Journal of Arid Meteorology ›› 2024, Vol. 42 ›› Issue (4): 485-497.DOI: 10.11755/j.issn.1006-7639(2024)-04-0485
• Special Column: Characteristics and Effects of Drought • Previous Articles Next Articles
CHEN Yixiao1(), YUE Siyu1(
), XIA Wenwen2
Received:
2024-05-22
Revised:
2024-07-18
Online:
2024-08-31
Published:
2024-09-13
通讯作者:
岳思妤(1995—),女,博士,工程师,主要从事气候变化相关研究。E-mail:作者简介:
陈逸骁(1999—),男,学士,助理工程师,主要从事气象灾害风险评估相关研究。E-mail:chenyx@cma.gov.cn。
基金资助:
CLC Number:
CHEN Yixiao, YUE Siyu, XIA Wenwen. Spatiotemporal variation characteristics of drought disaster in China and correlations with direct economic losses[J]. Journal of Arid Meteorology, 2024, 42(4): 485-497.
陈逸骁, 岳思妤, 夏雯雯. 中国干旱灾害的时空变化及其与直接经济损失的关联性研究[J]. 干旱气象, 2024, 42(4): 485-497.
Add to citation manager EndNote|Ris|BibTeX
URL: http://www.ghqx.org.cn/EN/10.11755/j.issn.1006-7639(2024)-04-0485
区域 | a | b | c | d |
---|---|---|---|---|
北方及西部地区 | 0.3 | 0.5 | 0.3 | 0.2 |
南方地区 | 0.5 | 0.6 | 0.2 | 0.1 |
Tab.1 The values of weighting coefficients of S P I W 60 , M I 30 , S P I 90 and S P I 150
区域 | a | b | c | d |
---|---|---|---|---|
北方及西部地区 | 0.3 | 0.5 | 0.3 | 0.2 |
南方地区 | 0.5 | 0.6 | 0.2 | 0.1 |
Fig.2 Time series of mean drought intensity from 1961 to 2022 (a), power spectrum of annual (b) and summer (June to August) mean drought intensity in China
Fig.7 The spatial distributions of annual mean drought-affected areas of crop damage (a) and crop failure (b), drought-affected population (c) and drought-affected direct economic losses (d) in provinces ( municipalities, autonomous region) during 2001-2022
区域 | 受灾面积/万hm2 | 绝收面积/万hm2 | 受灾人口/万人 | 直接经济损失/亿元人民币 | 单位面积直接经济损失/ (亿元人民币·万km-2) |
---|---|---|---|---|---|
北京 | 1.3 | 0.1 | 9.4 | 0.5 | 0.29 |
天津 | 2.9 | 0.1 | 10.6 | 0.3 | 0.25 |
河北 | 70.0 | 8.7 | 514.6 | 20.9 | 1.10 |
山西 | 86.8 | 12.5 | 510.5 | 32.4 | 2.03 |
内蒙古 | 177.3 | 30.2 | 398.5 | 62.3 | 0.53 |
辽宁 | 82.1 | 15.0 | 269.5 | 30.2 | 2.01 |
吉林 | 85.3 | 10.5 | 256.3 | 29.3 | 1.54 |
黑龙江 | 166.7 | 14.1 | 267.0 | 29.3 | 0.64 |
江苏 | 20.8 | 1.2 | 159.9 | 5.6 | 0.56 |
浙江 | 8.7 | 0.9 | 123.9 | 7.0 | 0.70 |
安徽 | 45.5 | 3.9 | 518.9 | 18.6 | 1.33 |
福建 | 8.9 | 0.7 | 29.5 | 4.3 | 0.36 |
江西 | 34.1 | 4.6 | 368.3 | 17.7 | 1.04 |
山东 | 54.6 | 3.2 | 424.9 | 17.3 | 1.08 |
河南 | 71.4 | 5.1 | 571.5 | 17.3 | 1.02 |
湖北 | 72.3 | 6.0 | 568.9 | 28.7 | 1.51 |
湖南 | 57.8 | 8.1 | 539.8 | 32.5 | 1.55 |
广东 | 13.9 | 0.7 | 100.5 | 2.1 | 0.12 |
