1960—2020年黄河流域气候生长季时空演变及成因分析

doi:10.13866/j.azr.2023.10.01

干旱区研究 ›› 2023, Vol. 40 ›› Issue (10): 1537-1546.doi: 10.13866/j.azr.2023.10.01

1960—2020年黄河流域气候生长季时空演变及成因分析

张志高¹(),孙梓欣²,张秀丽³,郭可欣⁴,李卓娅¹,郝海姣¹,蔡茂堂⁵()

1.安阳师范学院资源环境与旅游学院，河南安阳 455000
2.河南大学地理与环境学院，河南开封 475004
3.河南大学黄河文明与可持续发展研究中心，河南开封 475001
4.西南石油大学地球科学与技术学院，四川成都 610500
5.中国地质科学院地质力学研究所，北京 100081

收稿日期:2023-01-30 修回日期:2023-05-24 出版日期:2023-10-15 发布日期:2023-11-01
通讯作者: 蔡茂堂. E-mail: Caimaotang@126.com
作者简介:张志高（1986-），男，博士，副教授，主要从事气候变化研究. E-mail: Zhangzhg06@163.com
基金资助:
国家自然科学基金项目(42272112);河南省哲学社会科学规划项目(2022BJJ003);河南省科技攻关项目(232102320024);河南省科技攻关项目(232102321109);河南省高等学校青年骨干教师项目(2020GGJS188);河南省高等学校重点科研项目(23A170008);安阳市科技计划项目(2022C01NY019);安阳市科技计划项目(2021C01NY035)

Spatial-temporal evolution and impact factors during the climatic growing season in the Yellow River Basin from 1960 to 2020

ZHANG Zhigao¹(),SUN Zixin²,ZHANG Xiuli³,GUO Kexin⁴,LI Zhuoya¹,HAO Haijiao¹,CAI Maotang⁵()

1. School of Resources Environment and Tourism, Anyang Normal University, Anyang 455000, Henan, China
2. School of Geography and Environment, Henan University, Kaifeng 475004, Henan, China
3. Yellow River Civilization and Sustainable Development Research Center, Henan University, Kaifeng 475001, Henan, China
4. College of Earth Science and Technology, Southwest Petroleum University, Chengdu 610500, Sichuan, China
5. Institute of Geomechanics, Chinese Academy of Geological Sciences, Beijing 100081, China

Received:2023-01-30 Revised:2023-05-24 Online:2023-10-15 Published:2023-11-01

摘要/Abstract

摘要：

基于1960—2020年黄河流域89个气象站点资料，采用Mann-Kendall突变检验、Morlet小波分析和相关分析等方法对黄河流域生长季始期（GSS）、生长季末期（GSE）、生长季长度（GSL）、生长季内≥10 ℃活动积温（AT10）和≥10 ℃活动积温天数（DT10）的时空变化特征及其影响因素进行了分析。结果表明：（1）1960—2020年黄河流域GSS显著提前[-2.04 d·(10a)^-1]，GSE呈推迟趋势[0.85 d·(10a)^-1]，GSL显著延长[2.88 d·(10a)^-1]，但区域差异较大，下游GSS开始最早（2月23），上游最晚（3月30），上游GSE结束最早（10月24），下游最晚（11月30），下游GSL最长为334.03 d，上游最短为297.33 d。（2）近61 a黄河流域GSL的显著延长主要源于GSS的显著提前。（3）近61 a来黄河流域生长季指标存在28 a左右的周期变化，GSS、AT10和DT10于1998年发生突变，GSL于2002年发生突变。（4）黄河流域上、中、下游地区生长季指标变化趋势一致，下游地区变化幅度最大，上游地区次之，中游地区变幅最小。（5）相关分析表明，近61 a来黄河流域GSS提前主要与春季升温有关，GSE延迟主要源于秋季增温，上游和下游地区GSL延长主要源于春季增温，中游地区GSL延长主要与秋季变暖有关。

关键词: 生长季, 时空演变, 变化趋势, 季节温度, 黄河流域

Abstract:

