地球科学进展 ›› 2025, Vol. 40 ›› Issue (5): 441 -455. doi: 10.11867/j.issn.1001-8166.2025.037

综述与评述 上一篇    下一篇

基于位涡理论的青藏高原热力强迫数值模拟研究进展
何编1,2(), 冯适健1,2,3, 吴国雄1,2,3, 刘屹岷1,2,3, 生宸2, 何欣雨1,2,3   
  1. 1.中国科学院大气物理研究所,地球系统数值模拟与应用全国重点实验室,北京 100029
    2.中国科学院 大气物理研究所,大气科学与地球物理流体力学数值模拟国家重点实验室,北京 100029
    3.中国科学院大学 地球与行星科学学院,北京 100049
  • 收稿日期:2025-04-05 修回日期:2025-05-05 出版日期:2025-05-10
  • 基金资助:
    国家自然科学基金面上项目(42475020)

Research Progress on Numerical Simulations of the Tibetan Plateau Thermodynamic Forcing Based on Potential Vorticity Theory

Bian HE1,2(), Shijian FENG1,2,3, Guoxiong WU1,2,3, Yimin LIU1,2,3, Chen SHENG2, Xinyu HE1,2,3   

  1. 1.Key Laboratory of Earth System Numerical Modeling and Application, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
    2.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
    3.College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2025-04-05 Revised:2025-05-05 Online:2025-05-10 Published:2025-07-10
  • About author:HE Bian, research areas include Tibetan Plateau climate dynamics and modeling. E-mail: heb@lasg.iap.ac.cn
  • Supported by:
    the National Natural Science Foundation of China(42475020)

青藏高原热动力强迫作用对亚洲夏季风的形成和变化具有重要影响。然而,由于观测和数值模式本身的局限性,关于青藏高原动力和热力作用影响季风形成的相对重要性仍存在争议。针对相关理论和数值模拟问题,提出了基于位涡理论的青藏高原地表位涡强迫概念,并揭示了其与亚洲夏季风的关系。针对上述研究开展了回顾和总结,发现青藏高原动力、热力强迫影响的相对重要性与试验设计和模式模拟性能本身具有密切联系;青藏高原地表位涡指数可以作为衡量其相对重要性的一个指标;相比于感热通量,表面位涡能够更好地表征夏季高原表面的强迫作用,并可以作为量化指标评估不同数值模拟方案中高原表面强迫的强度和对季风降水的影响;从气候尺度而言,高原表面加热是导致夏季风在陆地上形成的主要因素;而从延伸期预测的角度,高原上空的热力和动力扰动时空尺度如何调控天气尺度波是影响下游降水预测的关键因子。相关理论和数值模拟研究可为进一步深化青藏高原气候动力学的认识提供参考。未来需要加强高原观测,并推动模式物理过程的发展,以进一步提高青藏高原气候数值模拟和预测水平。

The thermodynamic forcing of the Tibetan Plateau (TP) plays a crucial role in modulating the formation and variability of the Asian summer monsoon. However, due to limitations in both observational data and numerical models, the relative importance of the Plateau’s dynamic versus thermal effects on monsoon development remains a subject of ongoing debate. In recent years, a new framework based on Potential Vorticity (PV) theory has been proposed, introducing the concept of surface PV forcing over the Tibetan Plateau and revealing its relationship with the Asian summer monsoon. This paper reviews and synthesizes related research findings. Key conclusions include the following: the relative significance of TP thermodynamic forcing is closely related to experimental design and model performance; the surface PV index can serve as a quantitative metric to assess this relative significance. Compared to sensible heat flux, surface PV more accurately represents summer surface forcing over the Plateau and can be used to evaluate the strength of TP surface forcing under different model configurations and its impact on monsoonal rainfall. Climatologically, TP surface heating plays a dominant role in the formation of the summer monsoon over land. From an extended-range forecasting perspective, the spatiotemporal scales of thermodynamic disturbances over the TP that modulate synoptic-scale waves are key factors influencing the predictability of downstream precipitation. Notably, the intensity of TP surface forcing in climate system models—and its sensitivity in influencing monsoon precipitation—was quantified across different regions in 2022. Accurate simulation of TP surface PV forcing in June 2022 proved essential for reproducing the persistent rainfall observed over South China. These theoretical and modeling advancements contribute to a deeper understanding of the climatic dynamics associated with TP. However, observational data scarcity—particularly in high-elevation regions of the western TP—due to terrain and environmental constraints, limits the understanding of boundary-layer processes and results in biased physical parameterizations in climate models. Therefore, advancing TP simulation capabilities and deepening understanding of its climatic role require integrating observations, numerical modeling, and theoretical research into a unified framework. This approach will enhance the prediction of weather and climate extremes across TP and adjacent regions.

