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东北夏季降水预测技巧偏低的原因探讨

赵俊虎 熊开国 陈丽娟

赵俊虎, 熊开国, 陈丽娟. 2020. 东北夏季降水预测技巧偏低的原因探讨[J]. 大气科学, 44(5): 913−934 doi: 10.3878/j.issn.1006-9895.1911.19132
引用本文: 赵俊虎, 熊开国, 陈丽娟. 2020. 东北夏季降水预测技巧偏低的原因探讨[J]. 大气科学, 44(5): 913−934 doi: 10.3878/j.issn.1006-9895.1911.19132
ZHAO Junhu, XIONG Kaiguo, CHEN Lijuan. 2020. The Causes of Low Predictive Skills of Precipitation in Flood Season in Northeast China [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(5): 913−934 doi: 10.3878/j.issn.1006-9895.1911.19132
Citation: ZHAO Junhu, XIONG Kaiguo, CHEN Lijuan. 2020. The Causes of Low Predictive Skills of Precipitation in Flood Season in Northeast China [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(5): 913−934 doi: 10.3878/j.issn.1006-9895.1911.19132

东北夏季降水预测技巧偏低的原因探讨

doi: 10.3878/j.issn.1006-9895.1911.19132
基金项目: 国家重点研发计划“重大自然灾害监测预警与防范”重点专项2018YFC1506005,国家自然科学基金项目41875093、41705074、41275073,国家重点基础研究发展计划(973 计划)项目2015CB453203,湖北省气象局重点项目2016Z04
详细信息
    作者简介:

    赵俊虎,男,1985年出生,高级工程师,主要从事短期气候预测研究。E-mail: zhaojh@cma.gov.cn

    通讯作者:

    陈丽娟,主要从事短期气候预测研究。E-mail: chenlj@cma.gov.cn

  • 中图分类号: P461

The Causes of Low Predictive Skills of Precipitation in Flood Season in Northeast China

Funds: The National Key Research and Development Program on Monitoring, Early Warning and Prevention of Major Natural Disaster (Grant 2018YFC1506005), National Natural Science Foundation of China (NSFC) (Grants 41875093, 41705074, 41275073), National Basic Research Program of China (Grant 2015CB453203), Key Projects of Hubei Provincial Meteorological Bureau (Grant 2016Z04)
  • 摘要: 1978~2018年全国夏季降水实时业务预测技巧显示东北地区明显偏低,尤其是近几年在对全国夏季旱涝的总体分布预测效果明显提高的情况下,对东北地区的预测却与实况相反,因此有必要分析该区域预测技巧偏低的原因。利用站点资料、再分析格点数据、实时预测历史数据及统计诊断等方法,探讨了动力气候模式预测能力以及东北夏季降水预测的认识缺陷。通过系统地回顾东北夏季旱涝的气候特征、影响因子及预测方法等方面的研究进展,以及东北夏季降水实时预测检验,得出预测技巧偏低的可能原因:(1)东北初夏降水主要受东北冷涡活动的影响,盛夏主要受西太平洋副热带高压、东北南风和中高纬环流型的共同作用,而业务常用的国内外主要动力气候模式无法准确反映与东北初夏和盛夏降水相联系的关键环流系统;(2)东北夏季降水与全球海温的关系较弱且不稳定,尤其是与ENSO的关系较为复杂,年际关系随年代际变化而波动,即ENSO不是预测东北夏季降水的强信号;(3)东北夏季降水具有明显的季节内、年际和年代际等多时间尺度变率,夏季降水受到多种时间尺度信息的叠加和调控,不同尺度变率的贡献相当,且影响系统不同,导致预测难度较大。最后,进一步探讨了东北夏季降水预测存在的科学问题及可能的解决途径,以期为夏季业务预测提供参考。
  • 图  1  1978~2018年中国东部夏季降水预测(全国会商后的发布预报)效果检验:(a)时间相关系数(TCC),绿线表示达到90%的置信水平,黑线以东和以北表示东北(NEC)地区,黑色方框分别表示华北(NC)和长江中下游(MLRYR)地区;(b)距平符号预测正确年数百分率

    Figure  1.  The prediction test of summer precipitation in eastern China issued by the China Meteorological Administration from 1978 to 2018: (a) Temporal correlation coefficient (TCC), the green lines indicate significance at the 90% confidence level; the areas to the east and north of the black line represent the Northeast China (NEC), the black boxes indicate North China (NC) and the middle and lower reaches of the Yangtze River (MLRYR); (b) the percentage of anomaly sign consistency correctly predicted years