广西 | 34.0 | 2.7 | 409.1 | 9.8 | 0.41 |
海南 | 5.4 | 0.4 | 49.8 | 2.4 | 0.71 |
重庆 | 24.4 | 3.8 | 307.6 | 11.9 | 1.45 |
四川 | 65.6 | 6.5 | 772.2 | 23.9 | 0.49 |
贵州 | 39.3 | 8.6 | 638.4 | 25.8 | 1.43 |
云南 | 75.4 | 10.1 | 686.6 | 36.0 | 0.92 |
西藏 | 0.9 | 0.0 | 8.3 | 0.3 | 0.00 |
陕西 | 65.8 | 6.2 | 444.5 | 20.2 | 0.96 |
甘肃 | 71.7 | 7.6 | 418.4 | 15.3 | 0.36 |
青海 | 8.9 | 0.4 | 58.2 | 3.8 | 0.05 |
宁夏 | 21.5 | 2.7 | 92.1 | 6.1 | 0.92 |
新疆 | 27.0 | 2.4 | 40.7 | 9.4 | 0.06 |
Tab.2 Statistics of average annual drought losses in provinces (municipalities, autonomous region) during 2001-2022
区域 | 受灾面积/万hm2 | 绝收面积/万hm2 | 受灾人口/万人 | 直接经济损失/亿元人民币 | 单位面积直接经济损失/ (亿元人民币·万km-2) |
---|---|---|---|---|---|
北京 | 1.3 | 0.1 | 9.4 | 0.5 | 0.29 |
天津 | 2.9 | 0.1 | 10.6 | 0.3 | 0.25 |
河北 | 70.0 | 8.7 | 514.6 | 20.9 | 1.10 |
山西 | 86.8 | 12.5 | 510.5 | 32.4 | 2.03 |
内蒙古 | 177.3 | 30.2 | 398.5 | 62.3 | 0.53 |
辽宁 | 82.1 | 15.0 | 269.5 | 30.2 | 2.01 |
吉林 | 85.3 | 10.5 | 256.3 | 29.3 | 1.54 |
黑龙江 | 166.7 | 14.1 | 267.0 | 29.3 | 0.64 |
江苏 | 20.8 | 1.2 | 159.9 | 5.6 | 0.56 |
浙江 | 8.7 | 0.9 | 123.9 | 7.0 | 0.70 |
安徽 | 45.5 | 3.9 | 518.9 | 18.6 | 1.33 |
福建 | 8.9 | 0.7 | 29.5 | 4.3 | 0.36 |
江西 | 34.1 | 4.6 | 368.3 | 17.7 | 1.04 |
山东 | 54.6 | 3.2 | 424.9 | 17.3 | 1.08 |
河南 | 71.4 | 5.1 | 571.5 | 17.3 | 1.02 |
湖北 | 72.3 | 6.0 | 568.9 | 28.7 | 1.51 |
湖南 | 57.8 | 8.1 | 539.8 | 32.5 | 1.55 |
广东 | 13.9 | 0.7 | 100.5 | 2.1 | 0.12 |
广西 | 34.0 | 2.7 | 409.1 | 9.8 | 0.41 |
海南 | 5.4 | 0.4 | 49.8 | 2.4 | 0.71 |
重庆 | 24.4 | 3.8 | 307.6 | 11.9 | 1.45 |
四川 | 65.6 | 6.5 | 772.2 | 23.9 | 0.49 |
贵州 | 39.3 | 8.6 | 638.4 | 25.8 | 1.43 |
云南 | 75.4 | 10.1 | 686.6 | 36.0 | 0.92 |
西藏 | 0.9 | 0.0 | 8.3 | 0.3 | 0.00 |
陕西 | 65.8 | 6.2 | 444.5 | 20.2 | 0.96 |
甘肃 | 71.7 | 7.6 | 418.4 | 15.3 | 0.36 |
青海 | 8.9 | 0.4 | 58.2 | 3.8 | 0.05 |
宁夏 | 21.5 | 2.7 | 92.1 | 6.1 | 0.92 |
新疆 | 27.0 | 2.4 | 40.7 | 9.4 | 0.06 |
Fig.8 The distribution of correlation coefficients between average annual drought intensity and direct economic losses (after correction) in different provinces (autonomous region, municipalities) in China during 2001-2022 (The “▲” means passing the significance test at 95% confidence level)
区域 | 受灾面积 | 绝收面积 | 受灾人口 |
---|---|---|---|
北京 | 0.420 | 0.911* | 0.411 |
天津 | 0.560* | 0.861* | 0.837* |
河北 | 0.660* | 0.654* | 0.818* |
山西 | 0.836* | 0.857* | 0.742* |
内蒙古 | 0.842* | 0.727* | 0.790* |
辽宁 | 0.681* | 0.637* | 0.914* |
吉林 | 0.747* | 0.800* | 0.860* |