中图分类号: 

图1 不同版本AMIP试验中亚洲夏季风降水和850 hPa风场对青藏—伊朗高原地形动力热力强迫的响应(据参考文献[8]修改)
(a)CMIP5版本SAMIL模式参考试验减去无地形试验(CMIP5:CON-NTP);(b)CMIP5版本SAMIL模式参考试验减去无地形感热加热试验(CMIP5: CON-NS); (c) CMIP6版本FAMIL模式参考试验减去无地形试验(CMIP6: CON-NTP);(d)CMIP6版本FAMIL模式参考试验减去无地形感热加热试验(CMIP6: CON-NS)
Fig. 1 Response of Asian summer monsoon precipitation and 850 hPa wind field to dynamic and thermal forcing of the Tibetan-Iranian Plateau topography in different AMIP experiment versionsmodified after reference8])
(a) CMIP5 SAMIL model control experiment minus no-topography experiment (CMIP5: CON-NTP); (b) CMIP5 SAMIL model control experiment minus no topographic sensible heating experiment (CMIP5: CON-NS); (c) CMIP6 FAMIL model control experiment minus no-topography experiment (CMIP6: CON-NTP); (d) CMIP6 FAMIL model control experiment minus no topographic sensible heating experiment (CMIP6: CON-NS)
图2 青藏伊朗高原热力强迫调节海—气相互作用对亚洲夏季风影响的示意图63
青藏伊朗高原强迫的直接影响导致一个气旋环流异常在高原附近对流层低层生成,而其间接效应在高原附近形成一个反气旋式环流异常,并且伴随高原南侧的“气旋—反气旋”偶极型环流异常(细红箭头),与垂直方向上的经向环流异常耦合(粗红箭头),与高原的直接强迫作用相抵抗。其中AGCM表示单独大气试验,CGCM表示海—气耦合试验
Fig. 2 Schematic diagram of the Tibetan-Iranian Plateau thermal effect on modulating the influence of air-sea interaction on the Asian summer monsoon63
The direct effect of the Tibetan-Iranian Plateau thermal forcing generates a cyclonic circulation in the lower troposphere around the plateau, while the indirect effect generates an anticyclonic flow surrounding the plateau, and a cyclone-anticyclone circulation dipole to its south in the lower troposphere (fine red arrows), coupled with a pair of meridional circulations (bold red arrows), counteracting the Tibetan-Iranian Plateau direct impact on the Asian Summer monsoon. “AGCM” stands for atmospheric general circulation mode and “CGCM” atmosphere-ocean coupled general circulation model
图3 青藏高原地形加热对等熵面和环流影响示意图(据参考文献[7]修改)
(a)有地形加热的情况;(b)没有地形加热的情况。其中塔式地形为青藏高原,(a)中表面红粗线表示有高原地形加热;红色点线表示两层等熵面θ1θ2;黑色箭头表示环流运动;其中TP_SH表示有高原表面加热,TP_NSH表示无高原表面加热
Fig. 3 Schematic diagram of the Tibetan Plateau’s topographic heating effects on isentropic surfaces and circulationmodified after reference7])
(a) With topographic heating; (b) Without topographic heating. The stepped topography represents the Tibetan Plateau, where the thick red line in (a) indicates plateau topographic heating, red dotted lines denote two isentropic surfaces θ1 and θ2, and black arrows show circulation patterns. “TP_SH” indicates Tibetan Plateau surface heating and “TP_NSH” no Tibetan Plateau surface heating
图4 气候平均(19792019年)的各要素年循环的时间—经度分布图(25°~40°N平均并且地形高度大于500 m64
(a) GPCP观测降水(mm/d);(b) ERA5再分析的地表感热通量(W/m2);(c) ERA5再分析地表位涡[PVU,1 PVU=10-6 K·m2/(kg·s)]。黑色点线表明北半球6~8月