    图  2  1978~2018年3月起报的(a, d)东北、(b, e)华北和(c, f)长江中下游夏季降水(a,b,c)距平相关系数(ACC)和(d,e,f)距平符号一致率(ASCR)的年际变化。虚线为线性趋势

    Figure  2.  The inter-annual variability of (a, b, c) anomaly correlation coefficient (ACC) and (d, e, f) anomaly sign consistency rate (ASCR) skills for summer precipitation in (a, d) NC, (b, e) NEC, and (c, f) MLRYR based on observations and seasonal prediction issued in March from 1978 to 2018. Dotted lines represent the linear trends

    图  3  三个模式3月起报的中国东部夏季降水异常的TCC技巧:(a)CSM1.1模式,时间段为1991~2018年;(b)CFSv2模式,时间段为1982~2018年;(c)ECMWF4模式,时间段为1981~2018年。绿色线表示达到90%的置信水平

    Figure  3.  TCC skills for summer precipitation anomalies based on observations and seasonal prediction issued in March by (a) CSM1.1 model, from 1991 to 2018, (b) CFSv2 model, from 1982 to 2018, and (c) ECMWF4 model, from 1981 to 2018. The green lines indicate significance at the 90% confidence level

    图  4  CSM1.1、CFSv2和ECMWF4三个模式3月起报夏季降水ACC的年际变化(时间段同图3):(a)东北;(b)华北;(c)长江中下游

    Figure  4.  The inter-annual variability of ACC skills for summer precipitation in (a) NEC, (b) NC, and (c) MLRYR issued in March by CSM1.1, CFSv2, and ECMWF4 models. The periods of each model are the same as in Fig. 3

    图  5  1978~2018年东北(a)夏季、(b)初夏和(c)盛夏降水与同期500 hPa高度(等值线)和850 hPa水平风(箭头)的相关系数分布,(d)和(e)同图(a),但为华北和长江中下游。浅(深)色阴影表示达到95%(99%)的置信水平,仅绘出经向或纬向风速相关达到95%的置信水平的区域

    Figure  5.  Correlation coefficients between precipitation over NEC in (a) summer, (b) June, and (c) July–August and contemporaneous 500 hPa geopotential height (contour) and horizontal winds (vectors) at 850 hPa from 1978 to 2018. (d) and (e) are the same as (a), but for NC and MLRYR. The light (dark) shading areas indicate significance at the 95% (99%) confidence level. The vectors are of correlations significant at the 95% confidence level.

    图  6  (a,b,c)CSM1.1、(d,e,f)CFSv2和(g,h,i)ECMWF4三个模式3月起报的东北(a,d,g)夏季、(b,e,h)6月和(c,f,i)7~8月夏季降水和同期500 hPa位势高度相关系数。时间段同图3,浅(深)色阴影表示达到95%(99%)的置信水平

    Figure  6.  Correlation coefficients between (a, d, g) summer, (b, e, h) June, and (c, f, i) July–August precipitation in NEC and contemporaneous 500 hPa geopotential height issued in March by (a, b, c) CSM1.1, (d, e, f) CFSv2, and (g, h, i) ECMWF4 models. The periods of each model are the same as in Fig. 3. The light (dark) shading areas indicate significance at the 95% (99%) confidence level

    图  7  (a,d)CSM1.1、(b,e)CFSv2和(c,f)ECMWF4三个模式3月起报的(a,b,c)华北、(d,e,f)长江中下游夏季降水和同期500 hPa位势高度的相关系数。时间段同图3,浅(深)色阴影表示达到95%(99%)的置信水平

    Figure  7.  Correlation coefficients between summer precipitations in (a, b, c) NC, (d, e, f) MLRYR, and contemporaneous 500 hPa geopotential height issued in March by (a, d) CSM1.1, (b, e) CFSv2, and (c, f) ECMWF4. The periods of each model are the same as in Fig.3. The light (dark) shading areas and vectors drawn indicate significance at the 95% (99%) confidence level

    图  8  (a,b,c)CSM1.1、(d,e,f)CFSv2和(g,h,i)ECMWF4三个模式3月起报的东亚(a,d,g)夏季,(b,e,h)6月和(c,f,i)7~8月500 hPa位势高度异常预报技巧的TCC。时间段同图3,浅(深)色阴影表示达到95%(99%)的置信水平

    Figure  8.  TCC skills for 500 hPa geopotential height anomalies issued in March by (a, b, c) CSM1.1, (d, e, f) CFSv2 and (g, h, i) ECMWF4 models in (a, d, g) JJA (June–July–August), (b, e, h) June and (c, f, i) JA (July–August). The periods of each model are the same as in Fig.3, The light (dark) shading areas indicate significance at the 95% (99%) confidence level