黑龙江 | 0.775* | 0.444* | 0.737* |
江苏 | 0.474* | 0.114 | 0.823* |
浙江 | 0.967* | 0.938* | 0.792* |
安徽 | 0.919* | 0.812* | 0.722* |
福建 | 0.899* | 0.896* | 0.252 |
江西 | 0.860* | 0.831* | 0.828* |
山东 | 0.591* | 0.492* | 0.859* |
河南 | 0.430 | 0.356 | 0.896* |
湖北 | 0.901* | 0.863* | 0.949* |
湖南 | 0.880* | 0.866* | 0.927* |
广东 | 0.861* | 0.904* | 0.916* |
广西 | 0.798* | 0.608* | 0.682* |
海南 | 0.707* | 0.943* | 0.634* |
重庆 | 0.908* | 0.963* | 0.944* |
四川 | 0.613* | 0.517* | 0.959* |
贵州 | 0.952* | 0.982* | 0.891* |
云南 | 0.886* | 0.962* | 0.876* |
西藏 | 0.499* | 0.489* | 0.602* |
陕西 | 0.820* | 0.696* | 0.438 |
甘肃 | 0.635* | 0.670* | 0.777* |
青海 | 0.610* | 0.644* | 0.706* |
宁夏 | 0.795* | 0.711* | 0.669* |
新疆 | 0.689* | 0.481* | 0.627* |
Tab.3 Correlation coefficients between direct economic losses (after correction) and crop damage, crop failure, affected population caused by drought in different provinces (municipalities, autonomous region) from 2001 to 2022
区域 | 受灾面积 | 绝收面积 | 受灾人口 |
---|---|---|---|
北京 | 0.420 | 0.911* | 0.411 |
天津 | 0.560* | 0.861* | 0.837* |
河北 | 0.660* | 0.654* | 0.818* |
山西 | 0.836* | 0.857* | 0.742* |
内蒙古 | 0.842* | 0.727* | 0.790* |
辽宁 | 0.681* | 0.637* | 0.914* |
吉林 | 0.747* | 0.800* | 0.860* |
黑龙江 | 0.775* | 0.444* | 0.737* |
江苏 | 0.474* | 0.114 | 0.823* |
浙江 | 0.967* | 0.938* | 0.792* |
安徽 | 0.919* | 0.812* | 0.722* |
福建 | 0.899* | 0.896* | 0.252 |
江西 | 0.860* | 0.831* | 0.828* |
山东 | 0.591* | 0.492* | 0.859* |
河南 | 0.430 | 0.356 | 0.896* |
湖北 | 0.901* | 0.863* | 0.949* |
湖南 | 0.880* | 0.866* | 0.927* |
广东 | 0.861* | 0.904* | 0.916* |
广西 | 0.798* | 0.608* | 0.682* |
海南 | 0.707* | 0.943* | 0.634* |
重庆 | 0.908* | 0.963* | 0.944* |
四川 | 0.613* | 0.517* | 0.959* |
贵州 | 0.952* | 0.982* | 0.891* |
云南 | 0.886* | 0.962* | 0.876* |
西藏 | 0.499* | 0.489* | 0.602* |
陕西 | 0.820* | 0.696* | 0.438 |
甘肃 | 0.635* | 0.670* | 0.777* |
青海 | 0.610* | 0.644* | 0.706* |
宁夏 | 0.795* | 0.711* | 0.669* |
新疆 | 0.689* | 0.481* | 0.627* |
[1] | 曹丽娟, 严中伟, 2011. 地面气候资料均一性研究进展[J]. 气候变化研究进展, 7(2): 129-135. |
[2] | 程静, 彭必源, 2010. 干旱灾害安全网的构建:从危机管理到风险管理的战略性变迁[J]. 孝感学院学报, 30(4): 79-82. |
[3] | 程时雄, 何宇航, 2023. 自然灾害经济学研究新进展[J]. 经济学动态, 744(2): 143-160. |
[4] | 高歌, 李莹, 陈涛, 等, 2023. 2004—2019年中国干旱多承灾体灾损风险特征评估[J]. 气象, 49(5): 611-623. |
[5] | 高雅琦, 肖莺, 秦鹏程, 等, 2023. 2022年长江上游流域夏季干旱气候特征及成因分析[J]. 中国防汛抗旱, 33(3): 12-17. |
[6] |
韩兰英, 张强, 贾建英, 等, 2019. 气候变暖背景下中国干旱强度、频次和持续时间及其南北差异性[J]. 中国沙漠, 39(5): 1-10.