Fig. 4 Annual cycle time-longitude distributions25°~40°N average for elevations >500 mof climatological mean1979-2019atmospheric elements64
(a) GPCP observed precipitation (mm/d); (b) ERA5 reanalysis surface sensible heat flux (W/m²); (c) ERA5 reanalysis surface potential vorticity (PVU, 1 PVU = 10-6 K·m2/(kg·s). Black dotted lines indicate June-August in Northern Hemisphere
图5 19792019基于地表位涡指数的各气象要素合成分析图64
(a)基于ERA5再分析1979—2019年北半球夏季(JJA)青藏高原地表位涡指数(TP-SPVI)合成的夏季降水(mm/d)和850 hPa风场(m/s)异常,其中红点表明通过了99%显著性t检验的区域;(b)合成分析的夏季地表位涡(PVU)空间分布,黑色实线分别表示3 000 m和500 m以上的地形
Fig. 5 Composite analysis of atmospheric elements based on SPV index from 1979 to 201964
(a) Composite anomaly of the JJA precipitation (mm/d) and winds (m/s) at 850 hPa based on JJA TP-SPVI from 1979 to 2019 in ERA5, The red dots are statistically significant at the 99% confidence level based on a Student’s t-test; (b) Composite analysis of JJA Surface Potential Vorticity (PVU), the solid black lines denote the topography above 3 000 m and 500 m
图6 FGOALS-f2不同试验中模拟的北半球夏季平均地表位涡空间分布特征65
(a)AMIP参考试验;(b)AMIP无地形试验(A_NTP);(c)AMIP-A_NTP的试验结果(A_DIF);(d)CMIP参考试验;(e)CMIP无地形试验(C_NTP);(f) CMIP-CMIP_NTP的试验结果(C_DIF)。黑色实线代表3 000 m以上的地形,黑色虚线表示地形被去除
Fig. 6 Climate mean of the JJA SPV in different FGOALS-f2 experiments65
(a) AMIP reference experiment; (b) AMIP no-topography experiment (A_NTP); (c) Results from AMIP-A_NTP experiment (A_DIF); (d) CMIP reference experiment; (e) CMIP no-topography experiment (C_NTP); (f) Results from CMIP-CMIP_NTP experiment (C_DIF). The solid black lines denote the topography above 3 000 m, the dashed black lines denote the topography is removed
图7 不同试验中青藏高原地区3 000 m以上SPV总和的箱线图65
黑点表示数据均值,百分数分别表示A_DIF(C_DIF)相对于AMIP(CMIP)平均值的比值。AMIP:大气模式比较计划;A_NTP:AMIP无地形试验;A_DIF:AMIP-A_NTP的试验结果;CIMP:国际耦合模式比较计划;C_NTP:CMIP无地形试验;C_DIF:CMIP-CMIP_NTP的试验结果
Fig. 7 Boxplot of the total SPV above 3000 m over the Tibetan Plateau in different experiments65
The black dots denote the mean value of the datasets, and the percentages denote the mean value of the A_NTP (or A_DIF) divided by AMIP runs, and the mean value of the C_NTP (or C_DIF) divided by CMIP runs. AMIP:Atmospheric Model Intercomparison Project; A_NTP: AMIP no-topography experiment CMIP reference experiment; A_DIF: results from AMIP-A_NTP experiment; CMIP: Coupled Model Intercomparison Project Phase; C_NTP: CMIP no-topography experiment; C_DIF: results from CMIP-CMIP_NTP experiment
图8 地形扰动试验中青藏高原SPV变化对不同地区降水影响敏感性(相对比率)示意图65
柱状图上方的黑色数字表示相对比率(%),下方的黄色数字表示标准差;AMIP:大气模式比较计划,CMIP:无地形试验
Fig. 8 Map of the ratio of monsoon precipitation responses relative to the TP-SPV changes for both the AMIP and CMIP types of simulations65
