Impact of the Zonal Oscillation of the Western Pacific Subtropical High on Subseasonal Variability of Wind Energy Resources in Eastern China
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摘要: 风电高比例接人电力系统的背景下, 10 d以上的风能资源次季节预测对电网安全稳定运行具有重要意义。本文研究了西太平洋副热带高压(WPSH)的纬向振荡及其与中国东部次季节风能资源变化的联系。结果表明, WPSH存在显著的$ 10 \sim 40 \mathrm{~d} $纬向振荡, 其纬向振荡指数(VORT)与中国东部100 m风能资源第二经验正交函数(EOF)模态的时间系数显著相关, 表现为南北偶极型。WPSH西伸期间, 中国东南沿海附近出现异常反气旋, 其西侧低层南风异常与夏季背景季风气流叠加, 增强华南—西南地区的低层经向风分量, 并对应近地面风速和风能资源增加。副高西侧南风增强区同时伴随经向风垂直切变增强和低层静力稳定度降低, 表明动力与热力条件均有利于边界层动量交换, 边界层高度变化则可能进一步调节中低层动量向近地面的输送效率。华东地区位于异常反气旋东北侧附近, 异常西北风与气候态东南风或偏南风相抵消, 低层经向风分量及近地面风速随之减小。综上所述, WPSH纬向振荡与中国东部10~40 d风能资源变化密切相关, VORT指数可作为次季节风能资源预测的潜在大尺度环流指标。
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关键词:
- 西太平洋副热带高压纬向振荡 /
- 次季节风能资源 /
- 南北偶极模态 /
- 低层经向风 /
- 边界层动量交换
Abstract: Under the scenarios of high penetration of renewable wind energy, medium-to-long-term wind energy resource forecasts beyond 10 days are crucial for power grid security and stability. This study investigates the zonal oscillation of the Western Pacific Subtropical High(WPSH)and its influence on subseasonal wind-energy variability in eastern China. The WPSH exhibits a pronounced 10-40 days zonal oscillation cycle, which is strongly linked to the second empirical orthogonal function(EOF)mode(a north-south dipole pattern)of regional wind-energy variability. During WPSH westward-extension events, an anomalous anticyclone forms near the southeastern coast of China, accompanied by enhanced low-level southerly anomalies along its western flank. These southerly anomalies superimpose onto the climatological summer monsoon flow, directly strengthening the low-level meridional wind component over South and Southwest China and thereby favoring increases in near-surface wind speed and wind energy resources. Further analysis indicates that the regions with enhanced southerly anomalies on the WPSH western flank also feature increased meridional wind vertical shear and reduced low-level static stability. This suggests that enhanced dynamic shear and reduced stability jointly improve boundary-layer momentum exchange conditions, thereby modulating the efficiency of downward momentum transfer from the lower and middle troposphere to the near-surface layer. In contrast, East China is located near the northeastern flank of the anomalous anticyclone, where anomalous northwesterlies partially offset the climatological southeasterly or southerly flow, weakening the low-level meridional wind component and leading to reductions in near-surface wind speed and wind energy resources. These results demonstrate that the zonal oscillation of the WPSH affects subseasonal wind-energy variability in eastern China by regulating low-level circulation, vertical wind shear, low-level static stability, and boundary-layer structure, and can provide a valuable large-scale circulation predictor for 10-40-day wind-energy forecasts. -
图 1 VORT指数(红实线)和s100指数(蓝虚线)的标准化时间序列(a)；VORT指数(b)和s100指数(c)的功率谱, 红实线、蓝虚线和黑实线分别表示功率谱、红噪声谱和95%置信水平；VORT指数与s100指数在-30~+30d的超前/滞后相关系数(d), 粗红线表示通过$ 95 \% $显著性检验的时段
图 2 WPSH西伸和东退事件中700 hPa位势高度3150 gpm等值线的超前/滞后合成
a、b分别为西伸事件的西伸阶段(16~0 d)和东退阶段(0~+16 d)；c、d分别为东退事件的东退阶段(-16~0 d)和西伸阶段(0~+16 d)。合成间隔为4 d。
图 4 VORT指数与100 m总风速平方及其纬向、经向分量的超前/滞后相关系数分布
$ \mathrm{a} \sim \mathrm{c} $三列依次为总风速平方$ \left(u^{2}+v^{2}\right) $、纬向风速平方$ \left(u^{2}\right) $和经向风速平方($ v^{2} $)；各行依次为-16、-12、-8、-4、0、+4、+8和+12 d。黑色打点区域表示相关系数通过95%置信水平的Student's $ t $检验。
图 5 VORT指数与700 hPa水平风(矢量)及$ 500 \sim 850 \mathrm{hPa} $经向风垂直切变(阴影)的超前/滞后相关系数分布
$ \mathrm{a} \sim \mathrm{f} $依次为—12、-8、-4、0、+4和+8 d, 黑色打点区域表示阴影相关系数通过95%置信水平检验。
图 6 VORT指数与700 hPa水平风(矢量)及1000~850 hPa低层静力稳定度(阴影)的超前/滞后相关系数分布
$ \mathrm{a} \sim \mathrm{f} $依次为—12、-8、-4、0、+4和+8 d, 黑色打点区域表示阴影相关系数通过95%置信水平检验。
图 7 VORT指数与700 hPa水平风(矢量)及行星边界层高度(阴影)的超前/滞后相关系数分布
$ \mathrm{a} \sim \mathrm{f} $依次为—12、-8、-4、0、+4和+8 d, 黑色打点区域表示阴影相关系数通过95%置信水平检验。
