全球变暖下青藏高原东南侧常年南风强度的多模式结果比较分析

doi:10.12006/j.issn.1673-1719.2020.114

摘要/Abstract

摘要：

青藏高原东南侧存在一个特殊区域,它常年维持南风,与东亚季风紧密联系,强度变异也将对下游天气气候造成明显影响。该区域南风对全球变暖背景下青藏高原的快速增暖十分敏感。文中利用国际耦合模式比较计划第5阶段（CMIP5）中13个模式的多情景预估结果,分析了全球变暖1.5℃、2℃和3℃下常年南风区南风强度的变异特征。结果表明,13个模式中仅BCC-CSM1.1、GFDL-CM3和MIROC5模式能够较好地模拟常年南风区的范围,以及其独特的“双峰型”季节演变特征。然而,对南风的预估,模式间存在较大差异。MIROC5模式预估南风将明显加强,尤其6月之后,并持续至12月,但BCC-CSM1.1和GFDL-CM3模式预估南风在秋季后将明显减弱。进一步分析发现,各模式预估的差异主要源于它们对青藏高原及东亚地区之间温差的模拟存在显著差异。MIROC5模式模拟的青藏高原升温幅度高于周边区域,其与东亚平原之间的温度梯度将使常年南风区南风增强。因此,模式未来改进中应特别关注对青藏高原与其周边热力梯度的合理模拟,这对青藏高原区及东亚季风气候的正确模拟至关重要。

关键词: 青藏高原, 南风变化, 变暖1.5℃, 变暖2℃, 变暖3℃

Abstract:

There is a special region on the southeast side of Tibetan Plateau. Southerly wind occurs through the whole year, which is closely related with East Asian monsoon and plays an important role in the weather and climate in its downstream region. Under global warming, rapid warming Tibetan Plateau makes this southerly sensitive. In order to estimate its future change under global warming, CMIP5 simulations were analyzed and compared. The results show that, in 13 CMIP5 models, only BCC-CSM1.1, GFDL-CM3 and MIROC5 models can well simulate the southerly region and its “double-peak” evolution feature in seasonal cycle. However, there are significant differences among models in the future change of the southerly. In MIROC5, the southerly will significantly enhance from June to December. But the southerly in BCC-CSM1.1 and GFDL-CM3 simulation will be significantly weakened after the autumn. Further analysis indicates that the difference of the southerly wind change is occasioned by the simulation difference of the thermal contrast between the Tibetan Plateau and East Asian plain. For MIROC5 simulation, the temperature increase over Tibetan Plateau is larger than its surrounding. The induced thermal contrast will further enhance the southerly wind. Therefore, Reasonable simulation of the thermal contrast between the Tibetan Plateau and its surrounding is very important for East Asian climate estimation.

Key words: The Tibetan Plateau, Change of the southerly wind, Global warming of 1.5℃, Global warming of 2℃, Global warming of 3℃

祁莉, 杨睿婷. 全球变暖下青藏高原东南侧常年南风强度的多模式结果比较分析[J]. 气候变化研究进展, 2021, 17(4): 430-443.

QI Li, YANG Rui-Ting. Variation of southerly wind on the southeast side of Tibetan Plateau under global warming: comparison among CMIP5 simulations[J]. Climate Change Research, 2021, 17(4): 430-443.

图/表 12

图1 1980—2016年平均850 hPa经向风在全年72候中南风的概率注：图中灰色阴影为南风概率超过0.9的区域,红色方框为文中定义的常年南风区（22.5°~30°N,102.5°~107.5°E）。

Fig. 1 The probability of southerly wind in 850 hPa in 1980-2016 (The shade indicates the region whose probability greater than 0.9. Red rectangle shows the study region over 22.5°-30°N, 102.5°-107.5°E)

表1 13个CMIP5全球气候模式的基本信息

Table 1 Information of 13 CMIP5 GCMs

图2 1980—2005年再分析资料及13个CMIP5模式历史模拟资料的22.5˚~30˚N平均850 hPa经向风逐候时间-经度剖面图（单位：m/s）注：阴影区表示经向风为正值,等值线间隔为2 m/s。