Data from 89 meteorological stations in the Yellow River Basin from 1960 to 2020 was used in this investigation. The Mann-Kendall mutation test as well as Morlet wavelet and correlation analyses were conducted to assess the spatial and temporal change characteristics and influencing factors at the beginning of the growing season (GSS), the end of the growing season (GSE), and the length of the growing season (GSL), as well as days with an active accumulated temperature of ≥10 ℃ (AT10) and active accumulated temperature of ≥10 ℃ (DT10) during the growing season. From 1960 to 2020 the GSS significantly advanced at a rate of -2.04 d·(10a)^-1, while the GSE showed a delayed trend with a change rate of 0.85 d·(10a)^-1, and the GSL was significantly prolonged at a rate of 2.88 d·(10a)^-1; there were also significant regional differences. The GSS in the lower reaches of the Yellow River Basin was the earliest (February 23), while that in the upper reaches was the latest (March 30). Furthermore, the GSE in the upper reaches ended early (October 24), while that in the lower reaches was the latest (November 30), and the GSL in lower reaches was the longest (334.03 d), while that in the upper reaches was the shortest (297.33 d). The significant extension of GSL was mainly due to the significant advance of GSS. Over the past 61 years, the growth season indices were found to have a main period of approximately 28 a in the Yellow River Basin. GSS, AT10, and DT10 mutated in 1998, and GSL mutated in 2002. The changing trends for the growth season indices in the upper, middle, and lower reaches of the Yellow River Basin were consistent, with the largest change occurring in the lower reaches, followed by the upper and middle reaches, respectively. Correlation analyses showed that GSS advances in the Yellow River Basin were mainly related to spring warming over the past 61 years, and the delay of GSE was mainly due to autumn warming, the extension of GSL in the upstream and downstream areas was mainly due to spring warming, and the extension of GSL into the middle reaches was mainly related to autumn warming.

Key words: growing season, spatial-temporal variations, trend, seasonal temperature, the Yellow River Basin

张志高, 孙梓欣, 张秀丽, 郭可欣, 李卓娅, 郝海姣, 蔡茂堂. 1960—2020年黄河流域气候生长季时空演变及成因分析[J]. 干旱区研究, 2023, 40(10): 1537-1546.

ZHANG Zhigao, SUN Zixin, ZHANG Xiuli, GUO Kexin, LI Zhuoya, HAO Haijiao, CAI Maotang. Spatial-temporal evolution and impact factors during the climatic growing season in the Yellow River Basin from 1960 to 2020[J]. Arid Zone Research, 2023, 40(10): 1537-1546.