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[1] Wang B, Xiang B Q, Lee J Y. Subtropical High predictability establishes a promising way for monsoon and tropical storm predictions[J]. Proceedings of the National Academy of Sciences of the United States of America, 2013, 110(8): 2718-2722. [2] Tao, S., and Chen, L. (1987). A review of recent research on the East Asian summer monsoon in China. Monsoon Meteorology, 60-92. [3] Wang Y H, Chen W, Zhang J Y, et al. Relationship between soil temperature in may over Northwest China and the East Asian summer monsoon precipitation[J]. Acta Meteorologica Sinica, 2013, 27(5): 716-724. [4] Ding Y H, Sun Y, Wang Z Y, et al. Inter-decadal variation of the summer precipitation in China and its association with decreasing Asian summer monsoon Part Ⅱ: possible causes[J]. International Journal of Climatology, 2009, 29(13): 1926-1944. [5] Hu K M, Huang G, Huang R H. The impact of tropical Indian Ocean variability on summer surface air temperature in China[J]. Journal of Climate, 2011, 24(20): 5365-5377. [6] Camp J, Roberts M J, Comer R E, et al. The western Pacific subtropical high and tropical cyclone landfall: seasonal forecasts using the Met Office GloSea5 system[J]. Quarterly Journal of the Royal Meteorological Society, 2019, 145(718): 105-116. [7] Li R C Y, Zhou W. Modulation of western north Pacific tropical cyclone activity by the ISO. part Ⅰ: genesis and intensity[J]. Journal of Climate, 2013, 26(9): 2904-2918. [8] Zhao P, Chen M, Xiao D, et al. Summer Asian-Pacific oscillation and its relationship with atmospheric circulation and monsoon rainfall[J]. Acta Meteorologica Sinica, 2008, 22(4): 455-471. [9] Huang R H, Liu Y Y, Wang L, et al. Analyses of the causes of severe drought occurring in southwest China from the fall of 2009 to the spring of 2010[J]. Chinese Journal of Atmospheric Sciences, 2012, 36(3): 499-510. [10] Xu P Q, Wang L, Liu Y Y, et al. The record-breaking heat wave of June 2019 in Central Europe[J]. Atmospheric Science Letters, 2020, 21(4): e964. [11] Kittel M, Schill W P. Quantifying the Dunkelflaute: an analysis of variable renewable energy droughts in Europe[EB/OL]. arXiv: 2410.00244v4, 2024. [12] Ohlendorf N, Schill W P. Frequency and duration of low-wind-power events in Germany[J]. Environmental Research Letters, 2020, 15(8): 084045. [13] White C J, Domeisen D I V, Acharya N, et al. Advances in the application and utility of subseasonal-to-seasonal predictions[J]. Bulletin of the American Meteorological Society, 2022, 103(6): E1448-E1472. [14] Bloomfield H C, Brayshaw D J, Gonzalez P L M, et al. Sub-seasonal forecasts of demand and wind power and solar power generation for 28 European countries[J]. Earth System Science Data, 2021, 13(5): 2259-2274. [15] Grams C M, Beerli R, Pfenninger S, et al. Balancing Europe's wind-power output through spatial deployment informed by weather regimes [J]. Nature Climate Change, 2017, 7(8): 557-562. [16] Cassou C. Intraseasonal interaction between the madden-Julian oscillation and the north Atlantic oscillation[J]. Nature, 2008, 455(7212): 523-527. [17] Tedesco P, Lenkoski A, Bloomfield H C, et al. Gaussian copula modeling of extreme cold and weak-wind events over Europe conditioned on winter weather regimes[J]. Environmental Research Letters, 2023, 18(3): 034008. [18] Hersbach H, Bell B, Berrisford P, et al. The ERA5 global reanalysis[J]. Quarterly Journal of the Royal Meteorological Society, 2020, 146(730): 1999-2049. [19] Krishnamurthy V, Shukla J. Intraseasonal and interannual variability of rainfall over India[J]. Journal of Climate, 2000, 13(24): 4366-4377. [20] Ren X J, Yang D J, Yang X Q. Characteristics and mechanisms of the subseasonal eastward extension of the South Asian high[J]. Journal of Climate, 2015, 28(17): 6799-6822. [21] Zi Y C, Xiao Z N, Yan H M, et al. Sub-seasonal east-west oscillation of the western Pacific subtropical high in summer and its air-sea coupling process[J]. Climate Dynamics, 2022, 58(1): 115-135. [22] Haghshenas A, Mellado J P. Characterization of wind-shear effects on entrainment in a convective boundary layer[J]. Journal of Fluid Mechanics, 2019, 858: 145-183. [23] Park S B, Baik J J, Han B S. Role of wind shear in the decay of convective boundary layers[J]. Atmosphere, 2020, 11(6): 622. [24] Koning A M, Nuijens L, Bosveld F C, et al. Surface-layer wind shear and momentum transport from clear-sky to cloudy weather regimes over land[J]. Journal of Geophysical Research Atmospheres, 2021, 126(21): e2021JD035087. [25] Zhou B W, Chow F K. Turbulence modeling for the stable atmospheric boundary layer and implications for wind energy[J]. Flow, Turbulence and Combustion, 2012, 88(1): 255-277. [26] Porté-Agel F, Bastankhah M, Shamsoddin S. Wind-turbine and wind-farm flows: a review[J]. Boundary-Layer Meteorology, 2020, 174(1): 1-59. -
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