    图  9  1951~2018年(a,b,c)东北、(d,e,f)华北和(g,h,i)长江中下游夏季降水与(a,d,g)前冬、(b,e,h)春季和(c,f,i)夏季SST的相关系数。黑色线表示达到95%的置信水平

    Figure  9.  Correlation coefficients between the summer precipitation in (a, b, c) NEC, (d, e, f) NC, (g, h, i) MLRYR, and sea surface temperature (SST) in (a, d, g) previous winter (DJF, December–February), (b, e, h) spring (MAM, March–May), (c, f, i) summer (JJA, June–August) from 1951 to 2018. Black lines indicate significant at the 95% confidence level

    图  10  1951~2018年东北夏季降水与ENSO关系的复杂性:(a)夏季降水量标准化值(纵坐标)与冬季Niño3.4指数(横坐标)的散点图,灰色的点为1951~1977年,红色的点为1978~2018年期间发布预报预测ACC大于0的年份,蓝色的点为1978~2018年期间发布预报预测ACC小于0的年份;(b)二者的11年滑动相关系数(绿色点线),红色虚线表示达到90%的置信水平,灰色柱状和橙色柱状分别为CMA发布预测和CSM1.1模式3月起报的东北ACC技巧

    Figure  10.  The complexity of the relationship between the summer precipitation in NEC and ENSO: (a) Scatter plots of the standardized summer precipitation (y-axis) and DJF Niño 3.4 index (x-axis); gray points are for 1951–1977, red points indicate the years when ACC is greater than 0 during the period of 1978–2018, and blue points indicate the years when ACC is less than 0 during the period of 1978–2018; (b) the 11-year-sliding correlation coefficients (green dotted line) between summer precipitation and DJF Niño 3.4 index. The red dotted line denotes significance at the 90% confidence level. The grey and orange columns indicate the ACC skills for precipitation over NEC issued in March by CMA and CSM1.1, respectively

    图  11  (a)CSM1.1、(b)CFSv2和(c)ECMWF4三个模式对东北夏季降水预测的历年ACC技巧与Niño3.4指数绝对值的散点图及其相关系数,时间段同图3,图中实心圆点代表Niño3.4指数大于0,空心圆圈代表Niño3.4指数小于0

    Figure  11.  Scatter plots of ACC skills of the JJA precipitation in NEC for (a) CSM1.1, (b) CFSv2, and (c) ECMWF4 against the absolute value of Niño3.4 index, and their correlation coefficients. The periods of each model are the same as in Fig. 3. The solid circles represent the Niño3.4 index above 0, while the hollow circles represent Niño3.4 index below 0

    图  12  1951~2018年东北夏季降水量标准化时间序列:(a)年际分量;(b)年代际分量

    Figure  12.  The standardized time series of the (a) inter-annual and (b) inter-decadal components of summer precipitation in Northeast China during 1951–2018

    图  13  1951~2018年东北夏季降水与500 hPa位势高度(等值线)和850 hPa水平风(箭头)的年际相关:(a)6月;(b)7~8月。其他同图5

    Figure  13.  Inter-annual correlation between summer precipitation in Northeast China and 500 hPa geopotential height (contour) and horizontal winds (vectors) at 850 hPa from 1951 to 2018: (a) June, (b) JA (July–August). Others are the same as in Fig. 5.

    图  14  图13,但为年代际尺度

    Figure  14.  Same as in Fig. 13, but for the inter-decadal time scale

    表  1  CSM1.1、CFSv2和ECMWF4三个模式3月起报夏季降水距平相关系数(ACC)技巧

    Table  1.   The anomaly correlation coefficient (ACC) skills for summer precipitation issued in March by CSM1.1, CFSv2, and ECMWF4 models

    ACC(东北)ACC(华北)ACC(长江中下游)
    最高最低平均最高最低平均最高最低平均
     CSM1.10.51−0.550.020.79−0.75−0.060.58−0.720.01
     CFSv20.44−0.74−0.060.87−0.590.040.66−0.700.09
     ECMWF40.54−0.69−0.080.77−0.630.040.57−0.670.05
    下载: 导出CSV
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    Zong Haifeng, Chen Lieting, Zhang Qingyun. 2010. The instability of the interannual relationship between ENSO and the summer rainfall in China [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 34(1): 184−192. doi: 10.3878/j.issn.1006-9895.2010.01.17
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出版历程
  • 收稿日期:  2019-04-06
  • 网络出版日期:  2020-03-24
  • 刊出日期:  2020-10-20

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