河西走廊东部不同气候态气温变化及其对气候评价的影响

doi:10.13866/j.azr.2024.07.01

摘要/Abstract

摘要：

河西走廊东部是气候变化的敏感区，其气候态的更替对气候评价影响较大。采用河西走廊东部5个国家气象站的1961─2022年逐月气温数据，对比分析河西走廊东部1961─1990年、1971─2000年、1981─2010年和1991─2020年4个气候态气温的差异及其对气候业务评价的影响。结果表明：全区域及各地4个气候态年平均气温均呈升高趋势，P2（1971—2000年气候态）~P4（1991—2020年气候态）气温升高趋势均极显著。从4个气候态气温的差值来看，全区域及各地年、季、月气温基本一致升温，除P3（1981—2010年气候态）和P4外，其他气候态表现为冬季升幅最大，夏季升幅最小，各月升温差异较大，同一季度、同一月份气温升幅存在明显空间差异。气候态平均值更替后，河西走廊东部气温距平明显偏大的特征弱化了，其等级由正距平向负距平方向调整，P1（1961—1990年气候态）~P4年平均气温评价等级高达56%~87%向偏低一级转变，冷冬年份增多17~28 a，暖冬年份减少15~23 a。本研究将为了解河西走廊东部气温的变化规律以及气候业务、决策服务和气象科学研究提供参考依据。

关键词: 气候变暖, 温度气候态, 变化, 气候评价, 河西走廊东部

Abstract:

Hexi Corridor Eastern is an area sensitive to changes in climate and climate states, greatly affecting climate evaluation. Using the monthly temperature data of five national meteorological stations in Hexi Corridor Eastern from 1961 to 2022, differences in the average temperatures of four climate states, including 1961-1990, 1971-2000, 1981-2010 and 1991-2020 were compared, and their influence on the climate assessment business was analyzed. The results showed that the annual temperatures of the four climate states increased in various and whole regions, most notably in the P2 (1971-2000) and P4 (1991-2020) states. The temperature differences in the climate states revealed the following: (1) the monthly, seasonal, and yearly temperatures consistently warmed up in the whole basin and various regions, and (2) except for the P3 (1981-2010) to P4 climate states, others showed maximal and minimal elevation in winter and summer, respectively. The monthly variations in enhanced temperatures were apparent, and the growth rate demonstrated obvious spatial differences in the same season and month. After the replacement of the climate state means, the conspicuous characteristics of temperature variations were weakened in the Hexi Corridor Eastern, and their grades were adjusted from positive to negative; temperature rating was as high as 56%-87% to a lower level; the cold winter years increased by 17-28 years, and the warm winter years reduced by 15-23 years from P1(1961-1990) to P4 climate states. This study can provide a reference for understanding temperature changes, climate business, decision-making service, and meteorological science research in Hexi Corridor Eastern.

Key words: climate warming, temperature climate state, change, climate assessment, Hexi Corridor Eastern

杨晓玲, 周华, 陈静, 赵慧华, 吴雯. 河西走廊东部不同气候态气温变化及其对气候评价的影响[J]. 干旱区研究, 2024, 41(7): 1089-1098.

YANG Xiaoling, ZHOU Hua, CHEN Jing, ZHAO Huihua, WU Wen. Temperature in different climate states and their influence on climate evaluation in the Hexi Corridor Eastern[J]. Arid Zone Research, 2024, 41(7): 1089-1098.

