Vol.34,  No.1, 
December  2022
Turn off MathJax
Article Contents
Abstract
Figures and Tables
References
Related Articles
Zhang Zhichao, Zhou Fang, Zhang Haoxin, et al. Predication of typical winter circulation systems based on BCC_CSM1.1m model. J Appl Meteor Sci, 2023, 34(1): 27-38. DOI: 10.11898/1001-7313.20230103.
Citation: Zhang Zhichao, Zhou Fang, Zhang Haoxin, et al. Predication of typical winter circulation systems based on BCC_CSM1.1m model. J Appl Meteor Sci, 2023, 34(1): 27-38. DOI: 10.11898/1001-7313.20230103.
shu

Predication of Typical Winter Circulation Systems Based on BCC_CSM1.1m Model

  • 1.

    Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, NUIST, Nanjing 210044

  • 2.

    Xia County Meteorological Bureau of Shanxi Province, Yuncheng 044400

  • 3.

    Chinese Academy of Meteorological Sciences, Beijing 100081

More Information
    Abstract
  • Accurate prediction of East Asian winter climate has become an important topic in climate research. Coupled ocean-atmosphere dynamical model prediction systems have made great progress. It can offer overall outstanding performance, and become the major tool of dynamical climate prediction. The seasonal prediction performance of BCC_CSM1.1m model has been systematically evaluated. It's found that although the model can predict temperature, precipitation, snow cover, and Asian monsoon to some extent, there are still great challenges in the prediction of East Asian winter climate. It is important to analyze the possible causes of model biases and reveal the source of its predictability. Based on the hindcasts of BCC_CSM1.1m, time correlation coefficient and root mean square error are analyzed to evaluate the prediction skills of 3 typical East Asian winter circulation systems, including Siberian high (SH), Aleutian low (AL) and East Asian winter monsoon (EAWM). Then the predictability sources are also examined through time series analysis and pattern correlation coefficient. The results show that the prediction of sea level pressure in tropical region is better than that in the middle and high latitude region. Due to the influence of El Niño and Southern Oscillation (ENSO) and its remote teleconnection, the sea level pressure prediction over the ocean is better than that over the continent, which results in better prediction skills of AL and EAWM compared to SH. Further analysis shows that the elimination of super El Niño years leads to lower prediction skills of AL and EAWM. The correlation between sea level pressure in Eurasia and ENSO is less than that in tropical and north Pacific regions, indicating that ENSO is an important source of predictability of AL and EAWM. It is also found that soil temperature at 0-10 cm in Siberia is an important factor affecting the simultaneous and later SH, which suggests that the predictability of the SH may come from the shallow soil temperature. After removing super El Niño years, the prediction skill of SH is altered greatly, which reflects the modulation of ENSO on SH prediction. The model can overestimate the linear relationship between SH and ENSO, and lead to a poor SH prediction skill. Moreover, the prediction of EAWM depends on the accurate prediction of SH and AL, and its prediction skill is restricted by the poor SH prediction skills to some extent.
    • FullText(HTML)
    • References (34)

  • Fig  1.   Prediction skills of SHI, ALI and EAWMI initiated from Dec to Aug(LM0-LM4)

    (the dashed line and dotted line denote the levels of 0.05 and 0.01, respectively)

    DownLoad: Full-Size Img PowerPoint

    Fig  2.   TCC skills in winter sea level pressure initiated from Dec to Sep(LM0-LM3) in BCC_CSM1.1m

    (red, green, and blue boxes denote regions of SHI, ALI and EAWMI, dotted area denotes TCC passing the test of 0.05 level)
    (a)Dec(LM0), (b)Nov(LM1), (c)Oct(LM2), (d)Sep(LM3)

    DownLoad: Full-Size Img PowerPoint

    Fig  3.   Observational and predicted SHI, ALI and EAWMI initiated from Dec to Aug(LM0-LM4)

    DownLoad: Full-Size Img PowerPoint

    Fig  4.   TCC between Niño3.4 index and sea level pressure in observation and model prediction initiated from Dec to Aug(LM0-LM4)

    (red, green, and blue boxes denote the regions of SHI, ALI and EAWMI, dotted area denotes TCC passing the test of 0.05 level)
    (a)observation, (b)initiated in Dec(LM0), (c)initiated in Nov(LM1), (d)initiated in Oct(LM2), (e)initiated in Sep(LM3), (f)initiated in Aug(LM4)

