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基于多源资料的高原低涡源地研究

林志强 郭维栋 姚秀萍 杜军 葛骏 周振波

林志强, 郭维栋, 姚秀萍, 等. 2023. 基于多源资料的高原低涡源地研究[J]. 大气科学, 47(3): 837−852 doi: 10.3878/j.issn.1006-9895.2211.21262
引用本文: 林志强, 郭维栋, 姚秀萍, 等. 2023. 基于多源资料的高原低涡源地研究[J]. 大气科学, 47(3): 837−852 doi: 10.3878/j.issn.1006-9895.2211.21262
LIN Zhiqiang, GUO Weidong, YAO Xiuping, et al. 2023. Reexamine the Tibetan Plateau Vortices Sources Based on Multiple Resource Datasets [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(3): 837−852 doi: 10.3878/j.issn.1006-9895.2211.21262
Citation: LIN Zhiqiang, GUO Weidong, YAO Xiuping, et al. 2023. Reexamine the Tibetan Plateau Vortices Sources Based on Multiple Resource Datasets [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(3): 837−852 doi: 10.3878/j.issn.1006-9895.2211.21262

基于多源资料的高原低涡源地研究

doi: 10.3878/j.issn.1006-9895.2211.21262
基金项目: 国家自然科学基金项目42030611、42165005,第二次青藏高原综合科学考察研究项目2019QZKK0103、2019QZKK0105,高原与盆地暴雨灾害四川省重点实验室开放基金项目SZKT202107,成都信息工程大学科技创新能力提升计划重大项目KYTD202201
详细信息
    作者简介:

    林志强,男,1982年出生,博士,主要从事高原气象学研究。E-mail: linzq@cuit.edu.cn

    通讯作者:

    郭维栋,E-mail: guowd@nju.edu.cn

  • 中图分类号: P448

Reexamine the Tibetan Plateau Vortices Sources Based on Multiple Resource Datasets

Funds: National Natural Science Foundation of China (Grants 42030611, 42165005), Second Tibetan Plateau Scientific Expedition and Research Program (Grants 2019QZKK0103, 2019QZKK0105), Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province (Grant SZKT202107), Key Grant Project of Science and Technology Innovation Capacity Improvement Program of Chengdu University of Information Technology(Grant KYTD202201)
  • 摘要: 高原低涡是活跃于青藏高原近地面层的中尺度天气系统,是高原最重要的降水天气系统,少部分的低涡移出高原后在下游地区常带来灾害性的强降水天气。“青藏高原低涡切变线年鉴”(简称年鉴)是高原低涡研究的主要参考资料之一,但受到高原西部地区探空观测站点分布不足的影响,年鉴难以监测发源于高原西部的低涡。为了进一步提高对高原低涡源地的科学认识,本研究首先分析了影响高原低涡发生发展的环流在高原东西部地区的差异,结果表明高原西部地区的环流背景更有利于高原低涡形成。再利用2005~2019年暖季(5~9月)风云-2地球静止卫星观测的云迹风和黑体亮温资料对年鉴低涡进行重分析,表明年鉴中大部分的高原低涡可以溯源至高原西部地区。最后分析了在高原西部的3个新探空站(狮泉河、改则和申扎)建立前后年鉴中高原低涡源地的差异,发现增加的探空资料使位于高原西部的低涡源地大幅度增加。综合多源资料的结果,我们认为大多数高原低涡起源于高原西部,年鉴的结论可能源于高原西部的探空站不足的影响。本研究确认了再分析资料在高原低涡研究中的可用性和有效性,强调了卫星观测资料在高原天气系统研究中的重要性和进一步增强高原地区气象观测的迫切性。
  • 图  1  青藏高原及其周边地区的海拔高度(阴影)和气象探空站点分布,其中蓝色实心方块为2015年之后新增加的探空站,黑色粗线为青藏高原3000 m廓线

    Figure  1.  Topography (shading) and the meteorological sounding stations over the Tibetan Plateau (TP) and its surrounding areas. Blue solid cubes indicates the meteorological sounding stations constructed after 2015, and the black thick line denotes the boundary of the TP at 3000 m

    图  2  高原低涡(a)年鉴和(b)ERA5、(c)CFSR、(d)MERRA2、(e)JRA55、(f)CRA40再分析资料的客观识别结果2001~2019年年平均高原低涡源地空间分布。黑色虚线以90°E将高原分为东、西两部分,图中虚线两侧的数字分别给出了高原低涡生成于高原东西部的比例。蓝色方框分别给出了高原东部和西部高原低涡的主要生成区域

