Recent research progress on planetary waves in the middle and upper atmosphere during sudden stratospheric warmings
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摘要: 极区平流层爆发性增温(SSW)是冬季半球最剧烈的大气扰动现象之一. SSW期间温度和风场的剧烈变化被认为是冬季半球中高层大气波动能量异常增强的主要原因. 流星雷达是能够稳定连续探测中间层和低热层风场的重要地基探测设备. 主要依托国家重大科技基础设施建设项目:“子午工程”,我国已建设了多个流星雷达观测台站,对中间层和低热层风场进行了长期稳定连续的监测,为揭示SSW期间中间层和低热层波动异常变化的物理机制提供了重要的观测资料. 本文简述了近年来以我国“子午工程”流星雷达监测数据为核心,SSW期间中高层大气行星波的研究进展和成果;深入讨论了冬季半球中高层大气行星波发生异常变化的主要激发机制. 随着“子午工程”二期十个流星雷达台站即将建成,本文对利用“子午工程”流星雷达监测台网进一步研究SSW期间中高层大气波动的变化特性进行了展望.Abstract: Sudden stratospheric warming (SSW) is a violent atmospheric disturbance in the polar region of the winter hemisphere. The drastic changes in temperature and wind during SSWs are considered to be the main reasons for the abnormal increase in the energy of atmospheric waves in the upper and middle atmosphere in the winter hemisphere. Meteor radar is an important ground-based detection equipment that can stably and continuously detect neutral wind in the mesosphere and lower thermosphere (MLT) region. Based on one of the National Major Science Infrastructure Projects, the "Meridian Project", China has built several meteor radar observation stations to conduct long-term stable and continuous monitoring of the neutral wind in the MLT region, which provides important observation data for revealing the physical mechanism of abnormal changes in atmospheric waves during SSWs. Here, we briefly review the research progress on planetary waves in the middle and upper atmosphere during SSWs in recent years, especially the scientific findings based on the meteor radars in the Chinese "Meridian Project". The trigger mechanisms of the enhanced planetary waves during SSWs are discussed. With the completion of ten meteor radars in the second phase of the "Meridian Project", this paper prospects the use of its meteor radar monitoring network to further study the characteristics of atmospheric waves in the middle and upper atmosphere during SSWs.
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图 3 2019年1月5日(2018/2019 SSW发生后)北半球10 hPa位势高度分布(单位:m). 平流层极涡(蓝色)在大西洋区域(0°~60°W)发生分裂(修改自Ma et al., 2020a)
Figure 3. Distribution of geopotential height (unit: m) at 10 hPa in the Northern Hemisphere on January 5, 2019 (after the 2018/2019 SSW). The polar vortices (indicated by blue regions) are splitting over the Atlantic region (0°-60°W) (modified from Ma et al., 2020a)
图 4 2018/2019年冬季漠河站流星雷达观测的日平均经向风和纬向风(单位:m/s,北向/东向为正),在SSW发生期间(第30天附近)有明显的周期性波动(准4天波)被观测到(修改自Ma et al., 2020b)
Figure 4. Daily mean meridional (positive northward) and zonal winds (positive eastward) observed during the 2018/2019 SSW by the meteor radar at Mohe. The quasi-4-day oscillation during the SSW (around day 30) is evident in the meteor wind (modified from Ma et al., 2020b)
图 5 2020年3月SSW发生后漠河、北京及武汉站流星雷达纬向风的归一化LS周期谱图,三台流星雷达均观测到了明显的准10天周期性波动(修改自Yin et al., 2023)
Figure 5. Normalized LS periodogram of the zonal winds observed by meteor radars at Mohe, Beijing, and Wuhan after the March 2020 SSW. Quasi-10-day waves were captured at all three stations (modified from Yin et al., 2023)
图 6 2018/2019年冬季SSW期间漠河站上空经向风中准4天波的振幅(a)和相位(b),蓝色线为MERRA2再分析数据拟合结果,红色线为流星雷达观测数据拟合结果(修改自Ma et al., 2020b)
Figure 6. The amplitude (a) and phase (b) variations of the quasi-4-day wave in the meridional winds during the 2018/2019 SSW over Mohe. Fitting results derived from MERRA2 reanalysis data and meteor radar winds are presented with blue and red lines, respectively (modified from Ma et al., 2020b)
图 7 2019年9月南半球SSW期间漠河站流星雷达经向风观测数据的归一化LS谱分析结果,这次观测到的6天波振幅远大于其季节性变化,这是一次对SSW事件的跨半球响应
Figure 7. Normalized LS periodogram of the meridional winds over Mohe during the Antarctic SSW in September 2019. The amplitude of the observed quasi-6-day wave is significantly larger than the climatological level, which is an interhemispheric response to the SSW
图 8 准5天波拟合的新方法仿真结果. 仿真所使用的输入数据由6个分量合成:分别包括:(a)静态行星波波1和波2的变化以及(b)中东西向纬向波数为1和纬向波数为2的准5天振荡的变化. (c)和(d)分别展示了基于传统最小二乘拟合法和新的拟合方法所提取的准5天振荡振幅的变化(修改自Ma et al., 2022c)
Figure 8. Simulations of the new fitting method based on synthetic data, including (a) stationary planetary waves 1 and 2 and (b) westward and eastward Q5DOs with zonal wavenumbers of 1 and 2. (c) and (d) Daily amplitudes of the fitted Q5DOs obtained from the original least-square and new fitting methods (modified from Ma et al., 2022c)
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