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中国西北5月和9月地表气温的年际变率机理及其预测

姚梦莹 朱志伟 卢睿 姚俊强

姚梦莹, 朱志伟, 卢睿, 等. 2023. 中国西北5月和9月地表气温的年际变率机理及其预测[J]. 大气科学, 46(X): 1−16 doi: 10.3878/j.issn.1006-9895.2111.21124
引用本文: 姚梦莹, 朱志伟, 卢睿, 等. 2023. 中国西北5月和9月地表气温的年际变率机理及其预测[J]. 大气科学, 46(X): 1−16 doi: 10.3878/j.issn.1006-9895.2111.21124
YAO Mengying, ZHU Zhiwei, LU Rui, et al. 2023. Mechanism and Seasonal Prediction of Interannual Variations of the Surface Air Temperature in May and September over Northwest China [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(X): 1−16 doi: 10.3878/j.issn.1006-9895.2111.21124
Citation: YAO Mengying, ZHU Zhiwei, LU Rui, et al. 2023. Mechanism and Seasonal Prediction of Interannual Variations of the Surface Air Temperature in May and September over Northwest China [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(X): 1−16 doi: 10.3878/j.issn.1006-9895.2111.21124

中国西北5月和9月地表气温的年际变率机理及其预测

doi: 10.3878/j.issn.1006-9895.2111.21124
基金项目: 国家自然科学基金项目42088101、42175033,中国沙漠气象科学研究基金项目Sqj2022003
详细信息
    作者简介:

    姚梦莹,女,1997年出生,硕士,主要从事西北气候变率和预测方面的研究。E-mail: yaomy@nuist.edu.cn

    通讯作者:

    朱志伟,E-mail: zwz@nuist.edu.cn

  • 中图分类号: P461

Mechanism and Seasonal Prediction of Interannual Variations of the Surface Air Temperature in May and September over Northwest China

Funds: National Natural Science Foundation of China (Grants 42088101, 42175033), China Desert Meteorological Science Research Foundation (Grant Sqj2022003)
  • 摘要: 本文基于1961~2016年中国西北地区逐日地表气温观测资料以及全球大气再分析资料,通过统计诊断和数值模拟的方法,揭示了西北地区5月和9月地表气温年际变率规律及其机理,并在此基础上分别构建了季节预测模型。结果表明:(1)西北5月和9月地表气温年际变率经验正交函数分解第一模态均为全区一致型空间分布,但具有不同的变率特征;(2)西北5月地表气温正异常与拉尼娜衰减型海表温度异常所对应的热带纬向三极型对流(降水)异常强迫有关,对流异常激发的热带外遥相关波列导致西北地区上空受反气旋(高压)异常控制,造成局地向下太阳短波辐射增多,从而使得西北地表气温增加;而西北9月地表气温正异常与拉尼娜发展型海表温度异常所对应的热带纬向偶极型对流(降水)异常强迫有关,偶极型对流强迫能够在西北地区东西两侧激发反气旋(高压)异常,导致西北地表气温正异常;(3)基于物理机制,分别利用拉尼娜衰减和发展型的相关海表温度异常预测因子,建立针对西北地区5月和9月地表气温年际变率的季节预测模型,独立预报期间(2007~2016年)预测技巧相关系数分别可达0.74和0.62,可为西北地表气温短期气候预测提供参考。
  • 图  1  西北地区(a)区域平均的地表气温气候态逐月演变(单位:°C)以及(b)5月和(c)9月平均地表气温气候态空间分布(单位:°C)

    Figure  1.  (a) Monthly evolution of the climatological surface air temperature (units: °C) averaged over Northwest China, and the spatial pattern of the surface air temperature over Northwest China in (b) May and (c) September (units: °C)

    图  2  西北地区(a)5月和(b)9月地表气温年际分量的第一模态空间分布及其(c)各自主成分时间序列

    Figure  2.  First mode of the interannual surface air temperature over Northwest China in (a) May and (b) September and (c) their principal components

    图  3  5月(a)850 hPa高度场(等值线;单位:gpm)、风场(矢量;单位:m s−1)和海表/地表气温(填色;单位:°C),以及(b)200 hPa高度场(等值线;单位:gpm)、风场(矢量;单位:m s−1)和降水场(填色;单位:mm d−1)回归至5月西北地表气温主成分(PC)。(c)、(d)同(a)、(b),但为9月。打点为海表温度以及降水场回归系数通过90%显著性检验的区域,紫色虚线框为热带降水强迫关键区,黑色实线内为西北地区

    Figure  3.  Regressed (a) 850 hPa geopotential height field (contour; units: gpm), wind field (vector; units: m s−1), and sea surface/surface air temperature (shading; units: °C), (b) 200 hPa geopotential height field (contour; units: gpm), wind field (vector; units: m s−1), and precipitation (shading; units: mm d−1) onto the principal component (PC) of the surface air temperature of Northwest China in May. (c), (d) same as (a), (b), but for September. The dotted areas represent regression coefficients of the sea surface temperature (SST) and precipitation passing the 90% confidence level. The purple boxes represent the key regions of tropical diabatic forcing, and the solid black line outlines Northwest China

    图  4  (a)5月T1、T2、T3区域和(b)9月D1、D2区域上空与西北地区地表气温年际变率相关的大气非绝热加热垂直廓线(彩色实线;单位:1 K d−1),彩色虚线为数值模式中对应区域上空给定的大气非绝热加热垂直廓线(单位:10 K d−1