The black numbers above the boxes denote the ratios (%), and the yellow numbers denote the standard deviations. AMIP: Atmospheric Model Intercomparison Project; CMIP: Coupled Model Intercomparison Project Phase
图9 202261日起报的30天回算试验和观测对比66
(a)2022 OBS为观测的2022年6月平均降水场(mm/d)和850 hPa风场(m/s);(b)2022_SST为nudging海温试验;(c)2022_TP_TA为nudging高原温度廓线试验;(d)2022_NO为无nudging试验;(e)2022_TP_TUV为nudging高原温度和风场试验;(f)2022_TP_UV为nudging高原风场试验
Fig. 9 Comparison between the 30-day hindcast experiments initialized on 1 June 2022 and observations66
(a) 2022 OBS, observed 2022 June mean precipitation field (mm/d) and 850 hPa wind field (m/s); (b) 2022_SST, the SST nudging experiment; (c) 2022_TP_TA, the TP temperature profile nudging experiment; (d) 2022_NO, the no-nudging experiment; (e) 2022_TP_TUV, the TP temperature and wind field nudging experiment; (f) 2022_TP_UV, the TP wind field nudging experiment
图10 模式预测的20226月区域平均(20°~50°N105°~140°E)的逐日降水量时间序列66
OBS为观测降水的时间序列;ALL为全球nudging T、U、V和SST试验;NO为无nudging试验;SST为nudging全球海温试验;TP_TUV为nudging高原温度和风场试验;TP_TA为nudging高原温度廓线试验;TP_UV为nudging高原风场试验。试验后面的数字为预测和观测时间序列的线性相关系数
Fig. 10 The Predicted time series of regional mean20°~50°N105°~140°Edaily precipitation evolution for June 202266
OBS represents the time series of observed precipitation; ALL refers to the global nudging experiment with T, U, V, and SST; NO refers to the experiment without nudging; SST refers to the experiment with global SST nudging; TP_TUV refers to the experiment with nudging of both temperature and wind fields over the TP; TP_TA refers to the experiment with nudging of the temperature profile over the TP; TP_UV refers to the experiment with nudging of wind fields over the TP. The numbers following the experiment names in the figure captions represent the linear correlation coefficients between the predicted and observed time series
图11 准确模拟青藏高原地表位涡及上空热力结构如何改善东亚延伸期降水预测示意图66
TP-SPV及其上空非绝热加热的准确模拟提升了模式对高原南侧低层水汽输送和中纬度高原至东亚上空天气尺度波动的预测能力,二者的准确预测有效改善了与东亚强降水相关的强上升运动的预测,因此提高了东亚夏季降水的预测水平
Fig. 11 Schematic diagram of how accurately simulated Surface Potential VorticitySPVand the thermal structure over the Tibetan PlateauTPimproves extended-range precipitation forecasts in East Asia66
Accurate simulation of TP-SPV and diabatic heating above it enhances the model’s predictive capability for low-level moisture transport south of the plateau and synoptic-scale wave activity from mid-latitude plateau to East Asia. Improved prediction of these two factors effectively refines the forecast of strong upward motion associated with heavy precipitation in East Asia, thereby enhancing the skill of summer rainfall prediction in this region
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