Fig. 2 Time-longtitude cross section of 850 hPa meridional wind (m/s) over 22.5˚-30˚N in 1980-2005 from reanalysis data and historical simulation of 13 CMIP5 models (The shade marks the southerly wind)

图3 1980—2005年再分析资料及13个CMIP5模式历史模拟资料的常年南风区区域平均850 hPa经向风的逐候演变注：黑色实线为逐候结果,粗实线为5候平滑结果。

Fig. 3 Average meridional wind (black line) (thick line indicates the moving average of 5 pentad) over the study region in 1980-2005 from reanalysis data and historical simulation of 13 CMIP5 models

图4 3个模式在历史时期和未来不同排放情景下全球平均地表气温变化曲线注：相对于1986—2005年平均,虚线是年际变化曲线,实线为9 a平滑后的结果,灰色阴影为历史时期。

Fig. 4 Time series of global mean surface temperature (relative to 1986-2005) in (a) RCP 2.6, (b) RCP 4.5, (c) RCP 6.0 and (d) RCP 8.5 scenarios (Solid lines are the 9 years running average)

表2 3个模式在4个不同排放情景下增暖分别到达1.5℃、2℃和3℃的时间

Table 2 The time when global warming reaches 1.5℃, 2℃ and 3℃ under 4 scenarios in 3 GCMs simulation

图5 3个模式在不同排放情景下常年南风区年平均经向风异常的变化曲线注：相对于1986—2005年平均,虚线是年际变化曲线,实线为9点平滑后的结果。

Fig. 5 Southerly wind anomaly (dashed lines) over the study region relative to 1985-2005 in RCP 2.6 (a), RCP 4.5 (b), RCP 6.0 (c) and RCP 8.5 (d) scenarios (Solid lines are the 9 years running average)

图6 BCC-CSM1.1模式在不同排放情景下升温阈值分别达到1.5℃、2℃和3℃时22.5˚~30˚N平均850 hPa经向风异常的时间-经度剖面图注：相对于1986—2005年平均,图中为进行了3候平滑后的结果,黑点表示达到90%的信度检验。空白图表明该模式在该种情景下21世纪末之前未达到该增温阈值。

Fig. 6 The time-longtitude cross section of the future change of 850 hPa meridional wind over 22.5˚-30˚N relative to 1986-2005 when the global warming reaches 1.5℃, 2℃ and 3℃ in RCP2.6, RCP4.5, RCP6.0, and RCP8.5 in BCC-CSM1.1 simulation (The dots marks the region reaching 90% confidence level)

图7 同图6,但为MIROC5模式

Fig. 7 Same as Fig. 6, but for MIROC5 model

图8 BCC-CSM1.1和MIROC5模式在不同排放情景下全球气温升高1.5℃时秋季30˚N的气温异常垂直剖面图

Fig. 8 Anomaly air temperature along 30˚N in autumn when global warming reaches 1.5℃ in RCP2.6, RCP4.5, RCP6.0 and RCP8.5 in BCC-CSM1.1 and MIROC5 simulation (The dots marks the region reaching 90% confidence level)

图9 BCC-CSM1.1和MIROC5模式中4个排放情景下全球气温升高1.5℃时秋季地表气温的增幅注：图中打点区通过了90%的信度检验。

Fig. 9 The future change of autumn air temperature relative to 1986-2005 when the global warming reaches 1.5℃ in BCC-CSM1.1 and MIROC5 simulations (The dots mark the region reaching 90% confidence level)

图10 BCC-CSM1.1和MIROC5在不同排放情景下全球气温升高1.5℃时,青藏高原与东亚平原间地表增温温差的逐候演变注：实线为7候滑动平均曲线,灰色阴影为8—10月。

Fig. 10 The time series of surface thermal contrast between the Tibetan Plateau and East Asian plain when the global warming reaches 1.5℃ (Gray shade marks the autumn season)

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