    Figure  2.  Spatial distribution of the TPV sources during 2001–2019 derived from (a) the yearbook and the reanalysis datasets of (b) ERA5, (c) CFSR, (d) MERRA2, (e) JRA55, and (f) CRA40. The black dashed line divides the TP into the eastern and western parts by 90°E, and the number denotes the proportion of TPVs generated from the western and eastern TP. The blue rectangle indicates the dominant region of the TPV sources

    图  3  基于ERA5的再分析资料计算的2001~2019年5~9月的平均环流物理量的空间分布:(a)500 hPa相对涡度(单位:1.0×10−5 s−1);(b)高原东、西部的平均相对涡度;(c)400 hPa垂直速度(单位:10−1 Pa s−1);(d)高原东、西部的平均垂直速度。蓝色方框分别给出了高原东部和西部的范围,用于计算(b、d)的区域平均,其中90°E上的值不计入计算。(b、d)中圆点表示区域平均值,矩形上下位置表示平均值±标准差,长横线表示中位数,上、下的短横线分别表示95%和5%分位数

    Figure  3.  Spatial distributions of the large-scale circulation parameters in the warm season (May–September) during 2001–2019 via ERA5: (a) relative vorticity in 500 hPa (units: 1.0×10−5 s−1), (b) average relative vorticity over the eastern and western TP, (c) vertical velocity in 400 hPa (units: 10−1 Pa s−1), and (d) average velocity over the eastern and western TP. The blue rectangles denote the western and eastern TP to calculate the regional mean in panels (b, d). In panels (b, d), the dot, rectangle, and horizontal line denote the average value, the median, and the range of standard deviation, and the top and bottom error bars indicate the 95% and 5% percentiles, respectively

    图  4  基于ERA5的再分析资料计算的2001~2019年5~9月的平均环流物理量的空间分布:(a)地面感热(单位:W m−2);(b)高原东、西部的平均地面感热;(c)500 hPa散度(单位:1.0×10−6 s−1);(d)高原东、西部的平均500 hPa散度。蓝色方框分别给出了高原东部和西部的范围,用于计算(b、d)的区域平均,其中90°E上的值不计入计算。(b、d)中圆点表示区域平均值,矩形上下位置表示平均值±标准差,长横线表示中位数,上、下的短横线分别表示95%和5%分位数

    Figure  4.  Spatial distributions of the large-scale circulation parameters in the warm season (May–September) during 2001–2019 via ERA5: (a) Sensible heat flux (units: W m−2); (b) average sensible heat flux over the eastern and western TP; (c) divergence in 500 hPa (units: 1.0×10−6 s−1); (d) average divergence in 500 hPa over the eastern and western TP. The blue rectangles denote the western and eastern TP to calculate the regional mean in panels (b, d). In panels (b, d), the dot, rectangle, and horizontal line denote the average value, the median, and the range of standard deviation, and the top and bottom error bars indicate the 95% and 5% percentiles, respectively

    图  5  由ERA5月平均数据2001~2019年计算的高原低涡生成指数:(a)GTPV指数;(b)GQian指数。图中百分数字为低涡生成指数计算的90°E以东和以西区域生成的低涡百分比,在计算区域的低涡百分比时将GQian小于0的区域取为0

    Figure  5.  Spatial distribution of the TPV generation index during 2001−2019 via ERA5 with (a) GTPV and (b) GQian. The proportion of TPVs generated in the western and eastern TP are shown in the panels, and it has been calculated as 0 in the region with negative GQian

    图  6  对流层中层(600~400 hPa)的(a)长波红外通道(IR1, 10.3~11.3 μm)和(b)水汽通道(IR3, 6.5~7.0 μm)对应的亮温概率分布函数

    Figure  6.  Distributions of blackbody bright temperature in the mid-troposphere (600–400 hPa) derived from (a) the IR1 channel and (b) the IR3 channel

    图  7  对流层中层云迹风在2005~2019年5~9月的平均有效观测时次比例:(a)IR1通道;(b)IR3通道。当每个1°×1°网格至少有一个云迹风矢量时即认为该时次在该网格为一个有效观测

    Figure  7.  Data available ratio of the atmospheric motion vector (AMV) in the mid-troposphere during the warm season of 2005–2019 derived from (a) the IR1 channel and (b) the IR3 channel. It is defined as a valid observation with at least one AMV in each grid of 1°×1°

    图  8  2005~2019年5~9月逐月的有效观测覆盖率:(a)IR1通道;(b)IR3通道。红色线条为高原西部,蓝色线条为高原东部地区

    Figure  8.  Monthly available ratio of AMV observation in the warm season during 2005–2019 derived from (a) the IR1 channel and (b) the IR3 channel. The red and blue lines indicate the western and eastern TP, respectively

