Journal of Arid Meteorology ›› 2026, Vol. 44 ›› Issue (3): 387-397.DOI: 10.11755/j.issn.1006-7639-2026-03-0387
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GUO Nan1(
), CHEN Xing2, ZHANG Feimin1(
), WANG Chenghai1
Received:2025-11-21
Revised:2026-03-18
Online:2026-06-30
Published:2026-07-16
通讯作者:
张飞民
作者简介:郭楠(2001—),女,硕士生,主要从事数值预报、新能源气候风险研究。E-mail: guon2023@lzu.edu.cn。
基金资助:CLC Number:
GUO Nan, CHEN Xing, ZHANG Feimin, WANG Chenghai. Climate risks of future wind and solar resource development in the Gobi desert region of China within the arid zone[J]. Journal of Arid Meteorology, 2026, 44(3): 387-397.
郭楠, 陈星, 张飞民, 王澄海. 中国干旱区沙戈荒区域未来风光资源开发的气候风险研究[J]. 干旱气象, 2026, 44(3): 387-397.
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| 资源类型 | 指标类型 | 指标名称 | 指标内容 | 指标单位 |
|---|---|---|---|---|
| 风资源 | 危险性 | 致灾因子频率 | 次 | |
| 致灾因子强度 | ||||
| 致灾因子引起的风电发电效率损失 | % | |||
| 暴露度 | 风电基地面积 | km2 | ||
| 风电基地总装机容量 | kW | |||
| 敏感性 | 垂直风切变(Zhang et al., | m·s-1 | ||
| 湍流强度(夏馨等, | ||||
| 风速 | m·s-1 | |||
| 光资源 | 危险性 | 致灾因子频率 | 次 | |
| 致灾因子强度 | ||||
| 致灾因子引起的光伏发电效率损失 | % | |||
| 暴露度 | 光伏基地面积 | km2 | ||
| 光伏基地总装机容量 | kW | |||
| 敏感性 | 向下短波辐射 | W·m-2 |
Tab.1 Climate risk indicators for wind and solar resource development
| 资源类型 | 指标类型 | 指标名称 | 指标内容 | 指标单位 |
|---|---|---|---|---|
| 风资源 | 危险性 | 致灾因子频率 | 次 | |
| 致灾因子强度 | ||||
| 致灾因子引起的风电发电效率损失 | % | |||
| 暴露度 | 风电基地面积 | km2 | ||
| 风电基地总装机容量 | kW | |||
| 敏感性 | 垂直风切变(Zhang et al., | m·s-1 | ||
| 湍流强度(夏馨等, | ||||
| 风速 | m·s-1 | |||
| 光资源 | 危险性 | 致灾因子频率 | 次 | |
| 致灾因子强度 | ||||
| 致灾因子引起的光伏发电效率损失 | % | |||
| 暴露度 | 光伏基地面积 | km2 | ||
| 光伏基地总装机容量 | kW | |||
| 敏感性 | 向下短波辐射 | W·m-2 |
Fig.3 Spatial distribution of percentage changes of frequency and intensity of different extreme events in the Gobi desert region of China during 2030-2060 relative to the historical period under different emission scenarios (Black hatched areas indicate that percentage changes pass the significance test at the 0.1 level, the same as below)
Fig.4 Interannual variations of percentage changes of frequency and intensity of different extreme events in the Gobi desert region of China during 2030-2060 relative to the historical period under different emission scenarios (* denotes that the linear trend passes the significance test at the 0.1 level, the same as below)
Fig.6 Spatial distribution of percentage changes of climate risks for wind-solar power development under the influence of different extreme events in the future SSP2-4.5 emission scenario relative to the historical period (Unit: %)
Fig.7 Interannual variations of percentage changes of climate risks of wind and solar resource development in the Gobi desert region of China during 2030-2060 relative to the historical period under different emission scenarios and extreme events
Fig.8 Box plots of percentage changes of climate risks of wind and solar resource development in the Gobi desert region of China and its sub-regions during 2030-2060 relative to the historical period under different emission scenarios and extreme events
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