基于CMIP6多模式预估数据的石羊河流域未来气候变化趋势分析

doi:10.13866/j.azr.2023.10.02

干旱区研究 ›› 2023, Vol. 40 ›› Issue (10): 1547-1562.doi: 10.13866/j.azr.2023.10.02

基于CMIP6多模式预估数据的石羊河流域未来气候变化趋势分析

戴君^1,²(),胡海珠^1,²(),毛晓敏^2,³,张霁^2,⁴

1.内蒙古大学生态与环境学院，内蒙古自治区河流与湖泊生态重点实验室，内蒙古呼和浩特 010020
2.甘肃武威绿洲农业高效用水国家野外科学观测研究站，甘肃武威 733009
3.中国农业大学水利与土木工程学院，北京 100083
4.武威市水务局，甘肃武威 733099

收稿日期:2023-02-27 修回日期:2023-05-05 出版日期:2023-10-15 发布日期:2023-11-01
通讯作者: 胡海珠. E-mail: huhaizhu@imu.edu.cn
作者简介:戴君（1998-），女，硕士研究生，主要从事水文与水资源研究. E-mail: 1317330302@qq.com
基金资助:
国家自然科学基金重大项目课题(51790535);甘肃武威绿洲农业高效用水国家野外科学观测研究站开放课题(KF2021007)

Future climate change trends in the Shiyang River Basin based on the CMIP6 multi-model estimation data

DAI Jun^1,²(),HU Haizhu^1,²(),MAO Xiaomin^2,³,ZHANG Ji^2,⁴

1. School of Ecology and Environment, Inner Mongolia Key Laboratory of River and Lake Ecology, Inner Mongolia University, Hohhot 010020, Inner Mongolia, China
2. National Field Scientific Observation and Research Station on Efficient Water Use of Oasis Agriculture in Wuwei of Gansu Province, Wuwei 733009, Gansu, China
3. College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China
4. Wuwei Municipal Water Bureau, Wuwei 733099, Gansu, China

Received:2023-02-27 Revised:2023-05-05 Online:2023-10-15 Published:2023-11-01

摘要/Abstract

摘要：

石羊河流域地处我国西北干旱区和季风区边缘，流域内绿洲农业的快速发展导致水资源开发利用程度极高，生态环境脆弱，未来气候变化加剧了流域水资源的不确定性，对粮食安全与经济发展构成威胁。本文基于观测数据，评估第6次国际耦合模式比较计划（CMIP6）的11个气候模式在石羊河流域的模拟能力，用等距离累积分布函数法对气候数据进行降尺度，得到该流域的未来气候变化趋势。结果表明：（1）CMIP6模式数据在石羊河流域具有良好的适用性，多模式集合平均数据对石羊河流域降水和气温的模拟性能均优于其他模式。（2）未来不同情景下（2023—2100年），流域内降水量、气温和潜在蒸散发量均呈显著上升趋势，且随着辐射强迫增加而增大。（3）未来时期石羊河流域的干燥度指数整体减小，流域气候趋向暖湿化，且民勤盆地是流域内对气候变化最敏感的地区。研究结果对于石羊河流域应对气候变化、保障经济和农业可持续发展具有重要的参考价值。

关键词: CMIP6, 石羊河流域, 区域气候变化, 干燥度指数, 未来

Abstract:

Due in large part to global climate change, drought, flood, and high temperature events have increased significantly around the world in recent years. The Shiyang River Basin is in Northwest China and fringes onto a monsoon region, and is consequently, highly sensitive to climate change. The rapid development of oasis agriculture has led to high levels of development and the utilization of water resources in fragile ecological environments. Future climate change will aggravate the uncertainty of water resources in the basin, posing a threat to food security and economic development. Coupled General Circulation Models (GCMs) play an important role in the prediction of future climate change and formulation strategies to help devise adjustments accordingly. Based on the observed data in the historical period (1985-2014), the simulation capabilities of 11 climate models from the 6th international Coupled Model Intercomparison Program (CMIP6) in the Shiyang River Basin were evaluated. The equidistant cumulative distribution function method was applied to downscale climate data to obtain the future climate change trend for the basin as presented in this paper. The results show that the CMIP6 multi-model ensemble has good applicability in the Shiyang River Basin, as it accurately depicts the annual and seasonal distribution characteristics of climate factors, including precipitation, temperature, and potential evapotranspiration. The model performs well when simulating temperatures, in comparison to precipitation. While multimodel ensemble mean data perform better when simulating precipitation and temperature in the Shiyang River Basin, in comparison with other models. Under different future scenarios (2023-2100), precipitation, temperature, and potential evapotranspiration in the basin show a significant upward trend and increase with the radiative forcing increase. The late 21 century shows a greater increase in climate factors than the early and middle periods. Compared to the historical period, precipitation in the future could increase by 45.02% in the winter and 0.38% in the summer, and the greatest temperature increases can occur in spring and autumn. In the future, the aridity index of the Shiyang River Basin will decrease overall. The climate of the basin will tend to warm and humidify, with the summer season becoming drier while the other seasons become wetter than those in the historical period. The Minqin Basin located in the lower reaches of the basin is the area most sensitive to climate change. The research results have important reference value as they will help to address future climate change and ensure sustainable economic and agricultural development in the Shiyang River Basin.