    DownLoad: Full-Size Img PowerPoint

    Fig  5.   Scatter plots of PCC skill against absolute Niño3.4 index and its linear fitting line for SHI(a), ALI(b) and EAWMI(c) region initiated in Nov

    DownLoad: Full-Size Img PowerPoint

    Fig  6.   TCC between observed and BCC_CSM1.1m predicted winter SHI from Oct to Nov(LM2-LM1) and 0-10 cm soil temperature in Dec and Jan

    (red box denotes region of SHI, dotted area denotes TCC passing the test of 0.05 level)
    (a)observed winter SHI and soil temperature in Dec, (b)observed winter SHI and soil temperature in Jan, (c)winter SHI initiated in Oct and soil temperature in Dec, (d)winter SHI initiated in Oct and soil temperature in Jan, (e)winter SHI initiated in Nov and soil temperature in Dec, (f)winter SHI initited in Nov and soil temperature in Jan

    DownLoad: Full-Size Img PowerPoint

    Fig  7.   Scatter plots of PCC skill against soil temperature anomaly and its linear fitting line for SHI region initiated in Nov(LM1)(a) and Dec(LM0)(b)

    (hollow stars denote the strong El Niño year)

    DownLoad: Full-Size Img PowerPoint
  • [1]
    李莹, 王国复.气象灾害风险管理系统设计与应用.应用气象学报, 2022, 33(5):628-640. DOI: 10.11898/1001-7313.20220510

    Li Y, Wang G F. Design and implementation of meteorological disaster risk management system. J Appl Meteor Sci, 2022, 33(5): 628-640. DOI: 10.11898/1001-7313.20220510
    [2]
    董仕, 肖子牛. 冬季北极涛动对东亚表面温度的持续异常影响. 应用气象学报, 2015, 26(4): 422-431. DOI: 10.11898/1001-7313.20150404

    Dong S, Xiao Z N. The persistent impact of winter Arctic Oscillation on the East Asian surface air temperature. J Appl Meteor Sci, 2015, 26(4): 422-431. DOI: 10.11898/1001-7313.20150404
    [3]
    王政琪, 徐影, 周波涛. CMIP5模式对东亚冬季风指数变化及其与冬季大气环流和气温关系的模拟评估. 地球物理学报, 2017, 60(9): 3315-3324. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWX201709004.htm

    Wang Z Q, Xu Y, Zhou B T. Evaluation of the CMIP5 models in simulating the change of the East Asian winter monsoon indices and their relationship with the wintertime atmospheric circulation and temperature. Chinese J Geophys, 2017, 60(9): 3315-3324. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWX201709004.htm
    [4]
    刘实, 隋波, 涂钢, 等. 我国东北地区冬季气温变化的东亚冬季风背景. 应用气象学报, 2014, 25(1): 11-21. http://qikan.camscma.cn/article/id/20140102

    Liu S, Sui B, Tu G, et al. The East Asian winter monsoon background on the variation of winter air temperature in Northeast China. J Appl Meteor Sci, 2014, 25(1): 11-21. http://qikan.camscma.cn/article/id/20140102
    [5]
    Chen W, Yang S, Huang R H. Relationship between stationary planetary wave activity and the East Asian winter monsoon. J Geophys Res Atmos, 2005, 110: D14110.
    [6]
    Yan H, Yang H, Yuan Y, et al. Relationship between East Asian winter monsoon and summer monsoon. Adv Atmos Sci, 2011, 28(6): 1345-1356. DOI: 10.1007/s00376-011-0014-y
    [7]
    Fan G, Lv F, Zhang J, et al. A possible way to extract a stationary relationship between ENSO and the East Asian winter monsoon. Atmos Ocean Sci Lett, 2020, 13(4): 294-300. DOI: 10.1080/16742834.2020.1733918
    [8]
    Ding Y H. Build-up, air mass transformation and propagation of Siberian high and its relation to cold surge in East Asia. Meteor Atmos Phys, 1990, 44(1): 281-292.
    [9]
    Cohen J, Saito K, Entekhabi D. The role of the Siberian high in Northern Hemisphere climate variability. Geophys Res Lett, 2001, 28(2): 299-302. DOI: 10.1029/2000GL011927
    [10]
    Guirguis K, Gershunov A, Schwartz R, et al. Recent warm and cold daily winter temperature extremes in the Northern Hemisphere. Geophys Res Lett, 2011, 38: L17701.
    [11]
    Pickart R S, Macdonald A M, Moore G W K, et al. Seasonal evolution of Aleutian low pressure systems: Implications for the North Pacific subpolar circulation. J Phys Oceanogr, 2009, 39(6): 1317-1339. DOI: 10.1175/2008JPO3891.1
    [12]
    Rodionov S N, Overland J E, Bond N A. The Aleutian low and winter climatic conditions in the Bering Sea. Part I: Classification. J Climate, 2005, 18(1): 160-177. DOI: 10.1175/JCLI3253.1
    [13]
    Qian W H, Zhang H N, Zhu Y F, et al. Interannual and interdecadal variability of East Asian areas and their impact on temperature of China in winter season for the last century. Adv Atmos Sci, 2001, 18(4): 511-523. DOI: 10.1007/s00376-001-0041-1
    [14]
    吴统文, 宋连春, 刘向文, 等. 国家气候中心短期气候预测模式系统业务化进展. 应用气象学报, 2013, 24(5): 533-543. DOI: 10.3969/j.issn.1001-7313.2013.05.003