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参考文献 38

[1]	世界气象组织. WMO气候平均值计算指南[R]. 瑞士日内瓦: 主席出版物委员会, 2017.
	[World Meteorological Organization. WMO Guidelines on the Calculation of Climate Mean[R]. Switzerland Geneva: Chairperson Publications Board, 2017.]
[2]	中国气象局预报与网络司. 《关于做好气候业务中气候平均值更新工作的通知》[Z]. 北京: 中国气象局, 2021.
	[Forecast and network department of China Meteorological Administration. Notice on updating the climate average value in climate business[Z]. Beijing: China Meteorological Administration, 2021.]
[3]	王永光. 多年平均值的改变对中国气候业务的影响[J]. 气象, 2002, 28(8): 41-43.
	[Wang Yongguang. The influence of normals change upon climate operation of China[J]. Meteorological Monthly, 2002, 28(8): 41-43.]
[4]	王秀文, 李月安. 新气候平均值在中期预报业务中的应用[J]. 气象, 2003, 29(1): 43-45.
	[Wang Xiuwen, Li Yue’an. Application of new normals to med-range forecast operation[J]. Meteorological Monthly, 2003, 29(1): 43-45.]
[5]	林婧婧, 张强. 中国气候态变化特征及其对气候变化分析的影响[J]. 高原气象, 2015, 34(6): 1593-1600. doi: 10.7522/j.issn.1000-0534.2014.00092
	[Lin Jingjing, Zhang Qiang. Characteristics of China climate states change and its impact on the analysis of climate change[J]. Plateau Meteorology, 2015, 34(6): 1593-1600.] doi: 10.7522/j.issn.1000-0534.2014.00092
[6]	梅梅, 侯威, 周星妍. 新、旧气候态差异及对中国地区气候和极端事件评估业务的影响[J]. 气候变化研究进展, 2022, 18(6): 653-669.
	[Mei Mei, Hou Wei, Zhou Xingyan. The difference between new and old climate states and its impact on the assessment of climate and extreme event in China[J]. Climate Change Research, 2022, 18(6): 653-669.]
[7]	晏红明, 袁媛, 王永光. 气候变暖背景下气候平均值更替对中国气候业务的影响[J]. 气象, 2022, 48(3): 284-298.
	[Yan Hongming, Yuan Yuan, Wang Yongguang. Influence of climate mean value change on climate operation in China under the global warming[J]. Meteorological Monthly, 2022, 48(3): 284-298.]
[8]	房一禾, 赵春雨, 王颖, 等. 新、旧气候态的差异及对东北地区气候业务的影响[J]. 气候变化研究进展, 2016, 12(3): 193-201.
	[Fang Yihe, Zhao Chunyu, Wang Ying, et al. The differences between new and old climate states and its influence on climate operation in the Northeast China[J]. Climate Change Research, 2016, 12(3): 193-201.]
[9]	张萌萌, 赵春雨, 房一禾, 等. 基于新气候态背景的中国东北地区气候变化评估与预测研究[J]. 气象与环境学报, 2023, 39(4): 95-102.
	[Zhang Mengmeng, Zhao Chunyu, Fang Yihe, et al. Assessment and prediction of climate change in northeast China based on new climate state background[J]. Journal of Meteorology and Environmental, 2023, 39(4): 95-102.]
[10]	王劲廷, 马振峰, 杨小波, 等. 新旧气候平均值的差异及其对西南气候业务的影响[J]. 高原山地气象研究, 2014, 34(1): 46-50.
	[Wang Jinting, Ma Zhenfeng, Yang Xiaobo, et al. Difference of two 30 years averages and its influence on operational climatic analysis[J]. Plateau and Mountain Meteorology Research, 2014, 34(1): 46-50.]
[11]	邓彪, 王顺久, 王春学, 等. 1991-2020年四川省气候平均值的变化及业务应用评估[J]. 高原山地气象研究, 2023, 43(2): 90-95.
	[Deng Biao, Wang Shunjiu, Wang Chunxue, et al. Change of climate average value in Sichuan Province from 1991 to 2020 and assessment of operational applications[J]. Plateau and Mountain Meteorology Research, 2023, 43(2): 90-95.]
[12]	雷向杰, 黄祖英, 田武文, 等. 两个30年气候平均值的差异及其对气候业务的影响[J]. 气象科技, 2005, 33(2): 124-127.
	[Lei Xiangjie, Huang Zuying, Tian Wuwen, et al. Difference of two 30-year averages and its influence on operational climatic analysis[J]. Meteorological Science and Technology, 2005, 33(2): 124-127.]
