事件的特征的变化更为显著，一些指数的变化明显超过百年尺度的变化，说明20世纪中期以后冷事件迅速减弱、减少。两套百年尺度的再分析资料可用来研究中国区域极端冷事件变化，但在资料匮乏的地区不确定性很大，需要谨慎考虑资料分布范围和资料质量等问题。

关键词: 近百年气候变化, 极端冷事件, 极端气候指数

Abstract:

Significant changes of extreme cold events in China have occurred in the background of global warming. There are few studies focusing on the characteristics of extreme cold event change in the last century due to the limitation of observation data. By comparing the ETCCDI (Expert Team on Climate Change Detection and Indices) and the newly extended ET-SCI (Expert Team on Sector-specific Climate Indices) calculated from observations and two century-scale reanalysis datasets (NOAA-20CRv2 and ERA-20C), we analyzed the characteristics of the changes of extreme cold events in China. Consisting with global warming, the intensity, frequency, and duration of extreme cold events in China showed a decreasing trend since the early 20th century. Meanwhile, the number and duration of cold wave defined based on the ECF (Excess Cold Factor) presented the trend of reduction, and the decrease in Heating Degree Day (HDD) reflected the decreasing trend of heating energy demand in China. Trends of the characteristics of extreme cold event were more pronounced after 1951 in China, with trends of some indices significantly exceeding the century trends. The above showed that cold events had decreased rapidly since the mid-20th century. It’s worth noting that the two sets of centennial scale reanalysis data can be used to study the changes of regional extreme cold events in China, but the uncertainties are large in areas with insufficient spatio-temporal coverage of site observations, and the deficiencies caused by spatial coverage and quality issues need to be carefully considered.

Key words: Century climate change, Extreme cold events, Climate extremes indices

王冰杰, 孙颖, 胡婷, 董思言. 基于再分析资料的近百年中国极端冷事件的变化[J]. 气候变化研究进展, 2023, 19(4): 403-417.

WANG Bing-Jie, SUN Ying, HU Ting, DONG Si-Yan. Changes of extreme cold events in China over the last century based on reanalysis data[J]. Climate Change Research, 2023, 19(4): 403-417.

图/表 8

图1 中国2419个观测站点分布图

Fig. 1 Locations of 2419 stations over China

表1 NOAA-20CRv2c和ERA-20C的主要信息

Table 1 The main information of NOAA-20CRv2c and ERA-20C

表2 极端冷事件指数

Table 2 Indices of extreme cold event

图2 1961—2010年中国极端指数趋势分布注：小标题后缀为1基于观测，为2基于NOAA-20CRv2c；每个格点的趋势基于相对于1961—1990年均值的距平值计算，打点区域表示p<0.05；图上的数字表示全国指数趋势变化值，带*表示p<0.05。

Fig. 2 Spatial trend patterns of anomalies of extreme indices relative to the 1961-1990 average in China during 1961-2010 based on observation (1), NOAA-20CRv2c (2). (Dotting denotes pass of the t-test at the 95% confidence level. The number in the upper center area above panels indicates the trend in China, and * denotes pass of the t-test at the 95% confidence level)

图3 1961—2010年基于再分析与观测资料的极端指数的空间相关系数时间变化序列

Fig. 3 Time series of pattern correlations of annual fields between the reanalysis datasets and observation data during 1961-2010

图4 1961—2010年基于再分析与观测资料的极端指数对比标准化泰勒图注：括号后面A表示全国，W表示西部，E表示东部。

Fig. 4 The standardized Taylor diagram of extreme indices based on the observation and reanalysis datasets during 1961-2010. (A denotes all in China, W denotes western China, E denotes eastern China)

图5 中国区域平均极端指数时间变化序列注：相对于1961—1990年的距平。

Fig. 5 Time series of area-averaged annual extreme indices in China relative to 1961-1990

图6 1901—2010年中国极端指数线性趋势注：TNn/TXn/HDD单位为℃/(10 a)，TN10p/TX10p单位为%/(10 a)，FD/ID/CSDI/CWF/CWD单位为d/(10 a)，CWN单位为次/(10 a)，CWM/CWA单位为℃2/(10 a)。