DOI |
[7] | 胡振鹏, 2023. 2022年鄱阳湖特大干旱及防旱减灾对策建议[J]. 中国防汛抗旱, 33(2): 1-6. |
[8] | 黄晚华, 杨晓光, 李茂松, 等, 2010. 基于标准化降水指数的中国南方季节性干旱近58 a演变特征[J]. 农业工程学报, 26(7): 50-59. |
[9] | 李湘阁, 胡凝, 2015. 实用气象统计方法[M]. 北京: 气象出版社: 109-111; 238-239. |
[10] | 李学军, 肖国杰, 张伟超, 2022. 1960—2019 年西宁气候变化特征分析[J]. 气候变化研究快报, 11(4): 615-621. |
[11] | 李莹, 赵珊珊, 2022. 2001—2020年中国洪涝灾害损失与致灾危险性研究[J]. 气候变化研究进展, 18(2): 154-165. |
[12] | 廖要明, 张存杰, 2017. 基于MCI的中国干旱时空分布及灾情变化特征[J]. 气象, 43(11): 1 402-1 409. |
[13] |
林纾, 李红英, 黄鹏程, 2022. 2022年夏季我国高温干旱特征及其环流形势分析[J]. 干旱气象, 40(5): 748-763.
DOI |
[14] | 梅梅, 高歌, 李莹, 等, 2023. 1961—2022年长江流域高温干旱复合极端事件变化特征[J]. 人民长江, 54(2): 12-20. |
[15] | 莫兴国, 胡实, 卢洪健, 等, 2018. GCM预测情境下中国21世纪干旱演变趋势分析[J]. 自然资源学报, 33(7): 1 244-1 256. |
[16] | 倪深海, 吕娟, 刘静楠, 等, 2022. 变化环境下我国干旱灾害演变趋势分析[J]. 中国防汛抗旱, 32(10): 1-7. |
[17] | 钱正安, 宋敏红, 吴统文, 等, 2017a. 世界干旱气候研究动态及进展综述(Ⅰ): 若干主要干旱区国家的研究动态及联合国的贡献[J]. 高原气象, 36(6): 1 433-1 456. |
[18] | 钱正安, 宋敏红, 吴统文, 等, 2017b. 世界干旱气候研究动态及进展综述(Ⅱ): 主要研究进展[J]. 高原气象, 36(6): 1 457-1 476. |
[19] | 屈艳萍, 吕娟, 张伟兵, 等, 2018. 中国历史极端干旱研究进展[J]. 水科学进展, 29(2): 283-292. |
[20] | 全国气候与气候变化标准化技术委员会, 2017. 气象干旱等级:GB/T 20 481—2017[S]. 北京: 中国标准出版社. |
[21] | 宋艳玲, 2022. 全球干旱指数研究进展[J]. 应用气象学报, 33(5): 513-526. |
[22] | 苏乃芳, 李宏瑾, 张怀清, 2016. 有关GDP平减指数的再认识[J]. 经济学动态(5): 62-73. |
[23] |
王春学, 张顺谦, 陈文秀, 等, 2019. 气象干旱综合指数MCI在四川省的适用性分析及修订[J]. 中国农学通报, 35(9): 115-121.
DOI |
[24] | 王浩, 2010. 综合应对中国干旱的几点思考[J]. 中国水利(8): 4-6. |
[25] |
王素萍, 王劲松, 张强, 等, 2020. 多种干旱指数在中国北方的适用性及其差异原因初探[J]. 高原气象, 39(3): 628-640.
DOI |
[26] |
王莺, 沙莎, 王素萍, 等, 2015. 中国南方干旱灾害风险评估[J]. 草业学报, 24(5): 12-24.
