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青藏高原大气热源年际变率及其驱动因子

段安民 张萍

段安民, 张萍. 2022. 青藏高原大气热源年际变率及其驱动因子[J]. 大气科学, 46(2): 455−472 doi: 10.3878/j.issn.1006-9895.2201.21126
引用本文: 段安民, 张萍. 2022. 青藏高原大气热源年际变率及其驱动因子[J]. 大气科学, 46(2): 455−472 doi: 10.3878/j.issn.1006-9895.2201.21126
DUAN Anmin, ZHANG Ping. 2022. Interannual Variability of Atmospheric Heat Source over the Tibetan Plateau and Its Driving Factors [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(2): 455−472 doi: 10.3878/j.issn.1006-9895.2201.21126
Citation: DUAN Anmin, ZHANG Ping. 2022. Interannual Variability of Atmospheric Heat Source over the Tibetan Plateau and Its Driving Factors [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(2): 455−472 doi: 10.3878/j.issn.1006-9895.2201.21126

青藏高原大气热源年际变率及其驱动因子

doi: 10.3878/j.issn.1006-9895.2201.21126
基金项目: 国家自然科学基金杰出青年基金“海气自然变率影响青藏高原热源的过程和机理”41725018
详细信息
    作者简介:

    段安民,男,1973年出生,研究员,主要从事青藏高原气候动力学、海—陆—气相互作用以及气候变化的研究。E-mail: amduan@lasg.iap.ac.cn

  • 中图分类号: P461

Interannual Variability of Atmospheric Heat Source over the Tibetan Plateau and Its Driving Factors

Funds: Outstanding Youth Fund of the National Natural Science Foundation of China “Impact of the Air–Sea Natural Variability on the Tibetan Plateau Heat Source” (Grant 41725018)
  • 摘要: 青藏高原(以下简称高原)大气热源对亚洲夏季风爆发、演变、推进,乃至全球气候系统都有重要影响,因此近年来高原大气热源变异机理也日益受到关注。本文在回顾已有关于不同季节高原热源变异原因的研究基础上,利用1980~2018年日本气象厅再分析数据JRA55(Japanese 55-year Reanalysis),对逐月高原大气总热源的年际变率进行分类,并进一步探究了影响不同类别高原大气总热源的异常大尺度环流系统及海温驱动因子。除了传统上受关注的“冬季型”和“夏季型”以外,本文还提出了“早春型”和“过渡型”两种高原大气热源变率模态。总体而言,高原大气总热源年际变率以降水引起的凝结潜热异常为主,其中“冬季型”及“早春型”高原大气热源异常中心位于高原西部,主要受到中高纬遥相关波列的影响。此外,“冬季型”还受到厄尔尼诺—南方涛动(El Niño-Southern Oscillation, ENSO)及印度洋偶极子(Indian Ocean Dipole, IOD)的影响。“夏季型”高原大气热源呈东西偶极型反相变化,最大异常中心位于高原东南部,主要受北大西洋涛动(North Atlantic Oscillation, NAO)的影响;“过渡型”高原大气热源呈南北偶极型反相变化,受热带太平洋—印度洋海表温度异常的共同影响。因此,不同背景环流下高原热源年际变率的驱动因子存在明显差异。
  • 图  1  青藏高原80个气象站点分布。色标表示海拔高度(单位:m)。黑色曲线表示平均海拔在2000 m以上的青藏高原地形,下同

    Figure  1.  Spatial distribution of 80 meteorological stations on the Tibetan Plateau (TP). The altitude (units: m) is represented by the color bar. The black curve represents the TP domain with an altitude>2000 m, the same below

    图  2  不同资料高原大气热源及其分量的标准差(柱状,单位:W m–2)和气候平均值(实线,单位:W m–2):(a)站点和卫星资料;(b)JRA55资料;(c)MERRA-2资料;(d)ERA5资料;(e)NCEP2资料;(f)ERA-interim资料。红色:地表感热通量(SH);绿色:凝结潜热(LH);蓝色为大气净辐射(RC);黑色为大气总热源(汇)。图a资料的时间范围是1984~2015,图b–f资料的时间范围是1980~2018

    Figure  2.  Standard deviation (bars, units: W m–2) and climate mean (solid lines, units: W m–2) of each component of the TP heat source in different datasets: (a) Station and satellite data; (b) JRA55 (Japanese 55-year Reanalysis) data; (c) MERRA-2 (the second Modern-Era Retrospective analysis for Research and Applications) data; (d) ERA5 (Fifth major global reanalysis produced by European Centre for Medium-Range Weather Forecasts) data; (e) NCEP2 (National Centers for Environmental Prediction and the Department of Energy for reanalysis datasets) data; (f) ERA-interim (European Centre for Medium-Range Weather Forecasts interim reanalysis) data. Red: surface sensible heating (SH); green: latent heating (LH) of condensation; blue: net radiation of the air column (RC); black: their sum. In Fig. a, the time range of data is 1984–2015; in Figs. b–f, the time range of data is 1980–2018