[13]	刘桂芳, 卢鹤立. 全球变暖背景下的中国西部地区气候变化研究进展[J]. 气象与环境科学, 2009, 32(4): 69-73.
	[Liu Guifang, Lu Heli. Research progress on climate change in western China on the background of global warming[J]. Meteorological and Environmental Science, 2009, 32(4): 69-73.]
[14]	马鹏里, 杨金虎, 卢国阳, 等. 西北地区东部气候的转折性变化[J]. 高原气象, 2020, 39(4): 840-850. doi: 10.7522/j.issn.1000-0534.2019.00093
	[Ma Pengli, Yang Jinhu, Lu Guoyang, et al. The transitional change of climate in the east of Northwest China[J]. Plateau Meteorology, 2020, 39(4): 840-850.] doi: 10.7522/j.issn.1000-0534.2019.00093
[15]	李明, 孙洪泉, 苏志诚. 中国西北气候干湿变化研究进展[J]. 地理研究, 2021, 40(4): 1180-1194. doi: 10.11821/dlyj020200328
	[Li Ming, Sun Hongquan, Su Zhicheng. Research progress in dry/wet climate variation in northwest China[J]. Geographical Research, 2021, 40(4): 1180-1194.] doi: 10.11821/dlyj020200328
[16]	张强, 朱彪, 杨金虎, 等. 西北地区气候湿化趋势的新特征[J]. 科学通报, 2021, 66(增刊): 3757-3771.
	[Zhang Qiang, Zhu Biao, Yang Jinhu, et al. New characteristics of the climate humidification trend in Northwest China[J]. Chinese Science Bulletin, 2021, 66(Suppl. ): 3757-3771.]
[17]	张婧莉, 吴秀兰, 姚俊强, 等. 新、旧气候态的差异及其对新疆气候评价业务的影响[J]. 沙漠与绿洲气象, 2023, 17(5): 134-140.
	[Zhang Jingli, Wu Xiulan, Yao Junqiang, et al. The difference between new and old climate states and its influence on climate operation in Xinjiang[J]. Desert and Oasis Meteorology, 2023, 17(5): 134-140.]
[18]	孙爽, 高原, 裴宇航, 等. 黑龙江省1981-2010年气候平均值的变化对气候评价的影响[J]. 黑龙江气象, 2014, 31(2): 1-3.
	[Sun Shuang, Gao Yuan, Pei Yuhang, et al. The climate average change from 1981 to 2010 and its impact on the climate evaluation in Heilongjiang Province[J]. Heilongjiang Meteorology, 2014, 31(2): 1-3.]
[19]	梁茹雪, 李茜, 张丽君. 新旧气候平均值更替对陕西气候业务的影响[J]. 沙漠与绿洲气象, 2023, 17(4): 111-117.
	[Liang Ruxue, Li Qian, Zhang Lijun. Influence of climatic mean value change on Shanxi climatic operation[J]. Desert and Oasis Meteorology, 2023, 17(4): 111-117.]
[20]	黄彩婷, 董保华, 赵冠男, 等. 新旧气候态的差异及其对江西气候业务的影响[J], 气象与减灾研究, 2023, 6(2): 89-91.
	[Huang Caiting, Dong Baohua, Zhao Guannan, et al. Differences between old and new climate states and its influence on Jiangxi climatic operation[J]. Meteorology and Disaster Reduction Research, 2023, 6(2): 89-91.]
[21]	杨晓玲, 丁文魁, 杨金虎, 等. 河西走廊东部近50年气候变化特征及区内5站对比分析[J]. 干旱地区农业研究, 2011, 29(5): 259-268.
	[Yang Xiaoling, Ding Wenkui, Yang Jinhu, et al. Change characteristics and 5 statoins comparative analysis of climate in Hexi Corridor Eastern in resent 50 years[J]. Agricultural Research in the Arid Areas, 2011, 29(5): 259-268.]
[22]	李玲萍, 杨永龙, 钱莉. 石羊河流域近45年气温和降水特征分析[J]. 干旱区研究, 2008, 25(5): 705-710.
	[Li Lingping, Yang Yonglong, Qian Li. Analysis on the characteristics of temperature and precipitation in the Shiyang River Basin since resent 45 years[J]. Arid Zone Research, 2008, 25(5): 705-710.]
[23]	丁贞玉, 马金珠, 张宝军, 等. 近50年来石羊河流域气候变化趋势分析[J]. 干旱区研究, 2007, 24(6): 779-784.
	[Ding Zhenyu, Ma Jinzhu, Zhang Baojun, et al. Analysis on the climate change in the Shiyang River Basin since resent 50 years[J]. Arid Zone Research, 2007, 24(6): 779-784.]
[24]	魏邦宪, 苗婷, 雷瑜, 等. 石羊河流域气候变化特征及干旱变化趋势分析[J]. 现代农业科技, 2017(15): 220-222.
	[Wei Bangxian, Miao Ting, Lei Yu, et al. Analysis of climate change characteristics and drought change trend in Shiyang River Basin[J]. Modern Agricultural Science and Technology, 2017(15): 220-222.]