DOI |
[27] | 王莺, 王健顺, 张强, 2022a. 中国草原干旱灾害风险特征研究[J]. 草业学报, 31(8): 1-12. |
[28] | 王莺, 张强, 王劲松, 等, 2022b. 21世纪以来干旱研究的若干新进展与展望[J]. 干旱气象, 40(4): 549-566. |
[29] | 王芝兰, 奚立宗, 李耀辉, 等, 2020. 中国西北地区东部近546年干旱事件特征分析[J]. 气象学报, 78(1): 72-85. |
[30] | 夏智宏, 刘敏, 秦鹏程, 等, 2023. 2022年长江流域高温干旱过程及其影响评估[J]. 人民长江, 54(2): 21-28. |
[31] | 谢五三, 张强, 李威, 等, 2021. 干旱指数在中国东北、西南和长江中下游地区适用性分析[J]. 高原气象, 40(5): 1 136-1 146. |
[32] | 杨玮, 谢五三, 王胜, 等, 2018. 气象干旱综合监测指数在安徽省的适用性分析[J]. 气象科技, 46(5): 988-998. |
[33] | 雍燕兰, 郑雯, 赵铜铁钢, 等, 2023. 人类活动对于我国气象干旱的影响分析[J]. 水文, 43(2): 78-85. |
[34] | 张存杰, 张继权, 胡正华, 等, 2020. 干旱监测、预警及灾害风险评估技术研究[M]. 北京: 气象出版社: 4-5. |
[35] | 张强, 韩兰英, 郝小翠, 等, 2015. 气候变化对中国农业旱灾损失率的影响及其南北区域差异性[J]. 气象学报, 73(6): 1 092-1 103. |
[36] |
张强, 韩兰英, 张立阳, 等, 2014. 论气候变暖背景下干旱和干旱灾害风险特征与管理策略[J]. 地球科学进展, 29(1): 80-91.
DOI |
[37] | 张强, 李栋梁, 姚玉璧, 等, 2024. 干旱形成机制与预测理论方法及其灾害风险特征研究进展与展望[J]. 气象学报, 82(1): 1-21. |
[38] | 张强, 姚玉璧, 李耀辉, 等, 2020. 中国干旱事件成因和变化规律的研究进展与展望[J]. 气象学报, 78(3): 500-521. |
[39] | 张强, 张良, 崔显成, 等, 2011. 干旱监测与评价技术的发展及其科学挑战[J]. 地球科学进展, 26(7): 763-778. |
[40] |
张翔, 黄舒哲, 管宇航, 2023. 干旱传播的研究进展、挑战与展望[J]. 地球科学进展, 38(6): 563-579.
DOI |
[41] | 张寅, 闫凯, 刘钊, 等, 2020. 基于CRU数据的1901—2018年全球陆表气温时空变化特征分析[J]. 首都师范大学学报(自然科学版), 41(6): 51-58. |
[42] | 赵珊珊, 高歌, 黄大鹏, 等, 2017. 2004—2013年中国气象灾害损失特征分析[J]. 气象与环境学报, 33(1):101-107. |
[43] | 郑建萌, 张万诚, 万云霞, 等, 2013. 云南极端干旱年春季异常环流形势的对比分析[J]. 高原气象, 32(6): 1 665-1 672. |
[44] | 中国国家地理地图编委会, 2018. 中国国家地理地区[M]. 北京: 中国大百科全书出版社:30. |
[45] | 中国气象防灾减灾编委会, 2021. 中国气象防灾减灾[M]. 北京: 气象出版社:16. |
[46] | 周军, 任宏昌, 王蒙, 等, 2023. 2022年夏季长江流域干旱特征及成因分析[J]. 人民长江, 54(2): 29-35. |
[47] | AGHAKOUCHAK A, HUNING L, CHIANGh F, et al, 2018. How do natural hazards cascade to cause disasters?[J]. Nature, 561(7724): 458-460. |
[48] | BUDA S, HUANG J L, FISCHER T, et al, 2018. Drought losses in China might double between the 1.5 ℃ and 2.0 ℃ warming[J]. Proceedings of the National Academy of Sciences, 115(42): 10 600-10 605. |
[49] | CHEN H P, SUN J Q, 2015. Changes in drought characteristics over China using the Standardized Precipitation Evapotranspiration Index[J]. Journal of Climate, 28: 5 430-5 447. |
[50] | CHRISTIAN-SMITH J, LEVY M, GLEICK P, 2015. Maladaptation to drought: A case report from California, USA[J]. Sustainability Science, 10: 491-501. |
[51] | CUSICK T W, FLAHIVE M E, 1989. The markoff and lagrange spectra[M]. Providence, R I: American Mathematical Society. DOI:10.1090/surv/030/03 |
[52] | DI BALDASSARRE G, NOHRSTEDT D, MÅRD J, et al, 2018. An integrative research framework to unravel the interplay of natural hazards and vulnerabilities[J]. Earth’s Future, 6: 305-310. |