Key words: CMIP6, Shiyang River Basin, regional climate change, dryness index, future

戴君, 胡海珠, 毛晓敏, 张霁. 基于CMIP6多模式预估数据的石羊河流域未来气候变化趋势分析[J]. 干旱区研究, 2023, 40(10): 1547-1562.

DAI Jun, HU Haizhu, MAO Xiaomin, ZHANG Ji. Future climate change trends in the Shiyang River Basin based on the CMIP6 multi-model estimation data[J]. Arid Zone Research, 2023, 40(10): 1547-1562.

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模式名称	国家	所属机构	分辨率（纬度×经度）
ACCESS-ESM1-5	澳大利亚	英联邦科学和工业研究组织（CSIRO）	1.875°×1.24°
CanESM5	加拿大	加拿大气候建模和分析中心（CCCma）	2.8125°×2.8125°
EC-Earth3	瑞典	欧共体地球联合会（EC）	0.703°×0.703°
FGOALS-g3	中国	中国科学院大气物理研究所（CAS）	2.0°×2.0°
GFDL-ESM4	美国	美国国家海洋和大气管理局地球物理流体动力学实验室（GFDL）	1.25°×1.0°
INM-CM4-8	俄罗斯	俄罗斯科学院数值数学研究所（INMRAS）	2.0°×1.5°
IPSL-CM6A-LR	法国	皮埃尔-西蒙拉普拉斯学院（IPSL）	2.5°×1.25°
MIROC6	日本	日本海洋地球科学技术厅（JAMSTEC）	1.40625°×1.40625°
MPI-ESMl-2-LR	德国	马克斯普朗克气象研究所（MPI-M）	1.875°×1.875°
MRI-ESM2-0	日本	日本气象厅气象研究所（JMA）	1.125°×1.126°
NorESM2-MM	挪威	挪威气候中心（NorCC）	1.25°×0.9375°

干湿状态	分级标准
湿润	AI≤ 1.0
半湿润	1.0<AI≤ l.5
半干旱	1.5<AI≤ 4.0
干旱	4.0<AI≤ l6.0
极干旱	AI>16.0

排放情景	降水变化 /[mm·（10a）^-1]	气温变化 /[℃·（10a）^-1]	潜在蒸散发变化 /[mm·（10a）^-1]
SSP1-2.6	2.19^*（-11.63~7.98）	0.04^*（-0.02~0.14）	0.44^*（-3.73~5.01）
SSP2-4.5	6.70^**（0.29~14.86）	0.24^**（0.08~0.42）	3.27^**（-1.03~8.06）
SSP3-7.0	8.27^**（0.57~17.77）	0.51^**（0.36~0.86）	8.38^**（2.70~21.14）
SSP5-8.5	10.75^**（0.65~23.48）	0.67^**（0.43~1.11）	11.35^**（-0.21~18.77）

基于CMIP6多模式预估数据的石羊河流域未来气候变化趋势分析

Future climate change trends in the Shiyang River Basin based on the CMIP6 multi-model estimation data

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模式	降水					气温					综合排名
模式	r	RMSE	SD	S_T	M_R	r	RMSE	SD	S_T	M_R	综合排名
ACCESS-ESM1-5	11	7	2	10	9	6	6	8	6	7	8
CanESM5	2	8	11	1	5	12	10	12	10	11	9
EC-Earth3	7	4	6	4	3	8	4	4	3	4	2
FGOALS-g3	8	3	3	7	4	5	3	2	5	3	3
GFDL-ESM4	6	5	7	6	6	3	5	9	4	5	4
INM-CM4-8	9	12	12	12	12	2	2	5	2	2	6
IPSL-CM6A-LR	5	1	5	2	2	10	11	10	11	10	5
MIROC6	4	10	9	8	10	9	12	11	12	12	12
MPI-ESMl-2-LR	12	11	8	11	11	7	9	3	8	8	11
MRI-ESM2-0	10	6	1	9	7	11	7	6	7	9	10
NorESM2-MM	3	9	10	5	8	4	8	1	9	6	7
MME	1	2	4	3	1	1	1	7	1	1	1

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