[25]	白肇烨, 徐国昌, 孙学筠, 等. 中国西北天气[M]. 北京: 气象出版社, 1991: 258-357.
	[Bai Zhaoye, Xu Guochang, Sun Xuejun, et al. Weather over Northwest China[M]. Beijing: Meteorological Press, 1991: 258-237.]
[26]	魏凤英. 现代气候统计诊断与预测技术[M]. 北京: 气象出版社, 2007: 37-41.
	[Wei Fengying. Modern Climatic Statistical Giagnosis and Prediction Technology[M]. Beijing: Meteorological Press, 2007: 37-41.]
[27]	施能, 陈家其, 屠其璞. 中国近100年来4个年代际的气候变化特征[J]. 气象学报, 1995, 53(4): 431-439.
	[Shi Neng, Chen Jiaqi, Tu Qipu. Climate variation characteristics over China in 4 age nearly 100 years[J]. Journal of Meteorology, 1995, 53(4): 431-439.]
[28]	Livezey R E, Chen W Y. Statistical filed significance and its determination by Monte Carlo techniques[J]. Monthly Weather Review, 1983, 111(1): 46-59.
[29]	中国气象局. 《短期气候预测质量评定暂行办法》[Z]. 北京: 中国气象局, 1999.
	[China Meteorological Administration. Interim measures for quality assessment of short-term climate forecasting[Z]. Beijing: China Meteorological Administration, 1999.]
[30]	中华人民共和国国家质量监督检验检疫总局, 中国国家标准化管理委员会. 冷冬等级(GB/T 33675—2017)[S]. 北京: 中国标准出版社, 2017.
	[General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China, Standardization Administration of the People’s Republic of China, SAC. Cold Winter Grade (GB/T 33675—2017)[S]. Beijing: China Standards Press, 2017.]
[31]	中华人民共和国国家市场监督管理总局, 中国国家标准化管理委员会. 暖冬等级(GB/T 21983—2020)[S]. 北京: 中国标准出版社, 2020.
	[The State Administration for Market Regulation of the People’s Republic of China, Standardization Administration of the People’s Republic of China, SAC. Warm Winter Grade (GB/T 21983—2020) [S]. Beijing: China Standards Press, 2020.]
[32]	姚俊强, 李漠岩, 迪丽努尔·托列吾别克, 等. 不同时间尺度下新疆气候“暖湿化”特征[J]. 干旱区研究, 2022, 39(2): 333-346.
	[Yao Junqiang, Li Moyan, Dilinuer Tuoliewubieke, et al. The assessment on “warming-wetting” trend in Xinjiang at multi-scale during 1961-2019[J]. Arid Zone Research, 2022, 39(2): 333-346.]
[33]	白素琴. 不同气候平均值对气候评价业务的影响[J]. 沙漠与绿洲气象, 2016, 10(1): 88-94.
	[Bai Suqin. Difference of normals and its influence on climate assessment in Xinjiang[J]. Desert and Oasis Meteorology, 2016, 10(1): 88-94.]
[34]	中国气象局气候变化中心. 中国气候变化蓝皮书2020[M]. 北京: 科学出版社, 2020: 8.
	[The Climate Change Center of China Meteorological Administration. China Blue Book on Climate Change 2020[M]. Beijing: Science Press, 2020: 8.]
[35]	刘芸芸, 王永光, 柯宗健. 2020年夏季我国气候异常特征及成因分析[J]. 气象, 2021, 47(1): 117-126.
	[Liu Yunyun, Wang Yongguang, Ke Zongjian. Characteristics and possible causes for the climate anomalies over china in summer 2020[J]. Meteorological Monthly, 2021, 47(1): 117-126.]
[36]	吴立新. 气候变暖背景下全球平均海洋环流在加速[J]. 中国科学: 地球科学, 2020, 50(7): 1021-1022.
	[Wu Lixin. The global mean ocean circulation is accelerating under the climate warming[J]. Chinese Science: Earth Science, 2020, 50(7): 1021-1022.]
[37]	雷杨娜. 中国近50年夏季高温时空变化特征及其影响因子分析[D]. 北京: 北京师范大学, 2009.
	[Lei Yangna. The Change of Summer Fot Days in East China during the Last 50 Years[D]. Beijing: Beijing Normal University, 2009.]
[38]	杨若子. 东北地区玉米低温冷害指标及其风险研究[D]. 北京: 中国气象科学研究院, 2012.
	[Yang Ruozi. Study on Corn Chilling Damage and Its Risk Factor in Northeast China[D]. Beijing: Chinese Academy of Meteorological Sciences, 2012.]