Fig. 6 Linear trends of extreme indices in China during 1901-2010. ( “×” denotes no-pass of the t-test at the 95% confidence level)

参考文献 63

[1]	Masson-Delmotte V P, Zhai P, Pirani A, et al. Summary for policymakers[M]//IPCC. Climate change 2021: the physical science basis. Cambridge: Cambridge University Press, 2021: 1-41
[2]	Alexander L V, Zhang X B, Peter T C, et al. Global observed changes in daily climate extremes of temperature and precipitation[J]. Journal of Meteorological Research, 2006, 111 (D5): 1-22. DOI: 10.1029/2005JD006290 doi: 10.1029/2005JD006290
[3]	Donat M G, Alexander L V, Yang H, et al. Updated analyses of temperature and precipitation extreme indices since the beginning of the twentieth century: the HadEX2 dataset[J]. Journal of Geophysical Research Atmospheres, 2013, 118 (5): 2098-2118. DOI: 10.1002/jgrd.50150, 20 doi: 10.1002/jgrd.50150 URL
[4]	Sillmann J, Kharin V V, Zhang X, et al. Climate extremes indices in the CMIP5 multimodel ensemble: Part 1. Model evaluation in the present climate[J]. Journal of Geophysical Research Atmospheres, 2013, 118 (4): 1716-1733. DOI: 10.1002/jgrd.50203 doi: 10.1002/jgrd.50203 URL
[5]	Vavrus S, Walsh J E, Chapman W L, et al. The behavior of extreme cold air outbreaks under greenhouse warming[J]. International Journal of Climatology, 2006, 26 (9): 1133-1147. DOI: 10.1002/JOC.1301 doi: 10.1002/JOC.1301 URL
[6]	Smith E T, Sheridan S C. The characteristics of extreme cold events and cold air outbreaks in the eastern United States[J]. International Journal of Climatology, 2018, 38: e807-e820. DOI: 10.1002/joc.5408 doi: 10.1002/joc.5408
[7]	秦大河. 中国极端天气气候事件和灾害风险管理与适应国家评估报告[M]. 北京: 科学出版社, 2015: 104-110.
	Qin D H. National assessment report on risk management and adaptation to extreme weather and climate events and disasters in China[M]. Beijing: Science Press, 2015: 104-110 (in Chinese)
[8]	秦明月, 李双林. 2018年和2008年1—2月影响我国的持续低温事件及其对比分析[J]. 气候与环境研究, 2020, 25 (6): 15. DOI: 10.3878/j.issn.1006-9585.2020.19154. doi: 10.3878/j.issn.1006-9585.2020.19154
	Qin M Y, Li S L. Persistent low temperature events affecting China in January-February 2018 and 2008 and their comparative analysis[J]. Climate and Environment Research, 2020, 25 (6): 15. DOI: 10.3878/j.issn.1006-9585.2020.19154 (in Chinese) doi: 10.3878/j.issn.1006-9585.2020.19154
[9]	Zhou B T, Xu Y, Wu J, et al. Changes in temperature and precipitation extreme indices over China: analysis of a high-resolution grid dataset[J]. International Journal of Climatology, 2016, 36 (3): 1051-1066. DOI: 10.1002/joc.4400 doi: 10.1002/joc.4400 URL
[10]	Hu T, Sun Y. Anthropogenic influence on extreme temperatures in China based on CMIP6 models[J]. International Journal of Climatology, 2022, 42 (5): 2981-2995. DOI: 10.1002/joc.7402 doi: 10.1002/joc.7402 URL
[11]	尹红, 孙颖. 基于ETCCDI指数2017年中国极端温度和降水特征分析[J]. 气候变化研究进展, 2019, 15 (4): 363-373. DOI: 10.12006/j.issn.1673-1719.2018.164. doi: 10.12006/j.issn.1673-1719.2018.164
	Yin H, Sun Y. Analysis of extreme temperature and precipitation characteristics in China based on ETCCDI index in 2017[J]. Climate Change Research, 2019, 15 (4): 363-373. DOI: 10.12006/j.issn.1673-1719.2018.164 (in Chinese) doi: 10.12006/j.issn.1673-1719.2018.164