    图  9  2005~2019年5~9月利用卫星遥感产品判识的年鉴高原低涡源地的变化:(a)年鉴涡源位置;(b)经过卫星遥感产品校正的高原低涡涡源位置

    Figure  9.  TPV sources via the yearbook and the modulation by the satellite datasets in the warm season during 2005–2019: (a) the TPV sources via the yearbook; (b) the TPV sources modulated by the satellite datasets

    图  10  2018年8月(a)8日08:00和(b)10日08:00高原及其邻近地区高空观测的500 hPa风场。其中■为高原西部新增的气象探空站;△、●分别为不考虑和考虑新增气象探空站识别得到的低涡中心

    Figure  10.  Wind vectors in 500 hPa and the identification of TPVs at (a) 0800 BJT (Beijing time) on August 8, 2018, and (b) 0800 BJT on August 10, 2018. ■ denotes the new meteorological sounding stations over the western TP, △ and ● indicate the TPV center identified without and with the new meteorological sounding stations, respectively

    图  11  增加高原西部探空站之前(2001~2014年,黑色)和之后(2015~2019年,灰色)年鉴的不同经度范围(每5°经度为间隔)高原低涡源地的相对频次

    Figure  11.  Proportion of TPV sources via the yearbook in every 5° latitudes before (black line, 2001–2014) and after (gray line, 2015–2019) the era of new meteorological sounding stations over the western TP

    图  12  2017年5月15~17日的高原低涡(a)年鉴(编号:C1716)中的活动路径以及(b)ERA5、(c)CFSR、(d)MERRA2、(e)JRA55、(f)CRA40再分析资料对应的低涡路径。图中□表示低涡源地,等值线为再分析资料在2017年5月16日08:00的500 hPa高度场,●表示2017年5月16日08:00的低涡位置

    Figure  12.  TPV trajectory derived from (a) the yearbook (identified as C1716) and the reanalysis datasets of (b) ERA5, (c) CFSR, (d) MERRA2, (e) JRA55, and (f) CRA40 from May 15 to May 17, 2017. Contours shows the geopotential height in 500 hPa at 0800 BJT on May 16, 2017, □ denotes the TPV source, and ● denotes the TPV at 0800 BST (Beijing Standard Time) on May 16, 2017

    表  1  风云-2系列静止气象卫星数据

    Table  1.   Basic information about the FY-2 stationary meteorological satellite datasets

    卫星编号时段空间分辨率(经度×纬度)云迹风时间分辨率TBB时间分辨率
    FY-2C2005年6月至2009年12月0.1°×0.1°6 h1 h
    FY-2D2007年2月至2015年5月0.1°×0.1°6 h1 h
    FY-2E2010年1月至2019年1月0.1°×0.1°6 h1 h
    FY-2F2012年11月至2019年12月0.1°×0.1°6 h1 h
    FY-2G2015年6月至2019.12月0.1°×0.1°3 h1 h
    FY-2H2018年9月至2019.12月0.1°×0.1°0.5 h1 h
    下载: 导出CSV

    表  2  高原低涡年鉴和基于再分析分析及其获取的高原低涡概况

    Table  2.   Basic information about the Tibetan Plateau vortices derived from the yearbook and the reanalysis datasets

    数据单位国家/地区空间分辨率
    (经度×纬度)
    资料年限2001~2019年均
    高原低涡个数
    2001~2019年暖季
    平均高原低涡个数
    年鉴IPM中国2001~201945.531.7
    ERA5ECMWF欧洲0.25°×0.25°1950~202068.753.3
    CFSRNCEP美国0.5°×0.5°1979~202069.153.1
    MERRA2NASA美国0.5°×0.625°1980~202065.051.3
    JRA55JMA日本1.25°×1.25°1958~202064.751.1
    CRA40CMA中国0.5°×0.5°1979~202067.652.8
    下载: 导出CSV

    表  3  卫星遥感资料对高原低涡年鉴2005~2019年5~9月涡源的校正结果

    Table  3.   Modulation of TPV source by the satellite datasets in the warm season during 2005–2019

    个数比例
    没有有效的云迹风数据13125.7%
    年鉴的低涡在卫星观测未发现 8817.3%
    校正的低涡比年鉴的偏西26351.7%
    校正的低涡比年鉴的偏东 275.3%
    下载: 导出CSV

    表  4  2001~2019年暖季(5~9月)生成于高原西部的高原低涡(90ºE以西)相对比例

    Table  4.   Proportion of TPVs generated from the western TP in the warm season during 2001–2019, before and after the construction of the new meteorological sounding stations

    资料2001~2014年2015~2019年
    年鉴 2.5%17.5%
    ERA578.6%79.7%
    CFSR76.8%75.9%
    MERRA268.9%69.6%
    JRA5570.8%69.9%
    CRA4074.0%73.1%
    下载: 导出CSV
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  • 收稿日期:  2021-12-31
  • 录用日期:  2022-12-05
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