    Figure  4.  Observed vertical profile of diabatic heating related to the interannual variability of the surface air temperature in Northwest China of (a) T1, T2, and T3 regions in May and (b) D1 and D2 regions in September (colored solid line; units: 1 K d−1). The color-dotted lines represent the prescribed vertical profile of diabatic heating in the model of the key region of precipitation (units: 10 K d−1)

    图  5  模式中5月200 hPa位势高度(等值线;单位:gpm)和风场(矢量;单位:m s−1)对(a)T1、T2、T3区域上空大气加热或冷却共同作用的响应,以及分别对(b)T1上空冷却、(c)T2上空加热和(d)T3上空冷却作用的响应。红色(蓝色)阴影分别为模式中理想化大气加热(冷却)率的水平分布,中心加热强度为1 K d−1,黑色实线内为西北地区

    Figure  5.  200 hPa geopotential height (contours; units: gpm) and wind (vectors; units: m s−1) response to (a) the combined effect of atmospheric heating and cooling over T1, T2, and T3, (b) cooling over T1, (c) heating over T2, and (d) cooling over T3 in May. The red (blue) shading is the horizontal pattern of the idealized heating (cooling) with their maximum amplitude of 1 K d−1, and the solid black line outlines Northwest China

    图  6  模式中9月200 hPa位势高度(等值线;单位:gpm)和风场(矢量;单位:m s−1)对(a)D1和D2区域上空大气加热和冷却共同作用的响应,以及分别对(b)D1上空加热、(c)D2上空冷却作用的响应

    Figure  6.  200 hPa geopotential height (contours; units: gpm) and wind (vectors; units: m s−1) response to the combined action of atmospheric heating or cooling over (a) D1 and D2 and the responses to (b) heating over D1 and (c) cooling over D2 in September, respectively.

    图  7  10°S~10°N平均的(a)海表温度(单位:°C)和(b)降水(单位:mm d−1)对5月西北地表气温主成分(PC)的超前滞后回归。打点区域为海表温度和降水回归系数通过90%的显著性检验。(c)、(d)同(a)、(b),但为9月。 红色和蓝色虚线分别代表5月和9月

    Figure  7.  10°S–10°N averaged lead-lag regression of (a) the sea surface temperature (units: °C) and (b) precipitation (units: mm d−1) onto the principal component of the surface air temperature over Northwest China in May. The dotted areas represent the regression coefficients of the sea surface temperature and precipitation passing the 90% confidence level. (c), (d) same as (a), (b), but for September. The red and blue dashed lines represent May and September, respectively

    图  8  5月和9月西北地表气温主成分(PC)与前期表温度相关系数空间分布。(a)3~4月平均、(b)4月减3月以及(c)3~4月平均减12~1月平均的海温场与5月PC的相关分布;(d)7~8月平均、(e)8月减7月以及(f)7~8月平均减4~5月平均的海温场与9月PC的相关分布。打点区域表示通过了95%的置信水平,方框中为潜在预报因子区域

    Figure  8.  Spatial distribution of the correlation coefficient between the principal component of surface air temperature in May and September in Northwest China and the previous sea surface temperature. (a), (b), and (c) represent the correlation distributions between the sea surface temperature field of March and April average, April minus March, March and April average minus December and January average, and PC in May. (d), (e), and (f) are the correlation distributions between the sea surface temperature field of July and August average, August minus July, and July and August average minus April and May average, and PC in September. The dotted area indicates the passing of the statistical significance at a 95% confidence level, and the boxes are the key area of predictors

    图  9  10°S~10°N平均的(b)海表温度(单位:°C)对5月预测因子(a)IOBM和(b)IOWT的超前滞后回归,打点区域为海表温度回归系数通过90%的显著性检验,(c)、(d)同(a)、(b)但为对9月预测因子NAW和PDT。 红色和蓝色虚线分别代表5月和9月

    Figure  9.  10ºS–10ºN averaged lead–lag regression of sea surface temperature (units: °C) onto the predictors (a) IOBM and (b) IOWT in May. Dotted areas are regression coefficients of the SST passing the 90% confidence level. (c), (d) Same as (a), (b), but onto the predictors NAW and PDT in September. The red and blue dashed lines represent May and September, respectively

    图  10  (a)5月和(b)9月西北地表气温主成分(PC)的逐年变化。黑线为观测,蓝线为1961~2006年回报结果,红线为2007~2016年独立预报结果

    Figure  10.  Principal component of the surface air temperature in Northwest China in (a) May and (b) September. The black line corresponds to the observation, the blue line represents the hindcast from 1961 to 2006, and the red line indicates the independent forecast from 2007 to 2016

    图  11  1961~2016年间(a)5月和(b)9月西北地表气温主成分与各自潜在预测因子的11年滑动相关。虚线为95%的显著性检验的相关系数阈值

    Figure  11.  Eleven-year sliding correlation coefficient between principal components of the surface air temperature in Northwest China in (a) May and (b) September and their potential predictors. The dotted line is the threshold of the correlation coefficient at the 95% significance level

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出版历程
  • 收稿日期:  2021-07-14
  • 录用日期:  2021-12-09
  • 网络出版日期:  2021-12-13

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