[12]	Gulev S K, Thorne P W, Ahn J, et al. Changing state of the climate system[M]//IPCC. Climate change 2021: the physical science basis. Cambridge: Cambridge University Press, 2021: 45-46
[13]	PAGES2k Consortium. A global multiproxy database for temperature reconstructions of the Common Era[J]. Scientific Data, 2017, 4: 170088. DOI: 10.1038/sdata.2017.88 doi: 10.1038/sdata.2017.88 URL
[14]	PAGES2k Consortium. Consistent multidecadal variability in global temperature reconstructions and simulations over the Common Era[J]. Nature Geoscience, 2019, 12: 643-649. DOI: 10.1038/s41561-019-0400-0 doi: 10.1038/s41561-019-0400-0
[15]	Sun W B, Li Q X, Huang B Y. et al. The assessment of global surface temperature change from 1850s: the C-LSAT2.0 ensemble and the CMST-Interim datasets[J]. Advances in Atmospheric Sciences, 2021, 38: 875-888. DOI: 10.1007/s00376-021-1012-3 doi: 10.1007/s00376-021-1012-3
[16]	Yan Z W, Ding Y H, Zhai P M, et al. Re-assessing climatic warming in China since 1900[J]. Journal of Meteorological Research, 2020, 34: 243-251. DOI: 10.1007/s13351-020-9839-6 doi: 10.1007/s13351-020-9839-6
[17]	Cao L J, Zhao P, Yan Z W, et al. Instrumental temperature series in eastern and central China back to the nineteenth century[J]. Journal of Geophysical Research: Atmospheres, 2013, 118: 8197-8207. DOI: 10.1002/jgrd.50615 doi: 10.1002/jgrd.50615 URL
[18]	Cao L J, Yan Z W, Zhao P, et al. Climatic warming in China during 1901-2015 based on an extended dataset of instrumental temperature records[J]. Environmental Research Letters, 2017, 12 (6): 064005. DOI: 10.1088/1748-9326/aa68e8 doi: 10.1088/1748-9326/aa68e8 URL
[19]	Ren G Y, Ding Y H, Tang G L. An overview of mainland China temperature change research[J]. Journal of Meteorological Research, 2017, 31: 3-16. DOI: 10.1007/s13351-017-6195-2 doi: 10.1007/s13351-017-6195-2 URL
[20]	Si P, Li Q X, Jones P. Construction of homogenized daily surface air temperature for the city of Tianjin during 1887-2019[J]. Earth System Science Data, 2021, 13: 2211-2226. DOI: 10.5194/essd-13-2211-2021 doi: 10.5194/essd-13-2211-2021 URL
[21]	Si P, Guo J, Zhao Y F, et al. New series of daily maximum and minimum temperature observations for Beijing, China since 1841[J]. Acta Meteorologica Sinica, 2022, 80 (1): 136-152. DOI: 10.11676/qxxb2022.008 doi: 10.11676/qxxb2022.008
[22]	Yu X J, Ren G Y, Zhang P F, et al. Extreme temperature change of the last 110 years in Changchun Northeast China[J]. Advances in Atmospheric Sciences, 2020, 37 (4): 347-358. DOI: 10.1007/s00376-020-9165-z doi: 10.1007/s00376-020-9165-z
[23]	Yan Z W, Yang C, Jones P. Influence of inhomogeneity on the estimation of mean and extreme temperature trends in Beijing and Shanghai[J]. Advances in Atmospheric Sciences, 2001, 18: 309-322. DOI: 10.1007/BF02919312 doi: 10.1007/BF02919312 URL
[24]	Donat M G, Sillmann J, Wild S, et al. Consistency of temperature and precipitation extremes across various global gridded in situ and reanalysis datasets[J]. Journal of Climate, 2014, 27 (13): 5019-5035. DOI: 10.1175/JCLI-D-13-00405.1 doi: 10.1175/JCLI-D-13-00405.1 URL
[25]	Ajjur S B, Al-Ghamdi S G. Global hotspots for future absolute temperature extremes from CMIP6 models[J]. Earth and Space Science, 2021: 8. DOI: 10.1029/2021EA001817 doi: 10.1029/2021EA001817