图/表 10

图1

图2

表1

表2

图3

图4

表3

图5

表4

表5

参考文献 34

[1]	IPCC. Climate Change 2021: The Physical Science Basis[R]. Cambridge and New York: Cambridge University Press, 2021.
[2]	Linderholm H W. Growing season changes in the last century[J]. Agricultural and Forest Meteorology, 2006, 137(1-2): 1-14. doi: 10.1016/j.agrformet.2006.03.006
[3]	杨丹, 王晓峰. 黄土高原气候和人类活动对植被NPP变化的影响[J]. 干旱区研究, 2022, 39(2): 161-179.
	[Yang Dan, Wang Xiaofeng. Contribution of climatic change and human activities to changes in net primary productivity in the Loess Plateau[J]. Arid Zone Research, 2022, 39(2): 161-179.]
[4]	Asseng S, Ewert F, Martre P, et al. Rising temperatures reduce global wheat production[J]. Nature Climate Change, 2015, 5(2): 143-147. doi: 10.1038/nclimate2470
[5]	Carter T R. Changes in the thermal growing season in Nordic countries during the past century and prospects for the future[J]. Agricultural and Food Science, 1998, 7(2): 161-179. doi: 10.23986/afsci.72857
[6]	Piao S L, Friedlingstein P, Ciais P, et al. Growing season extension and its effects on terrestrial carbon flux over the last two decades[J]. Global Biogeochemical Cycles, 2007, 21(3): GB3018.
[7]	Allen M J, Sheridan S C. Evaluating changes in season length, onset, and end dates across the United States (1948-2012)[J]. International Journal of Climatology, 2016, 36(3): 1268-1277. doi: 10.1002/joc.2016.36.issue-3
[8]	Robeson S M. Increasing growing-season length in Illinois during the 20th century[J]. Climatic Change, 2002, 52(1-2): 219-238. doi: 10.1023/A:1013088011223
[9]	王连喜, 陈怀亮, 李琪, 等. 植物物候与气候研究进展[J]. 生态学报, 2010, 30(2): 447-454.
	[Wang Lianxi, Chen Huailiang, Li Qi, et al. Research advances in plant phenology and climate[J]. Acta Ecologica Sinica, 2010, 30(2): 447-454.]
[10]	刘玉洁, 葛全胜, 戴君虎. 全球变化下作物物候研究进展[J]. 地理学报, 2020, 75(1): 14-24. doi: 10.11821/dlxb202001002
	[Liu Yujie, Ge Quansheng, Dai Junhu, et al. Research progress in crop phenology under global climate change[J]. Acta Geographica Sinica, 2020, 75(1): 14-24.] doi: 10.11821/dlxb202001002
[11]	Ho C H, Lee E J, Lee I, et al. Earlier spring in Seoul, Korea[J]. International Journal of Climatology, 2006, 26(14): 2117-2127. doi: 10.1002/joc.v26:14
[12]	陶泽兴, 葛全胜, 王焕炯. 1963—2018年中国垂柳和榆树开花始期积温需求的时空变化[J]. 地理学报, 2020, 75(7): 1451-1464. doi: 10.11821/dlxb202007009
	[Tao Zexing, Ge Quansheng, Wang Huanjiong. Spatio-temporal variations in the thermal requirement of the first flowering dates of Salix babylonica and Ulmus pumila in China during 1963-2018[J]. Acta Geographica Sinica, 2020, 75(7): 1451-1464.] doi: 10.11821/dlxb202007009
[13]	Barichivich J, Briffa K R, Myneni R B, et al. Large-scale variations in the vegetation growing season and annual cycle of atmospheric CO₂ at high northern latitudes from 1950 to 2011[J]. Global Change Biology, 2013, 19(10): 3167-3183. doi: 10.1111/gcb.12283 pmid: 23749553
[14]	McCabe G J, Betancourt J L, Feng S. Variability in the start, end, and length of frost-free periods across the conterminous United States during the past century[J]. International Journal of Climatology, 2015, 35(15): 4673-4680. doi: 10.1002/joc.2015.35.issue-15
[15]	Cui L L, Shi J, Ma Y, et al. Distribution and trend in the thermal growing season in China during 1961-2015[J]. Physical Geography, 2017, 38(6): 1-18. doi: 10.1080/02723646.2016.1258885
[16]	Menzel A, Fabian P. Growing season extended in Europe[J]. Nature, 1999, 397(6721): 659. doi: 10.1038/17709
[17]	Myneni R B, Keeling C D, Tucker C J, et al. Increased plant growth in the northern high latitudes from 1981 to 1991[J]. Nature, 1997, 386(6626): 698-702. doi: 10.1038/386698a0
[18]	Piao S L, Fang J Y, Zhou L M, et al. Variations in satellite-derived phenology in China’s temperate vegetation[J]. Global Change Biology, 2006, 12(4): 672-685. doi: 10.1111/gcb.2006.12.issue-4