    图  3  1984~2015年高原大气热源(汇)在观测资料与(a)JRA55资料、(b)MERRA-2资料、(c)ERA5资料、(d)ERA-interim资料、(e)NCEP2资料之间的相关系数。AHS表示大气总热源,SH表示地表感热,LH表示凝结潜热。RC表示大气净辐射通量。*、**、***分别代表相关系数通过90%、95%、99%置信水平的显著性检验

    Figure  3.  Correlation coefficients of the TP heat source (sink) between station dataset and (a) JRA55 data, (b) MERRA-2 data, (c) ERA5 data, (d) ERA-interim data, (e) NCEP2 data during 1984–2015. AHS represents the total atmospheric heat source, SH represents the surface sensible heating, LH represents latent heating of condensation, RC represents net radiation of the air column. *, **, and *** represent correlation coefficients exceeding the 90%, 95%, and 99% confidence level, respectively

    图  4  1980~2018年1~12月高原大气总热源(汇)第一模态(EOF1)的空间分布。右上角的数字表示其解释方差

    Figure  4.  Spatial distribution of the first EOF (empirical orthogonal function) mode (EOF1) of the TP heat source (sink) from January to December during 1980–2018. The number in the upper right corner of each subgraph represents its interpreted variance

    图  5  1980~2018年(a、e)“冬季型”(NDJ)、(b、f)“早春型”(FMA)、(c、g)“夏季型”(JJAS)、(d、h)“过渡型”(以5月代表)高原大气总热源第一模态(EOF1)的(a–d)空间分布及其(e–h)时间系数。右上角的数字表示EOF1的解释方差

    Figure  5.  (a–d) Spatial distribution and (e–h) time series (PC1) of the first EOF mode (EOF1) of (a, e) “winter type” (NDJ), (b, f) “early spring type” (FMA), (c, g) “summer type” (JJAS), (d, h) “transition type” (represented by May) of total atmospheric heat source over the TP during 1980–2018. The number in the upper right corner of each subgraph represents its interpreted variance

    图  6  1980~2018年“冬季型”青藏高原大气总热源第一模态时间系数(PC1)的回归场:(a)200 hPa位势高度(填色,单位:gpm)及水平风速(矢量,单位:m s–1);(b)700 hPa位势高度(填色,单位:gpm)及水平风速(矢量,单位:m s–1);(c)地表到100 hPa垂直积分的水汽通量(矢量,单位:kg m s−1)及水汽通量散度(填色,单位:10–5 kg m–2 s−1);(d)降水(填色,单位:mm d–1)。(e)1980~2018年 “冬季型”青藏高原大气热源PC1与全球海表温度异常(SSTA)的同期相关。紫色矢量及黑色打点区域表示通过90%置信水平的显著性t检验

    Figure  6.  Regression field of the first principal component (PC1) of the “winter type” total atmospheric heat source over the TP: (a) 200-hPa geopotential height (shadings, units: gpm) and horizontal wind (vectors; units: m s−1); (b) 700-hPa geopotential height (shadings, units: gpm) and horizontal wind (vectors; units: m s−1); (c) surface–100-hPa vertically integrated moisture transport anomalies (vectors; units: kg m s−1) and moisture divergence (shadings, units: 10−5 kg m−2 s−1); (d) precipitation (shadings, units: mm d–1) during 1980–2018. (e) Correlations between the PC1 of “winter type” total atmospheric heat source over the TP and the global sea surface temperature anomaly (SSTA) during 1980–2018. The purple vectors and black stippled regions indicate statistical significance above the 90% confidence level according to the Student’ s t test

    图  7  同图6,但为“早春型”的结果

    Figure  7.  As in Fig. 6, but for the results for “early spring type”

    图  8  1980~2018年“夏季型”青藏高原大气总热源PC1的回归场:(a)200 hPa位势高度(填色,单位:gpm)及水平风速(矢量,单位:m s−1);(b)500 hPa位势高度(填色,单位:gpm)及水平风速(矢量,单位:m s−1);(c)地表到100 hPa垂直积分的水汽通量(矢量,单位:kg m s−1)及水汽通量散度(填色,单位:10−5 kg m−2 s−1);(d)降水(填色,单位:mm d−1)。(e)1980~2018年“夏季型”青藏高原大气热源PC1与全球SSTA的同期相关。紫色矢量及黑色打点区域表示通过90%置信水平的显著性t检验

