天气与气候

基于CMIP6模式的中国西北地区干旱时空变化

  • 山建安 ,
  • 朱睿 ,
  • 尹振良 ,
  • 杨华庆 ,
  • 张薇 ,
  • 方春爽
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  • 1.兰州交通大学测绘与地理信息学院,地理国情监测技术应用国家地方联合工程研究中心,甘肃省测绘科学与技术重点实验室,甘肃 兰州 730000
    2.中国科学院西北生态环境资源研究院,国家冰川冻土沙漠科学数据中心,干旱区生态安全与可持续发展重点实验室,甘肃 兰州 730000
    3.山东科技大学安全与环境工程学院,山东 青岛 266000
山建安(1999-),男,硕士研究生,主要从事干旱区气候变化预测. E-mail: 11220853@stu.lzjtu.edu.cn
尹振良. E-mail: yinzhenliang@lzb.ac.cn

收稿日期: 2023-11-18

  修回日期: 2024-01-21

  网络出版日期: 2024-05-29

基金资助

国家自然科学基金项目(42161018);国家自然科学基金项目(52179026);中国科学院青年创新促进会会员项目(2021424);甘肃省陇原青年创新创业人才(团队)项目(2023);新疆生产建设兵团科技攻关计划项目(2021AB021)

Spatial and temporal variation of drought in Northwest China based on CMIP6 model

  • SHAN Jian'an ,
  • ZHU Rui ,
  • YIN Zhenliang ,
  • YANG Huaqing ,
  • ZHANG Wei ,
  • FANG Chunshuang
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  • 1. National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Key Laboratory of Science and Technology in Surveying & Mapping, Gansu Province, Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730000, Gansu, China
    2. Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, National Cryosphere Desert Data Center, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, Gansu, China
    3. College of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao 266000, Shandong, China

Received date: 2023-11-18

  Revised date: 2024-01-21

  Online published: 2024-05-29

摘要

基于西北地区的152个气象台站和 CMIP6(Coupled Model Intercomparison Project 6)的16个气候模式输出资料,采用RoMBC(Robust Multivariate Bias Correction)方法对CMIP6模式数据进行偏差校正,构建标准化降水蒸散发指数(Standardized Precipitation Evapotranspiration Index,SPEI),分析西北地区历史及未来4种情景下(SSP1-2.6、SSP2-4.5、SSP3-7.0、SSP5-8.5)的干旱时空分布及变化特征。结果表明:(1) 历史和未来情景下西北地区气温和降水均呈显著增加趋势,增温速率为0.15~0.74 ℃·(10a)-1,降水增加速率为2.71~14.83 mm·(10a)-1。(2) 历史(1975—2014年)西北地区年、季节尺度SPEI整体呈下降趋势,春季下降速率最大,为0.19·(10a)-1,年、春季、冬季大部分地区干旱趋势加重,干旱频率轻中旱高于重特旱,东部干旱频率高于西部。(3) 未来情景下(2020—2100年)SSP1-2.6情景有干旱趋势但无明显干旱特征,其余3种情景干旱次数增加、干旱趋势加重、干旱频率提高,SSP5-8.5情景下干旱最为明显。该研究通过气象数据和模式数据揭示了西北地区的干旱时空发展规律,可为西北地区干旱风险评估、水资源科学管理及农业生产提供依据。

本文引用格式

山建安 , 朱睿 , 尹振良 , 杨华庆 , 张薇 , 方春爽 . 基于CMIP6模式的中国西北地区干旱时空变化[J]. 干旱区研究, 2024 , 41(5) : 717 -729 . DOI: 10.13866/j.azr.2024.05.01

Abstract

Based on data from 152 meteorological stations in Northwest China and 16 climate models of CMIP6, the CMIP6 model data were bias-corrected using the RoMBC method. The Standardized Precipitation Evapotranspiration Index (SPEI) was then constructed to analyze the spatial and temporal distribution and variation of drought in Northwest China under the historical and future scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). The results are as follows: (1) Under the historical scenario, the northwest area experienced a notable increase in both the temperature and precipitation. The temperature and precipitation have been rising at a rate of 0.15-0.74 ℃ and 2.71-14.83 mm per decade, respectively, and the same is expected for future scenarios. (2) From 1975 to 2014, the annual and seasonal SPEI in Northwest China decreased overall. The maximum decline rate in spring was 0.19 per decade. Droughts in most areas were increasingly intense throughout the year, particularly in spring and winter. In terms of drought frequency in Northwest China, mild and moderate droughts appeared more than severe and extreme droughts, and this type of natural disaster was more frequent in the east of the country than in the west. (3) From 2020 to 2100, Northwest China is likely to suffer from droughts, but there are no distinct drought characteristics identified in the research under the SSP1-2.6 scenario. The northwest region is expected to experience an increase in the number of droughts, trends in drought, and drought frequency under the other three scenarios. The most severe drought conditions were observed under the SSP5-8.5 scenario. This study provides insights into the spatial and temporal development of drought in Northwest China using meteorological and model data. The findings can serve as a basis for drought risk assessment, scientific water resources management, and agricultural production in the region.

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