[53] | FAULKNER-MACDONAGH C, TAIMUR B, DECRESSIN J, et al, 2003. Deflation: determinants, risks, and policy options[J]. IMF Occasional Papers, 221. DOI: http://dx.doi.org/. |
[54] | GAO H, YANG S, 2009. A severe drought event in northern China in winter 2008-2009 and the possible influences of La Niña and Tibetan Plateau[J]. Journey of Geophysical Research Atmospheres, 114: 1-16. |
[55] | GUO Y, HUANG Q, HUANG S Z, et al, 2021. Elucidating the effects of mega reservoir on watershed drought tolerance based on a drought propagation analytical method[J]. Journal of Hydrology, 598(3), 125738. DOI: 10.1016/j.jhydrol.2020.125738. |
[56] | HAN L Y, ZHANG Q, ZHANG Z C, et al, 2021. Drought area, intensity and frequency changes in China under climate warming, 1961-2014[J]. Journal of Arid Environments, 193, 104596. DOI:10.1016/j.jaridenv.2021.104596. |
[57] | HAO Z C, SINGH V P, 2015. Drought characterization from a multivariate perspective: A review[J]. Journal of Hydrology, 527: 668-678. |
[58] | HUANG Y J, GUO M J, BAI P, et al, 2023. Warming intensifies severe drought over China from 1980 to 2019[J]. International Journal of Climatology, 43(4): 1 980-1 992. |
[59] | IPCC, 2021. Climate Change 2021-The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change[M]. Cambridge, UK: Cambridge University Press. |
[60] | LI Y, ZHAO S S, WANG G F, 2021. Spatiotemporal variations in meteorological disasters and vulnerability in China during 2001-2020[J]. Frontiers in Earth Science, 9, 789523. DOI:10.3389/feart.2021.789523. |
[61] | LIU Z C, ZHOU W, WANG X, 2024. Extreme meteorological drought events over China (1951-2022): Migration pattern, diversity of temperature extremes, and decadal variations[J]. Advances in Atmospheric Sciences. |
[62] | MA B, ZHANG B, JIA L G, et al, 2020. Conditional distribution selection for SPEI-daily and its revealed meteorological drought characteristics in China from 1961 to 2017[J]. Atmospheric Research, 246: 105-108. |
[63] | MARVEL K, COOK B I, BONFILS C, et al, 2019. Twentieth-century hydroclimate changes consistent with human influence[J]. Nature, 569(7754): 59-65. |
[64] | MISHRA A, SINGH V P, 2010. A review of drought concepts[J]. Journal of Hydrology, 391(1/2): 202-216. |
[65] | NAUMANN G, CAMMALLERI C, MENTASCHI L, et al, 2021. Increased economic drought impacts in Europe with anthropogenic warming[J]. Nature Climate Change, 11: 485-491. |
[66] | RUITER M, COUASNON A, HOMBERG M, et al, 2020. Why we can no longer ignore consecutive disasters[J]. Earth's Future, 8, e2019EF001425. DOI: 10.1029/2019EF001425. |
[67] |
SAMANIEGO L, THOBER S, KUMAR R, et al, 2018. Anthropogenic warming exacerbates European soil moisture droughts[J]. Nature Climate Change, 8: 421-426.