    Figure  8.  Regression field of the PC1 of the “summer type” total atmospheric heat source over TP: (a) 200-hPa geopotential height (shadings, units: gpm) and horizontal wind (vectors, units: m s−1); (b) 500-hPa geopotential height (shadings, units: gpm) and horizontal wind (vectors; units: m s−1); (c) surface–100-hPa vertically integrated moisture transport anomalies (vectors, units: kg m s−1) and moisture divergence (shadings, units: 10−5 kg m−2 s−1); (d) precipitation (shadings, units: mm d–1) during 1980–2018. (e) Correlations between the PC1 of the “summer type” total atmospheric heat source over the TP and the global SSTA during 1980–2018. The purple vectors and black stippled regions indicate statistical significance above the 90% confidence level according to the Student’ s t test

    图  9  1980~2018年5月青藏高原大气总热源PC1的回归场:(a)200 hPa位势高度(填色,单位:gpm)及水平风速(矢量,单位:m s−1);(b)500 hPa垂直速度(填色,单位:m s−1)及850 hPa水平风速(矢量,单位:m s−1);(c)地表到100 hPa垂直积分的水汽通量(矢量,单位:kg m s−1)及水汽通量散度(填色,单位:10−5 kg m−2 s−1);(d)降水(填色,单位:mm d−1)。(e)1980~2018年平均的5月青藏高原大气热源PC1与全球SSTA的同期相关。紫色矢量及黑色打点区域表示通过90%置信水平的显著性t检验

    Figure  9.  Regression field of the PC1 of the total atmospheric heat source over TP in May: (a) 200-hPa geopotential height (shadings, units: gpm) and horizontal wind (vectors, units: m s−1); (b) 500-hPa vertical velocity (shadings, units: m s−1) and 850-hPa horizontal wind (vectors, units: m s−1); (c) surface–100-hPa vertically integrated moisture transport anomalies (vectors, units: kg m s−1) and moisture divergence (shadings, units: 10−5 kg m−2 s−1); (d) precipitation (shadings, units: mm d–1) during 1980–2018. (e) Correlations between the PC1 of the total atmospheric heat source over the TP and the global SSTA in May averaged in the period 1980–2018. The purple vectors and black stippled regions indicate statistical significance above the 90% confidence level according to the Student’ s t-test

    图  10  影响不同类型青藏高原大气总热源的物理过程示意图:(a)“冬季型”;(b)“早春型”;(c)“夏季型”;(d)“过渡型”(以5月为代表)。“C”和“AC”分别代表气旋和反气旋异常,深蓝色箭头虚线表示Rossby波列传播路径,蓝色环状虚线代表异常经圈环流,高原上空彩色阴影代表降水异常,蓝色(红色)竖直虚线代表异常环流的正压结构,图a、d中红(蓝)色阴影表示正(负)SSTA异常。+IOD:印度洋偶极子正位相;+NAO:北大西洋涛动正位相;+IOBM:印度洋海盆一致模正位相

    Figure  10.  Schematic diagram of physical processes affecting different types of total atmospheric heat source over TP: (a) “Winter type”; (b) “early spring type”; (c) “summer type”; (d) “transition type” (represented by May). “C” and “AC” represent cyclonic and anticyclonic anomalies, respectively; the dark blue dotted arrow line represents the propagation path of Rossby wave train; the blue dotted ring represents the anomalous meridional circulation; the color shadings over the plateau represent the precipitation anomalies; the blue (red) dotted vertical line represents the barotropic structure of anomalous circulation; in Figs. a and d, the red (blue) shadings represent positive (negative) SSTA. +IOD: positive phase of the Indian Ocean Dipole; +NAO: positive phase of the North Atlantic Oscillation; +IOBM: positive phase of the Indian Ocean Basin Mode

    表  1  1980~2018年青藏高原总热源EOF1的空间分布(Mode1)以及时间序列(PC1)在“冬季型”、“早春型”、“夏季型”与其相应的每个月之间的相关系数

    Table  1.   Correlation coefficients of the spatial distribution (Mode1) and time series (PC1) of the EOF1 of the total atmospheric heat source over the TP between “winter type”, “early spring type”, “summer type” and their corresponding months, respectively, during 1980–2018

    相关系数
    冬季型11月12月1月
    PC10.63***0.45***0.45***
    EOF10.89 0.92 0.79
    早春型2月3月4月
    PC10.80***0.56***0.28*
    EOF10.940.95 0.71
    夏季型6月7月8月9月
    PC10.66***0.67***0.40***0.55***
    EOF10.93 0.73 0.91 0.88
    注:******分别代表通过90%、95%、99%置信水平的显著性检验。
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  • 收稿日期:  2021-07-15
  • 录用日期:  2022-01-21
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