[26]	Nairn J R, Fawcett R. Defining heatwaves: heatwave defined as a heat impact event servicing all community and business sectors in Australia, CAWCR technical report[R/OL]. 2013 [2022-10-20]. https://www.cawcr.gov.au/technical-reports/CTR_060.pdf
[27]	Nairn J R, Fawcett R J. The excess heat factor: a metric for heatwave intensity and its use in classifying heatwave severity[J]. International Journal of Environmental Research and Public Health, 2014, 12 (1): 227-253. DOI: 10.3390/ijerph120100227 doi: 10.3390/ijerph120100227 pmid: 25546282
[28]	Perkins S E, Alexander L V. On the measurement of heat waves[J]. Journal of Climate, 2013, 26: 4500-4517. DOI: 10.1175/JCLI-D-12-00383.1 doi: 10.1175/JCLI-D-12-00383.1 URL
[29]	Thom H C. The rational relationship between heating degree days and temperature[J]. Monthly Weather Review, 1954, 82 (1): 1-6. DOI: 10.1175/1520-0493(1954)082<0001:TRRBHD>2.0.CO;2 doi: 10.1175/1520-0493(1954)082<0001:TRRBHD>2.0.CO URL
[30]	Islam A R M T, Ahmed I, Rahman M S. Trends in cooling and heating degree-days overtimes in Bangladesh? An investigation of the possible causes of changes[J]. Natural Hazards, 2020, 101 (3): 879-909. DOI: 10.1007/s11069-020-03900-5 doi: 10.1007/s11069-020-03900-5
[31]	袁顺全, 千怀遂. 气候对能源消费影响的测度指数及计算方法[J]. 资源科学, 2004, 26 (6): 125-130.
	Yuan S Q, Qian H S. Measurements of climate impact on energy consumption and calculation methods[J]. Resource Science, 2004, 26 (6): 125-130 (in Chinese)
[32]	Shi Y, Wang G, Gao X, et al. Effects of climate and potential policy changes on heating degree days in current heating areas of China[J]. Scientific Reports, 2018, 8 (1): 1-13. DOI: 10.1038/s41598-018-28411-z doi: 10.1038/s41598-018-28411-z
[33]	You Q L, Fraedrich K, Min J, et al. Can temperature extremes in China be calculated from reanalysis[J]. Global and Planetary Change, 2013, 111: 268-279. DOI: 10.1016/J.GLOPLACHA.2013.10.003 doi: 10.1016/J.GLOPLACHA.2013.10.003 URL
[34]	Donat M G, Alexander L V, Herold N, et al. Temperature and precipitation extremes in century-long gridded observations, reanalyses, and atmospheric model simulations[J]. Journal of Geophysical Research: Atmospheres, 2016, 121 (19): 11174-11189. DOI: 10.1002/2016JD025480 doi: 10.1002/2016JD025480
[35]	Cao L J, Zhu Y N, Tang G L, et al. Climatic warming in China according to a homogenized dataset from 2419 stations[J]. International Journal of Climatology, 2016, 36 (13): 4384-4392. DOI: 10.1002/joc.4639 doi: 10.1002/joc.4639 URL
[36]	Compo G P, Whitaker J S, Sardeshmukh P D, et al. The twentieth century reanalysis project[J]. Quarterly Journal of the Royal Meteorological Society, 2011, 137: 1-28. DOI: 10.1002/qj.776 doi: 10.1002/qj.776
[37]	Poli P, Hersbach H, Dee D P, et al. ERA-20C: an atmospheric reanalysis of the twentieth century[J]. Journal of Climate, 2016, 29 (11): 4083-4097. DOI: 10.1175/JCLI-D-15-0556.1 doi: 10.1175/JCLI-D-15-0556.1 URL
[38]	Alexander L V, Herold N. ClimPACTv2 indices and software. A document prepared on behalf of the Commission for Climatology (CCl) Expert Team on Sector-Specific Climate Indices (ET-SCI)[EB/OL]. 2016 [2023-01-23]. https://github.com/ARCCSS-extremes/climpact2/blob/master/ClimPACTv2_manual.pdf