序号	评价标准/℃	等级
1	ΔA≤-2.0	异常偏低
2	-2.0<ΔA≤-1.0	明显偏低
3	-1.0<ΔA<0.0	正常略低
4	0.0≤ΔA<1.0	正常略高
5	1.0≤ΔA<2.0	明显偏高
6	ΔA≥2.0	异常偏高

项目		永昌	凉州	民勤	古浪	天祝	全区域
	均值(T₁)/℃	4.8	7.7	7.9	4.9	-0.3	5.0
	倾向率(a₁)/[℃·（10a）^-1]	0.139	0.029	0.272	0.127	0.064	0.126
	趋势系数	0.250	0.054	0.433^**	0.244	0.137	0.243
	均值(T₂)/℃	5.0	7.9	8.3	5.2	0.0	5.3
	倾向率(a₂)/[℃·（10a）^-1]	0.298	0.407	0.548	0.418	0.385	0.411
	趋势系数	0.505^*	0.551^*	0.739^*	0.594^*	0.612^*	0.621^*
	均值(T₃)/℃	5.4	8.5	8.8	5.7	0.3	5.8
	倾向率(a₃)/[℃·（10a）^-1]	0.412	0.792	0.541	0.626	0.293	0.533
	趋势系数	0.629^*	0.795^*	0.719^*	0.787^*	0.523^*	0.736^*
	均值(T₄)/℃	5.8	9.2	9.4	6.3	0.7	6.3
	倾向率(a₄)/[℃·（10a）^-1]	0.528	0.894	0.554	0.770	0.519	0.653
	趋势系数	0.750^*	0.842^*	0.730^*	0.844^*	0.753^*	0.810^*
Δa_2-1/[℃·（10a）^-1]		0.159	0.378	0.276	0.291	0.321	0.285
Δa_3-2/[℃·（10a）^-1]		0.114	0.385	-0.007	0.208	-0.092	0.122
Δa_4-3/[℃·（10a）^-1]		0.116	0.102	0.013	0.144	0.226	0.120
Δa_4-1/[℃·（10a）^-1]		0.389	0.865	0.282	0.643	0.455	0.527

