1. 中国农业大学水利与土木工程学院,北京,100083
2. 中国农业大学中国农业水问题研究中心,北京,100083
3. 中国科学院青藏高原研究所,北京,100101
4. 北京师范大学水科学研究院,北京,100875
[ "张文青(2000—),女,在读硕士研究生,主要从事极端气候研究。E-mail:sy20213091851@cau.edu.cn" ]
纸质出版:2023
移动端阅览
张文青, 刘浏, 伦玉蕊, 等. 青藏高原未来极端降水时空变化特征及海拔依赖性研究[J]. 水土保持学报, 2023,37(2):149-158.
ZHANG Wenqing, LIU Liu, LUN Yurui, et al. Spatial-temporal Variation Characteristics of Future Extreme Precipitation and Its Elevation Dependency over the Qinghai-Tibet Plateau[J]. 2023, 37(2): 149-158.
张文青, 刘浏, 伦玉蕊, 等. 青藏高原未来极端降水时空变化特征及海拔依赖性研究[J]. 水土保持学报, 2023,37(2):149-158. DOI: 10.13870/j.cnki.stbcxb.2023.02.018.
ZHANG Wenqing, LIU Liu, LUN Yurui, et al. Spatial-temporal Variation Characteristics of Future Extreme Precipitation and Its Elevation Dependency over the Qinghai-Tibet Plateau[J]. 2023, 37(2): 149-158. DOI: 10.13870/j.cnki.stbcxb.2023.02.018.
极端降水对青藏高原生态—水资源—农业的可持续发展具有重要影响。基于CMIP6(coupled model intercomparison project phase 6)最新发布的大气环流模式(general circulation models
GCMs)日尺度降水数据
系统评估GCMs对青藏高原历史极端降水特征的模拟能力
并对未来时期极端降水进行预估。结果表明:多模式集合(multi-model ensemble
MME)能够更好地捕捉极端降水的时空分布特征
其中R95p、SDII、R1mm、CWD和PRCP在不同高程带表现出与观测值较为一致的变化趋势
然而
CMIP6 MME再现极端降水指数变化趋势的能力随海拔增高而降低。青藏高原未来近期、中期、远期在不同共享社会经济路径与典型浓度路径组合情景(shared socioeconomic pathways and the representative concentration pathways
SSP)下的极端降水特征预估结果表明
未来时期随时间的推移和温室气体排放浓度的增加
R95p、SDII、R1mm、CWD和PRCP相对于基准期均呈显著增加趋势
并且除SDII表现为东南部增幅最为显著以外
其他4个极端降水指数的增幅呈现较为一致的由西北向东南逐渐减小的空间分布特征。此外
各极端降水指数相较于基准期的变化率在低海拔地区(<2 000 m)变异性最大
最大变化率超过200%。SDII表现出较强的海拔依赖性
SSP5-8.5情景下SDII在低(<3 500 m)、中(3 500~4 500 m)、高(>4 500 m)海拔下的相对变化率分别为-0.06%
14.45%
17.95%
表明高海拔地区极端降水强度增加更为显著。
Extreme precipitation events have important impacts on the sustainable development of ecological-water-resource-agricultural on the Qinghai-Tibet Plateau.Based on the daily precipitation datasets of General Circulation Models (GCMs) released by CMIP6(coupled model intercomparision project phase)
the ability of GCMs to simulate the characteristics of historical extreme precipitation over the Qinghai-Tibet Plateau was systematically evaluated
and the future extreme precipitation was predicted.The results showed that multi-model ensemble (MME) exhibited a better performance of capturing spatio-temporal variation characteristics of extreme precipitation.Specifically
the variation trends of R95p
SDII
R1mm
CWD
and PRCP were consistent with those of observed values in different altitude zones
while the ability of CMIP6 MME to reproduce the variation trends of extreme precipitation indices decreased increasing altitude.The predicted extreme precipitation characteristics over the Qinghai-Tibet Plateau during the future near-term
mid-term
and long-term periods under different combination scenarios of shared socioeconomic pathways and the representative concentration pathways (SSP) were implemented.With the process of time and the increase of greenhouse gas emission concentration in the future period R95p
SDII
R1mm
CWD
and PRCP all showed a significantly increasing trend compared with the baseline period.While the most significant increase of SDII occurred in the southeast
the variation patterns of R95p
R1mm
CWD
and PRCP exhibited a relatively consistent spatial distribution characteristics of decreasing from northwest to southeast.The increase in extreme precipitation intensity is most significant in the southeast.In addition
the future variability of each extreme precipitation index compared to the base period showed the most remarkable variability in lower altitude regions (<2 000 m)
with the maximum variability exceeding 200%.SDII showed a consistent increasing trend with rising elevation
and the relative changing rates of SDII under the SSP5-8.5 scenario were-0.06%
14.45%
and 17.95% at low (<3 500 m)
middle (3 500~4 500 m)
and high (>4 500 m) elevation zones
respectively
indicating that the increase of extreme precipitation intensity was more significant at higher elevations.
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