[39]	中国国家标准化管理委员会. GB/T 21987—2017, 寒潮等级[S]. 北京: 中国标准出版社, 2017.
	Standardization Administration. GB/T 21987—2017, Grade of cold wave[S]. Beijing: Standards Press of China, 2017 (in Chinese)
[40]	Wilks D S. Statistical methods in the atmospheric sciences, 3rd edn[M]. New York: Academic Press, 2011: 676
[41]	Sen P K. Estimates of the regression coefficient based on Kendall’s tau[J]. Journal of the American Statistical Association, 1968, 63 (324): 1379-1389. DOI: 10.2307/2285891 doi: 10.2307/2285891 URL
[42]	Qian C, Zhang X B, Li Z. Linear trends in temperature extremes in China, with an emphasis on non-Gaussian and serially dependent characteristics[J]. Climate Dynamics, 2019, 53: 533-550. DOI: 10.1007/s00382-018-4600-x doi: 10.1007/s00382-018-4600-x
[43]	Taylor K E. Summarizing multiple aspects of model performance in a single diagram[J]. Journal of Geophysical Research: Atmospheres, 2001, 106 (D7): 7183-7192. DOI: 10.1029/2000JD900719 doi: 10.1029/2000JD900719 URL
[44]	蒋文好, 陈活泼. CMIP6模式对亚洲中高纬区极端温度变化的模拟及预估[J]. 大气科学学报, 2021, 44 (4): 12. DOI: 10.13878/j.cnki.dqkxxb.20210203001. doi: 10.13878/j.cnki.dqkxxb.20210203001
	Jiang W H, Chen H P. Simulation and prediction of temperature extremes in the mid- and high-latitude regions of Asia by the CMIP6 model[J]. Journal of Atmospheric Sciences, 2021, 44 (4): 12. DOI: 10.13878/j.cnki.dqkxxb.20210203001 (in Chinese) doi: 10.13878/j.cnki.dqkxxb.20210203001
[45]	Zhao Y M, Qian C, Zhang W J, et al. Extreme temperature indices in Eurasia in a CMIP6 multi-model ensemble: evaluation and projection[J]. International Journal of Climatology, 2021, 41: 5368-5385. DOI: 10.1002/joc.7134 doi: 10.1002/joc.7134 URL
[46]	Huang X X, Xiao J H, He R, et al. Urban expansion patterns of 291 Chinese cities, 1990-2015 [J]. International Journal of Digital Earth, 2017, 12: 1-16. DOI: 10.1080/17538947.2017.1395090 doi: 10.1080/17538947.2017.1395090 URL
[47]	Ren G Y, Li J, Ren Y Y, et al. An integrated procedure to determine a reference station network for evaluating and adjusting urban bias in surface air temperature data[J]. Journal of Applied Meteorology and Climatology, 2015, 54 (6): 1248-1266. DOI: 10.1175/JAMC-D-14-0295.1 doi: 10.1175/JAMC-D-14-0295.1 URL
[48]	Sun Y, Zhang X B, Ren G Y, et al. Contribution of urbanization to warming in China[J]. Nature Climate Change, 2016, 6: 706-709. DOI: 10.1038/nclimate2956 doi: 10.1038/NCLIMATE2956
[49]	Zhang P F, Ren G Y, Qin Y, et al. Urbanization effects on estimates of global trends in mean and extreme air temperature[J]. Journal of Climate, 2021, 34: 1923-1945. DOI: 10.1175/JCLI-D-20-0389.1 doi: 10.1175/JCLI-D-20-0389.1 URL
[50]	Li Q X, Huang J Y, Jiang Z H, et al. Detection of urbanization signals in extreme winter minimum temperature changes over northern China[J]. Climatic Change, 2014, 122: 595-608. DOI: 10.1007/s10584-013-1013-z doi: 10.1007/s10584-013-1013-z URL
[51]	储鹏, 江志红, 李庆祥, 等. 城市分类对中国城市化影响评估的不确定性分析[J]. 大气科学学报, 2016, 39 (5): 661-671. DOI: 10.13878/j.cnki.dqkxxb.20130303003. doi: 10.13878/j.cnki.dqkxxb.20130303003
