云南初夏干湿演变特征和基于CMIP6模式模拟的预估分析

doi:10.12006/j.issn.1673-1719.2022.016

摘要/Abstract

摘要：

使用1961—2020年的观测数据和2021—2080年的模式预估数据,首先分析了云南初夏干燥度指数（aridity index,AI）的演变特征和影响因子相对贡献,然后采用国际耦合模式比较计划第六阶段（CMIP6）中的20个全球模式,对SSP1-2.6、SSP2-4.5以及SSP5-8.5情景下云南初夏未来干湿变化进行了预估研究。结果表明：(1) 1961—2020年云南初夏气候整体湿润,但为变干燥的趋势,有明显的年代际变化特征,1960s、1970s以及2000s气候相对湿润,其余年代相对干燥,2000s（2010s）为1961年以来最湿润（干燥）的10年。(2) 2021—2080年在3种排放情景下,云南初夏气候较1995—2014年均为变干燥的趋势,SSP1-2.6、SSP2-4.5以及SSP5-8.5情景下,AI分别减少13.9%、17.9%以及24.9%,西南部将可能是湿润度降幅最大值中心。(3) 1961—2020年,降水对云南初夏气候干湿变化的贡献大于潜在蒸散量;而2021—2080年,潜在蒸散量对气候变干燥的贡献大于降水量,且随排放情景的增高和时间推移,其贡献将逐渐增大。

关键词: 云南, 干湿变化, 预估, 干燥度指数（AI）

Abstract:

The dry/wet climate change in early summer has an important impact on the industrial and ecological environment in Yunnan province. In this article, the evolution characteristics of aridity index (AI) were analyzed from 1961 to 2020 using observation data, and the probable trend in 2021-2080 was projected by using 20 CMIP6 models under SSP1-2.6, SSP2-4.5 and SSP5-8.5. The AI in early summer of Yunnan province showed a decreasing trend from 1961 to 2020, and it had obvious inter-decadal change characteristics, the climate of 1960s, 1970s and 2000s was humid, and the rest period was dry, 2000s (2010s) was the wettest (driest) decade since 1961. Under three SSPs from 2021 to 2080, the climate in early summer of Yunnan will be drier than the average of 1995-2014. The regional average AI over Yunnan would decrease by 13.9%, 17.9%, and 24.9% under SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. Southwestern Yunnan will be the center of the largest decrease for wetness. The main influencing factor of climate drying is precipitation in 1961-2020, but it will be potential evapotranspiration in 2021-2080, which would increase gradually with time and the increase of emission scenario.

Key words: Yunnan province, Dry-wet climate change, Projection, Aridity index (AI)

周建琴, 黄玮, 李蒙, 郑建萌, 罗蒙, 符睿. 云南初夏干湿演变特征和基于CMIP6模式模拟的预估分析[J]. 气候变化研究进展, 2022, 18(4): 482-491.

ZHOU Jian-Qin, HUANG Wei, LI Meng, ZHENG Jian-Meng, LUO Meng, FU Rui. Dry-wet climate evolution feature and projection of future changes based on CMIP6 models in early summer over Yunnan province, China[J]. Climate Change Research, 2022, 18(4): 482-491.

图/表 10

表1 20个CMIP6全球气候模式的基本信息

Table 1 Basic information of the 20 CMIP6 global climate models used in this study

图1 1961—2020年云南初夏AI平均观测值(a)和线性变化趋势(b)的空间分布注：黑色圆点表示通过95% 信度水平的显著性检验。

Fig. 1 Spatial distributions of AI (aridity index) average (a) and linear variation trend (b) in early summer of Yunnan province during 1961-2020. (The black dots represent the 95% confidence level)

图2 1961—2020年每10年平均观测值的AI距平百分率（相对于1981—2010年）

Fig. 2 The percentage of AI anomaly per decade average from 1961 to 2020 (relative to 1981-2010)

图3 1961—2020年云南初夏AI、降水距平百分率以及潜在蒸散量距平11 a滑动平均的时间分布（相对于1981—2010年）

Fig. 3 Distribution of 11-year moving average of AI, precipitation anomaly percentage and PET anomaly in early summer in Yunnan from 1961 to 2020 (relative to 1981-2010)

图4 1961—2020年云南各站降水(a)、潜在蒸散量(b)对AI变化的贡献,降水和潜在蒸散量对AI变化贡献绝对值的差值(c)以及AI距平百分率(d)（相对于1981—2010年）

Fig. 4 Contribution of precipitation (a) and PET (b) to AI changes, the difference between absolute value of precipitation contribution and PET contribution (c) and percentage of AI anomaly during 1961-2020 (d) (relative to 1981-2010)

图5 1961—2020年云南区域每10年平均的AI距平百分率,降水量和潜在蒸散量对AI变化的贡献

Fig. 5 Regional mean to every 10-year change of AI index, contribution of precipitation and potential evapotranspiration to AI changes over Yunnan during 1961-2020

图6 2021—2080年SSP1-2.6 (a)、SSP2-4.5 (b)以及SSP5-8.5 (c)情景下20个CMIP6模式模拟的云南初夏AI距平百分率（相对于1995—2014年）

Fig. 6 The AI anomaly percentage of Yunnan in early summer from 2021 to 2080 relative to 1995-2014, as derived from 20 CMIP6 models under SSP1-2.6 (a), SSP2-4.5 (b), and SSP5-8.5 (c), respectively

表2 模式模拟的2021—2080年降水距平百分率、潜在蒸散量距平以及AI距平百分率相对于1995—2014年的变化

Table 2 Projected precipitation anomaly percentage, PET anomaly and AI anomaly percentage in Yunnan during 2021-2080 relative to 1995-2014

图7 同图6,但为潜在蒸散量距平

Fig. 7 The same as Fig. 6, but for anomaly of PET

图8 SSP1-2.6 (a),SSP2-4.5 (b)以及SSP5-8.5 (c)排放情景下2021—2080年每10年平均的20个模式集合平均的AI距平百分率,降水量和潜在蒸散量对AI变化的贡献

Fig. 8 AI anomaly percentage, contribution of regional precipitation and PET to the AI changes during 2021-2080 (a) SSP1-2.6, (b) SSP2-4.5, and (c) SSP5-8.5

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