[19]	郭灵辉, 吴绍洪, 赵东升, 等. 近50年内蒙古地区生长季变化趋势[J]. 地理科学, 2013, 33(4): 505-512. doi: 10.13249/j.cnki.sgs.2013.04.505
	[Guo Linghui, Wu Shaohong, Zhao Dongsheng, et al. Change trends of growing season over Inner Mongolia in the past 50 years[J]. Scientia Geographica Sinica, 2013, 33(4): 505-512.] doi: 10.13249/j.cnki.sgs.2013.04.505
[20]	董满宇, 李洁敏, 王磊鑫, 等. 1960—2017年华北地区气候生长季变化特征及成因分析[J]. 地理科学, 2019, 39(12): 1990-2000. doi: 10.13249/j.cnki.sgs.2019.12.018
	[Dong Manyu, Li Jiemin, Wang Leixin, et al. Climatic characteristics of climatic growing season and impact factors in north China during 1960-2017[J]. Scientia Geographica Sinica, 2019, 39(12): 1990-2000.] doi: 10.13249/j.cnki.sgs.2019.12.018
[21]	Dong M Y, Jiang Y, Zheng C T, et al. Trends in the thermal growing season throughout the Tibetan Plateau during 1960-2009[J]. Agricultural and Forest Meteorology, 2012, 166-167: 201-206.
[22]	王苗苗, 周蕾, 王绍强, 等. 东北地区生长季长度变化及其对总初级生产力的影响分析[J]. 地理科学, 2018, 38(2): 284-292.
	[Wang Miaomiao, Zhou Lei, Wang Shaoqiang, et al. Change of growing season length and its effects on gross primary productivity in Northeast China[J]. Scientia Geographica Sinica, 2018, 38(2): 284-292.]
[23]	徐铭志, 任国玉. 近40年中国气候生长期的变化[J]. 应用气象学报, 2004, 15(3): 306-312.
	[Xu Mingzhi, Ren Guoyu. Change in growing season over China: 1961-2000[J]. Journal of Applied Meteorological Science, 2004, 15(3): 306-312.]
[24]	Xia J J, Yan Z W, Wu P L. Multidecadal variability in local growing season during 1901-2009[J]. Climate Dynamics, 2013, 41(2): 295-305. doi: 10.1007/s00382-012-1438-5
[25]	吴蓓蕾, 姜大膀, 王晓欣. 1961—2018年中国生长季变化[J]. 大气科学, 2021, 45(2): 424-434.
	[Wu Beilei, Jiang Dabang, Wang Xiaoxin. Changes in the growing season across China during 1961-2018[J]. Chinese Journal of Atmospheric Sciences, 2021, 45(2): 424-434.]
[26]	Jiang F Q, Hu R J, Zhang Y W, et al. Variations and trendonset, cessation and length of climatic growing season over Xinjiang, NW China[J]. Theoretical and Applied Climatology, 2011, 106(3-4): 449-458. doi: 10.1007/s00704-011-0445-5
[27]	Wu C Y, Wang J, Ciais P, et al. Widespread decline in winds delayed autumn foliar senescence over high latitudes[J]. Proceedings of the National Academy of Sciences, 2021, 118(16): e2015821118.
[28]	陈晓艺, 曹雯, 王晓东, 等. 淮河流域南部作物生长季农业气候资源特征分析[J]. 生态环境学报, 2018, 27(6): 1005-1015. doi: 10.16258/j.cnki.1674-5906.2018.06.003
	[Chen Xiaoyi, Cao Wen, Wang Xiaodong, et al. Analysis of agroclimatic resource characteristics of main crops growing season in the south of Huaihe River Basin[J]. Ecology and Environmental Sciences, 2018, 27(6): 1005-1015.] doi: 10.16258/j.cnki.1674-5906.2018.06.003
[29]	Frich P, Alexander L V, Della-Marta P, et al. Observed coherent changes in climatic extremes during the second half of the twentieth century[J]. Climate Research, 2002, 19(3): 193-212. doi: 10.3354/cr019193
[30]	魏凤英. 现代气候统计诊断与预测技术[M]. 北京: 气象出版社, 1999.
	[Wei Fengying. Modern Climate Statistical Diagnosis and Prediction Technology[M]. Beijing: China Meteorological Press, 1999.]
[31]	苗运玲, 于永波, 霍达, 等. 中天山北坡冬季降雪变化及其影响因子分析[J]. 干旱区研究, 2023, 40(1): 9-18.
	[Miao Yunling, Yu Yongbo, Huo Da, et al. Analysis of winter snowfall variability and its influencing factors on the north slopes of the middle Tianshan Mountains[J]. Arid Zone Research, 2023, 40(1): 9-18.]
[32]	Torrence C, Compo G P. A practical guide to wavelet analysis[J]. Bulletin of the American Meteorological Society, 1998, 79(1): 61-78. doi: 10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2
[33]	任国玉, 徐铭志, 初子莹, 等. 近54年中国地面气温变化[J]. 气候与环境研究, 2005, 10(4): 717-727.
	[Ren Guoyu, Xu Mingzhi, Chu Ziying, et al. Changes of surface air temperature in China during 1951-2004[J]. Climatic and Environmental Research, 2005, 10(4): 717-727.]
[34]	Reid P C, Hari R E, Beaugrand G, et al. Global impacts of the 1980s regime shift[J]. Global Change Biology, 2016, 22(2): 682-689. doi: 10.1111/gcb.13106 pmid: 26598217