	Chu P, Jiang Z H, Li Q X, et al. Analysis of the effect of uncertainty in urban and rural classification on urbanization impact assessment[J]. Transactions of Atmospheric Sciences, 2016, 39 (5): 661-671. DOI: 10.13878/j.cnki.dqkxxb.20130303003 (in Chinese) doi: 10.13878/j.cnki.dqkxxb.20130303003
[52]	Kalnay E, Cai M. Impact of urbanization and land-use change on climate[J]. Nature, 2003, 423 (6939): 528-531. DOI: 10.1038/nature01675 doi: 10.1038/nature01675 URL
[53]	Park B J, Kim Y H, Min S K, et al. Long-term warming trends in Korea and contribution of urbanization: an updated assessment[J]. Journal of Geophysical Research: Atmospheres, 2017, 122 (10): 637-654. DOI: 10.1002/2017JD027167 doi: 10.1002/2017JD027167
[54]	Zhang S Q, Ren G Y, Ren Y Y, et al. Comprehensive evaluation of surface air temperature reanalysis over China against urbanization-bias-adjusted observations[J]. Advances in Climate Change Research, 2021, 12 (6): 783-794. DOI: 10.1016/j.accre.2021.09.010 doi: 10.1016/j.accre.2021.09.010 URL
[55]	Zhang S Q, Ren G Y, Ren Y Y, et al. Comparison of surface air temperature between observation and reanalysis data over eastern China for the last 100 years[J]. Journal of the Meteorological Society of Japan, 2019, 97 (1): 89-103. DOI: 10.2151/jmsj.2019-004 doi: 10.2151/jmsj.2019-004
[56]	Yang J X, Huang M T, Zhai P M. Performance of the CRA-40/Land, CMFD, and ERA-Interim datasets in reflecting changes in surface air temperature over the Tibetan Plateau[J]. Journal of Meteorological Research, 2021, 35: 663-672. DOI: 10.1007/s13351-021-0196-x doi: 10.1007/s13351-021-0196-x
[57]	Zhu Z, Shi C X, Zhang T, et al. Applicability analysis of various reanalyzed land surface temperature datasets in China[J]. Journal of Glaciology and Geocryology, 2015, 37 (3): 614-624. DOI: 10.7522/j.issn.1000-0240.2015.0069 doi: 10.7522/j.issn.1000-0240.2015.0069
[58]	Liu D W, Grimmond C S B, Tan J G, et al. A new model to downscale urban and rural surface and air temperatures evaluated in Shanghai, China[J]. Journal of Applied Meteorology and Climatology, 2018, 57 (10): 2267-2283. DOI: 10.1175/JAMC-D-17-0255.1 doi: 10.1175/JAMC-D-17-0255.1 URL
[59]	中国气象局气候变化中心. 中国气候变化蓝皮书(2021)[M]. 北京: 科学出版社, 2021.
	CMA Climate Change Centre. Blue book on climate change in China (2021)[M]. Beijing: Science Press, 2021 (in Chinese)
[60]	Wei T, Ni Y M, Lu C H. Cold waves in East China and their response to two types of Arctic amplification[J]. Atmosphere, 2020, 11: 612. DOI: 10.3390/atmos11060612 doi: 10.3390/atmos11060612 URL
[61]	Ma W J, Xu X B, Li P, et al. Impact of extreme temperature on hospital admission in Shanghai, China[J]. Science of the Total Environment, 2011, 409 (19): 3634-3637. DOI: 10.1016/j.scitotenv.2011.06.042 doi: 10.1016/j.scitotenv.2011.06.042 URL
[62]	Jegasothy E, McGuire R, Nairn J, et al. Extreme climatic conditions and health service utilisation across rural and metropolitan New South Wales[J]. International Journal of Biometeorology, 2017, 61 (8): 1359-1370. DOI: 10.1007/s00484-017-1313-5 doi: 10.1007/s00484-017-1313-5 pmid: 28321590
[63]	Lei J, Chen R J, Yin P, et al. Association between cold spells and mortality risk and burden: a nationwide study in China[J]. Environmental Health Perspectives, 2022, 130 (2): 27006. DOI: 10.1289/EHP9284 doi: 10.1289/EHP9284 pmid: 35157500