| 基于CMIP6模式的黄河上游地区未来气温模拟预估 |
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| 引用本文： | 李纯,姜彤,王艳君,缪丽娟,李溯源,陈梓延,吕嫣冉.基于CMIP6模式的黄河上游地区未来气温模拟预估[J].冰川冻土,2022,44(1):171-178. |
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| 作者姓名： | 李纯 姜彤 王艳君 缪丽娟 李溯源 陈梓延 吕嫣冉 |
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| 作者单位： | 1.南京信息工程大学 地理科学学院，江苏 南京 210044;2.南京信息工程大学 大气科学学院，江苏 南京 210044 |
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| 基金项目： | 国家重点研发计划项目（2019YFC1510200）；;国家社科基金重大项目（16ZDA047）； |
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| 摘 要： | 利用第六次国际耦合模式比较计划（CMIP6）提供的5个气候模式，并结合基于地面气象站的CN05.1气象资料，评估了CMIP6模式对黄河上游地区1961—2014年气温变化的模拟能力。基于7个共享社会经济路径及代表性浓度路径（SSP-RCP）组合情景，结合多模式集合平均预估了2015—2100年黄河上游地区年均气温和季平均气温的时空变化规律。结果表明：多模式集合平均能较好地模拟黄河上游地区历史平均气温的空间分布格局与年变化。7个未来情景一致表明，2015—2100年黄河上游地区年平均气温呈现波动上升趋势［0.03～0.82 ℃?（10a）-1］。其中，低辐射强迫情景下（SSP1-1.9、SSP1-2.6及SSP4-3.4）气温先呈现增加趋势，21世纪中期到达增幅峰值，之后增温呈现放缓趋势；而中、高辐射强迫情景下（SSP2-4.5、SSP3-7.0、SSP4-6.0及SSP5-8.5）气温表现为持续上升态势。空间上，未来气温增幅显著的区域位于黄河上游西部地区；时间上，呈现夏季增温快，春季增温慢。四季增温的空间分布呈现出一致特征，表现为西部增温强于东部，北部增温强于南部。研究结果可为黄河流域水资源管理及气候变化的适应性研究提供科学依据。
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| 关 键 词： | 黄河上游地区 气温 CMIP6 多模式集合平均 预估 |
| 收稿时间： | 2020-09-29 |
| 修稿时间： | 2020-12-21 |
Simulation and estimation of future air temperature in upper basin of the Yellow River based on CMIP6 models |
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| LI Chun,JIANG Tong,WANG Yanjun,MIAO Lijuan,LI Suyuan,CHEN Ziyan,Lü Yanran.Simulation and estimation of future air temperature in upper basin of the Yellow River based on CMIP6 models[J].Journal of Glaciology and Geocryology,2022,44(1):171-178. |
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| Authors: | LI Chun JIANG Tong WANG Yanjun MIAO Lijuan LI Suyuan CHEN Ziyan Lü Yanran |
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| Institution: | 1.School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China;2.School of Atmospheric Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China |
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| Abstract: | Five global climate models from the latest released Coupled Model Intercomparison Project Phase 6 （CMIP6） and CN05.1 meteorological data are applied to evaluate annual air temperature variations in upper basin of the Yellow River from 1961 to 2014. This study focuses on characterizing the spatiotemporal and annual variations of air temperature across upper basin of the Yellow River under seven future scenarios， combing the shared socioeconomic pathways and the representative concentration pathways （SSP1-1.9， SSP1-2.6， SSP2-4.5， SSP3-7.0， SSP4-3.4， SSP4-6.0 and SSP5-8.5）. The simulation capability of CMIP6 outputs are evaluated during the historical period （1961—2014）. We find that： Multi-model ensemble mean provides good results in characterizing spatial distribution and annual variations of air temperature dynamics across the study area. The average air temperature shows a significant upward trend ［0.03~0.82 ℃?（10a）-1］ under all seven scenarios during 2015—2100. Air temperature increased and reached the peak till the middle 21st century， and showed a slowly increasing trend till the end of the century， under the low forcing scenarios （SSP1-1.9， SSP1-2.6 and SSP4-3.4）. Under the mid and high forcing scenarios （SSP2-4.5， SSP3-7.0， SSP4-6.0 and SSP5-8.5）， the annual mean air temperature showed a continuous rising trend. Regions featured with highest temperature increasing located in western part of upper basin of the Yellow River. Air temperature in summer will rise in a relatively fast speed， while that in spring is slower. Patterns of seasonal air temperature rising shows an obvious spatial distribution， relatively fast in west and slow in east， fast in north and slow in south. In the context of global warming， a reasonable estimation of the future air temperature changes in upper basin of the Yellow River is crucial for the water resources management and study on adaptions to climate change. |
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| Keywords: | upper basin of the Yellow River air temperature CMIP6 multi-model ensemble mean estimation |
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