DOI |
[68] | STOICA P, MOSES R. 2005. Spectral analysis of signals[M]. New Jersey: Prentice Hall. |
[69] | SU X Y, HUANG G, WANG L, et al, 2024. Global drought changes and attribution under carbon neutrality scenario[J]. Climate Dynamics, https://doi.org/10.1007/s00382-024-07310-2. |
[70] | SUN C H, YANG S, 2012. Persistent severe drought in southern China during winter-spring 2011:Large-scale circulation patterns and possible impacting factors[J]. Journal of Geophysical Research, 117(D10), D10112. DOI:10.1029/2012JD017500. |
[71] | TANG B, HU W T, DUAN A M, et al, 2024. Impacts of Future Changes in Heavy Precipitation and Extreme Drought on the Economy over South China and Indochina[J]. Atmospheric Sciences, 41: 1 184-1 200. |
[72] | TRENBERTH K, DAI A, SCHRIER G, et al, 2014. Global warming and changes in drought[J]. Nature Climate Change, 4: 17-22. |
[73] | VAN LOON A F, 2015. Hydrological drought explained[J]. Wiley Interdisciplinary Reviews: Water, 2(4): 359-392. |
[74] | VAN LOON A F, Gleeson T, Clark J, et al, 2016. Drought in the Anthropocene[J]. Nature geoscience,9: 89-91. |
[75] | WALLEMACQ P, HOUSE R, 2018. Economic losses, poverty & disasters: 1998-2017[R]. DOI:10.13140/RG.2.2.35610.08643 |
[76] | WANG A H, LETTENMAIER D P, SHEFFIELD J, 2011. Soil moisture drought in China, 1950-2006[J]. American Meteorological Society, 24(13): 3 257-3 271. |
[77] | WILHITE D A, 2016. Introduction: Managing drought risk in a changing climate[J]. Climate Research,70: 99-102. |
[78] | WILKS D S, 2017. 大气科学中的统计方法[M]. 朱玉祥, 译. 3版. 北京: 气象出版社: 114-120. |
[79] | WLOSTOWSKI A N, JENNINGS K S, BASH R E, et al, 2022. Dry landscapes and parched economies: A review of how drought impacts nonagricultural socioeconomic sectors in the US Intermountain West[J]. Wiley Interdisciplinary Reviews: Water, 9(1), e1571. DOI:10.1002/wat2.1571. |
[80] | WMO, 2021. WMO atlas of mortality and economic losses from weather, climate and water extremes (1970-2019)[R]. World Meteorological Organization, WMO-NO. 1267. https://library.wmo.int/idurl/4/57564. |
[81] | WU Z Y, LU G H, WEN L, et al, 2011. Reconstructing and analyzing China's fifty-nine year (1951-2009) drought history using hydrological model simulation[J]. Hydrology and Earth System Sciences, 15(9): 2 881-2 894. |
[82] | XU K, YANG D W, YANG H B, et al, 2015. Spatio‐temporal variation of drought in China during 1961-2012: A climatic perspective[J]. Journal of Hydrology, 526: 253-264. |
[83] | YANG Q, MA Z G, FAN X G, et al, 2017. Decadal Modulation of Precipitation Patterns over Eastern China by Sea Surface Temperature Anomalies[J]. Journal of Climate, 30(17): 7 017-7 033. |
[84] | ZENG J Y, ZHANG R R, LIN Y H, et al, 2020. Drought frequency characteristics of China, 1981-2019, based on the vegetation health index[J]. Climate Research, 81: 131-147. |
[85] | ZHANG Q, HAN L Y, LIN J J, et al, 2018. North-South differences in Chinese agricultural losses due to climate-change-influenced droughts[J]. Theoretical and Applied Climatology, 131(1/2): 719-732. |
[86] | ZHANG Q, WANG Y, 2022. Distribution of hazard and risk caused by agricultural drought and flood and their correlations in summer monsoon-affected areas of China[J]. Theoretical and Applied Climatology,149: 965-981. |
[87] | ZHANG Q, YAO Y B, LI Y H, et al, 2020. Causes and Changes of Drought in China: Research Progress and Prospects[J]. Journal of Meteorological Research, 34(3): 460-481. |
[88] | ZHOU L, WU J J, MO X Y, et al, 2017. Quantitative and detailed spatio-temporal patterns of drought in China during 2001-2013[J]. Science of The Total Environment, 589: 136-145. |
[89] | ZOU X K, ZHAI P M, ZHANG Q, 2005. Variations in droughts over China: 1951-2003[J]. Geophysical Research Letters, 32(4): 353-368. |
[1] | ZHANG Cunjie, ZHANG Siqi, NING Huifang. Trends of extreme weather and climate events in China in recent 60 years and their characteristics in 2023 [J]. Journal of Arid Meteorology, 2024, 42(4): 536-552. |