差值	永昌	凉州	民勤	古浪	天祝	全区域
ΔT_2-1	0.2	0.2	0.4	0.3	0.2	0.3
ΔT_3-2	0.4	0.6	0.5	0.5	0.4	0.5
ΔT_4-3	0.4	0.7	0.5	0.6	0.4	0.5
ΔT_4-1	1.0	1.5	1.4	1.5	1.0	1.3

差值	站点	1月	2月	3月	4月	5月	6月	7月	8月	9月	10月	11月	12月
ΔT_2-1	永昌	0.2	0.6	0.1	0.4	-0.1	-0.1	0.1	0.2	0.4	-0.1	0.5	0.4
	凉州	0.3	0.7	0.1	0.3	-0.1	-0.1	0.0	0.0	0.2	-0.1	0.4	0.7
	民勤	0.6	1.0	0.4	0.5	0.1	0.1	0.1	0.1	0.2	0.1	0.6	1.0
	古浪	0.5	0.8	0.2	0.3	0.0	0.2	0.2	0.0	0.3	0.0	0.6	0.7
	天祝	0.2	0.5	0.1	0.2	-0.1	0.2	0.2	0.1	0.4	-0.1	0.7	0.4
	全区域	0.4	0.7	0.2	0.3	0.0	0.1	0.1	0.1	0.3	0.0	0.5	0.6
ΔT_3-2	永昌	0.3	0.7	0.5	0.3	0.2	0.5	0.6	0.3	0.3	0.3	0.3	0.2
	凉州	0.6	1.0	0.8	0.5	0.5	0.8	0.7	0.3	0.5	0.7	0.7	0.4
	民勤	0.4	0.9	0.7	0.4	0.5	0.6	0.5	0.1	0.2	0.4	0.5	0.4
	古浪	0.6	1.0	0.6	0.3	0.3	0.7	0.7	0.3	0.4	0.5	0.6	0.4
	天祝	0.4	0.7	0.5	0.2	0.2	0.5	0.5	0.2	0.4	0.2	0.4	0.2
	全区域	0.5	0.9	0.6	0.4	0.4	0.6	0.6	0.3	0.4	0.4	0.5	0.3
ΔT_4-3	永昌	0.0	0.5	0.8	0.7	0.2	0.6	0.6	0.4	0.2	0.3	0.3	-0.1
	凉州	0.3	0.8	1.1	0.8	0.5	1.0	0.7	0.6	0.6	0.7	0.7	0.3
	民勤	0.2	0.7	1.0	0.8	0.4	0.7	0.5	0.5	0.4	0.4	0.6	0.3
	古浪	0.3	0.8	1.1	0.8	0.3	0.8	0.8	0.6	0.4	0.5	0.7	0.2
	天祝	0.0	0.6	0.8	0.7	0.2	0.5	0.4	0.4	0.3	0.3	0.3	-0.1
	全区域	0.1	0.7	1.0	0.8	0.3	0.7	0.6	0.5	0.4	0.4	0.5	0.1
ΔT_4-1	永昌	0.5	1.9	1.5	1.4	0.3	1.0	1.3	0.9	0.9	0.5	1.1	0.6
	凉州	1.2	2.5	2.0	1.7	1.0	1.7	1.4	0.8	1.3	1.3	1.8	1.4
	民勤	1.2	2.6	2.2	1.7	1.0	1.5	1.1	0.7	0.8	1.0	1.6	1.6
	古浪	1.4	2.6	1.8	1.4	0.7	1.6	1.6	1.0	1.1	1.0	1.9	1.3
	天祝	0.6	1.9	1.4	1.1	0.4	1.1	1.1	0.7	1.1	0.5	1.4	0.5
	全区域	1.0	2.3	1.8	1.5	0.7	1.4	1.3	0.8	1.0	0.8	1.6	1.1