年代	GSS		GSE		GSL		AT10		DT10
年代	均值	距平	均值	距平	均值	距平	均值	距平	均值	距平
1961—1970	79	3	309	-1	231	-4	3157	-109	183	-5
1971—1980	81	5	309	-1	229	-6	3146	-120	182	-6
1981—1990	81	5	309	-1	229	-6	3141	-125	183	-5
1991—2000	75	-1	311	1	237	2	3272	6	187	-1
2001—2010	70	-6	311	1	242	7	3424	158	196	8
2011—2020	71	-5	313	3	243	8	3467	201	196	8

地区	GSS		GSE		GSL		AT10		DT10
地区	均值	倾向率/[d·(10a)^-1]	均值	倾向率/[d·(10a)^-1]	均值	倾向率/[d·(10a)^-1]	均值	倾向率/[℃·(10a)^-1]	均值	倾向率/[d·(10a)^-1]
上游	88.81	-2.00	297.33	1.02	208.02	3.02	2472.16	73.33	156.31	3.69
中游	66.73	-1.96	318.03	0.60	252.30	2.57	3732.24	66.10	207.89	2.90
下游	53.63	-2.70	334.03	1.48	281.40	4.18	4619.85	82.95	232.88	3.15

地区	GSS				GSE				GSL
地区	春季	夏季	秋季	冬季	春季	夏季	秋季	冬季	春季	夏季	秋季	冬季
黄河流域	-0.65^**	-0.54^**	-0.44^**	-0.40^**	0.29^*	0.22	0.75^**	0.51^**	0.66^**	0.53^**	0.69^**	0.55^**
上游	-0.83^**	-0.63^**	-0.43^**	-0.38^**	0.31^*	0.40^**	0.82^**	0.52^**	0.80^**	0.69^**	0.73^**	0.55^**
中游	-0.55^**	-0.43^**	-0.38^**	-0.27^*	0.18	0.02	0.66^**	0.36^**	0.52^**	0.35^**	0.62^**	0.39^**
下游	-0.34^**	-0.13	-0.19	-0.31	0.26^*	0.03	0.42^**	0.32^*	0.41^**	0.12	0.37^**	0.28^*

1960—2020年黄河流域气候生长季时空演变及成因分析

Spatial-temporal evolution and impact factors during the climatic growing season in the Yellow River Basin from 1960 to 2020

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 10

参考文献 34

相关文章 15

Metrics

本文评价

推荐阅读 0

生长季指标	趋势检验通过率/%	趋势增加个数	显著增加个数	趋势减少个数	显著减少个数
GSS	71.9	0	0	89	65
GSE	80.9	82	71	7	1
GSL	80.9	88	72	1	0
AT10	93.3	89	83	0	0
DT10	79.8	88	71	1	0

[1]	齐润泽, 潘竟虎. 河湟地区生态脆弱性时空演变及影响因素研究[J]. 干旱区研究, 2023, 40(6): 1002-1013.
[2]	邹易, 蒙吉军. 干旱区绿洲-城镇-荒漠景观演变及生态环境效应[J]. 干旱区研究, 2023, 40(6): 988-1001.
[3]	吴玥葶, 郭利丹, 井沛然, 黄峰, 王浩轩. 中亚五国水-能源-粮食-生态耦合关系及时空分异[J]. 干旱区研究, 2023, 40(4): 573-582.
[4]	陈实, 黄银兰, 金云翔. 退耕还林（草）工程实施前后黄河中游生境质量时空变化分析[J]. 干旱区研究, 2023, 40(3): 456-468.
[5]	王鹏, 秦思彤, 胡慧蓉. 近30 a拉萨河流域土地利用变化和生境质量的时空演变特征[J]. 干旱区研究, 2023, 40(3): 492-503.
[6]	王娟, 王钊, 郭斌, 何慧娟, 董金芳. 陕西黄河流域植被碳利用率时空特征及对气候的敏感性研究[J]. 干旱区研究, 2023, 40(12): 1959-1968.
[7]	吴万民, 刘涛, 陈鑫. 西北干旱半干旱区NDVI季节性变化及其影响因素[J]. 干旱区研究, 2023, 40(12): 1969-1981.
[8]	黄莹, 王素艳, 马阳, 王岱, 张雯, 王璠. 宁夏近60 a寒潮变化特征及其环流异常[J]. 干旱区研究, 2023, 40(11): 1718-1728.
[9]	党慧, 荣丽华, 李伊彤, 赵名君. 农牧交错区三生空间时空演变特征与影响因素——以内蒙古呼和浩特市为例[J]. 干旱区研究, 2023, 40(10): 1698-1706.
[10]	姬倩倩, 潘换换, 吴树荣, 武志涛, 杜自强. 山西黄河流域“三生”空间重构和降水变化对产水服务的影响[J]. 干旱区研究, 2023, 40(1): 132-142.
[11]	高晓瑜,汤鹏程,张莎,屈忠义,杨威. 内蒙古各气候区主要作物生长季干旱特征及其与响应因子回归模型[J]. 干旱区研究, 2022, 39(5): 1410-1427.
[12]	张赟鑫,郝海超,范连连,李耀明,张仁平,李凯辉. 中亚草地NPP时空动态及其驱动因素研究[J]. 干旱区研究, 2022, 39(3): 698-707.
[13]	王澄海,杨金涛,杨凯,张飞民,张晟宁,李课臣,杨毅. 过去近60 a黄河流域降水时空变化特征及未来30 a变化趋势[J]. 干旱区研究, 2022, 39(3): 708-722.
[14]	高秉丽,巩杰,李焱,靳甜甜. 基于SPEI的黄河流域多尺度干湿特征分析[J]. 干旱区研究, 2022, 39(3): 723-733.
[15]	侯青青,陈英,裴婷婷,吉珍霞,谢保鹏. 近25 a来甘肃省耕地资源时空变化及其影响因子[J]. 干旱区研究, 2022, 39(3): 955-967.