[2] | LU Xiaojuan, WANG Zhilan, ZHANG Jinyu, WANG Yun, WANG Lijuan, HU Die, SHA Sha, WANG Suping, LI Yiping. The synergistic effect of sea temperature and MJO on spring drought in southwestern China in 2023 [J]. Journal of Arid Meteorology, 2024, 42(2): 166-179. |
[3] | DONG Yuanzhu, WANG Tianhe, TAN Ruiqi, WANG Sichen, JIAO Yingzi, TANG Jingyi. A comparative study of two extreme dust events in the deserts and gobi regions in the arid regions of northwest China [J]. Journal of Arid Meteorology, 2024, 42(2): 197-208. |
[4] | GAO Zhiwei, LIU Jia, CHEN Yan, Zhong Aihua. Exploration of the hysteresis response characteristics of precipitation in China to tropical Pacific sea surface temperature [J]. Journal of Arid Meteorology, 2024, 42(2): 209-216. |
[5] | HAO Lisheng, HE Liye, MA Ning, HAO Yuqian. Relationship between interannual variability of El Niño events and summer droughts in North China [J]. Journal of Arid Meteorology, 2023, 41(6): 829-840. |
[6] | LI Danhua, ZHANG Qiang, LU Guoyang, LIU Liwei, REN Yulong, BAI Bing, YANG Yang, DUAN Bolong, HUANG Pengcheng. Numerical prediction ability analysis of extended period for a typical severe sandstorm process in northern China [J]. Journal of Arid Meteorology, 2023, 41(6): 944-951. |
[7] | ZENG Yingting, LI Cheng, LIN Yan, CHEN Li, LIN Binbin. Characteristics of LAI variation in East China and its relationship with climate factors from 1982 to 2016 [J]. Journal of Arid Meteorology, 2023, 41(5): 705-713. |
[8] | GAI Changsong, CAO Lijuan, YANG Yuanyan. The application of three interpolation methods to temperature in southwestern China [J]. Journal of Arid Meteorology, 2023, 41(5): 792-801. |
[9] | ZHANG Qiang, YANG Jinhu, MA Pengli, YUE Ping, YU Haipeng, YANG Zesu, WANG Pengling, DUAN Xinyu, LIU Xiaoyun, ZHU Biao, ZHANG Hongli, LU Guoyang, WANG Youheng, LIU Weiping, LIN Jinjin, LIU Liwei, YAN Xinyang. The enhancement and eastward expansion of climate warming and humidification, formation mechanism and important environmental impacts in Northwest China [J]. Journal of Arid Meteorology, 2023, 41(3): 351-358. |
[10] | WEI Dong, SHA Hong’e, QIN Haojun, LYU Qiaoyi, LIU Liwei, FU Zhao. Comparison of cloud products of ECMWF-HR and FY-2G satellite in the central and eastern parts of Northwest China [J]. Journal of Arid Meteorology, 2023, 41(3): 483-490. |
[11] | ZHAO Hong, CAI Dihua, WANG Heling, YANG Yang, WANG Runyuan, ZHANG Kai, QI Yue, ZHAO Funian, CHEN Fei, YUE Ping, WANG Xing, YAO Yubi, LEI Jun, WEI Xingxing. Progress and prospect on impact of drought disaster on food security and its countermeasures [J]. Journal of Arid Meteorology, 2023, 41(2): 187-206. |
[12] | ZHANG Cunhou, CUI Wei, YUE Kun, ZHAO Xinghua, WU Yingjie, SEN Di. Fluctuating response of soil moisture to precipitation in arid and semi-arid areas: a case study of Damao County in desert steppe [J]. Journal of Arid Meteorology, 2023, 41(2): 260-267. |
[13] | WANG Yehong, ZHAO Yuchun. Verification and assessment of persistent rainfall forecasts of GRAPES-REPS in pre-summer of 2017 in southern China [J]. Journal of Arid Meteorology, 2023, 41(2): 328-340. |
[14] | ZHANG Wen, MA Yang, WANG Suyan, WANG Dai, LI Xin. Circulation characteristics of drought-flood transition from spring to summer over the east region of Northwest China and its relationship with Atlantic sea surface temperature [J]. Journal of Arid Meteorology, 2023, 41(1): 14-24. |
[15] | FU Zhao, LIU Weicheng, SONG Xingyu, XU Lili, SHA Honge, MA Li, CUI Yu. Local enhanced convective environment characteristics of an extreme rainstorm event in arid region of Northwest China [J]. Journal of Arid Meteorology, 2022, 40(6): 909-921. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||
©2018 Journal of Arid Meteorology
Tel: 0931-2402270、0931-2402775 Email:ghqx@iamcma.cn、ghs_ghqx@sina.com