    Wu T W, Song L C, Liu X W, et al. Progress in developing the short-range operational climate prediction system of China National Climate Center. J Appl Meteor Sci, 2013, 24(5): 533-543. DOI: 10.3969/j.issn.1001-7313.2013.05.003
    [15]
    唐慧琴, 曾刚, 黄悦. BCC_CSM1.1(m)模式对热带太平洋潜热通量的评估. 应用气象学报, 2016, 27(4): 463-472. DOI: 10.11898/1001-7313.20160409

    Tang H Q, Zeng G, Huang Y. An assessment of the tropical Pacific latent heat flux simulated by BCC_CSM1.1(m). J Appl Meteor Sci, 2016, 27(4): 463-472. DOI: 10.11898/1001-7313.20160409
    [16]
    吴捷, 任宏利, 张帅, 等. BCC二代气候系统模式的季节预测评估和可预报性分析. 大气科学, 2017, 41(6): 1300-1315. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXK201706013.htm

    Wu J, Ren H L, Zhang S, et al. Evaluation and predictability analysis of seasonal prediction by BCC second-generation climate system model. Chinese J Atmos Sci, 2017, 41(6): 1300-1315. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXK201706013.htm
    [17]
    周鑫, 李清泉, 孙秀博, 等. BCC_CSM1.1模式对我国气温的模拟和预估. 应用气象学报, 2014, 25(1): 95-106. http://qikan.camscma.cn/article/id/20140110

    Zhou X, Li Q Q, Sun X B, et al. Simulation and projection of temperature in China with BCC_CSM1.1 model. J Appl Meteor Sci, 2014, 25(1): 95-106. http://qikan.camscma.cn/article/id/20140110
    [18]
    成菲, 李巧萍, 沈新勇, 等. BCC_CSM1.1m对欧亚积雪覆盖的预测评估. 应用气象学报, 2021, 32(5): 553-566. DOI: 10.11898/1001-7313.20210504

    Cheng F, Li Q P, Shen X Y, et al. Evaluation of Eurasian snow cover fraction prediction based on BCC_CSM1.1m. J Appl Meteor Sci, 2021, 32(5): 553-566. DOI: 10.11898/1001-7313.20210504
    [19]
    张丹琦, 孙凤华, 张耀存. 基于BCC第二代短期气候预测模式系统的中国夏季降水季节预测评估. 高原气象, 2019, 38(6): 1229-1240. https://www.cnki.com.cn/Article/CJFDTOTAL-GYQX201906010.htm

    Zhang D Q, Sun F H, Zhang Y C. Evaluation of seasonal prediction for summer rainfall in China based on BCC second-generation short-range climate forecast system. Plateau Meteor, 2019, 38(6): 1229-1240. https://www.cnki.com.cn/Article/CJFDTOTAL-GYQX201906010.htm
    [20]
    Zhou F, Ren H L, Hu Z Z, et al. Seasonal predictability of primary East Asian summer circulation patterns by three operational climate prediction models. Quart J Roy Meteor Soc, 2020, 146(727): 629-646.
    [21]
    Tian B, Ren H L. Diagnosing SST error growth during ENSO developing phase in the BCC_CSM1.1(m) prediction System. Adv Atmos Sci, 2022, 39(3): 427-442.
    [22]
    Hasanean H M, Almazroui M, Jones P D, et al. Siberian high variability and its teleconnections with tropical circulations and surface air temperature over Saudi Arabia. Climate Dyn, 2013, 41(7): 2003-2018.
    [23]
    Chen Y, Zhai P. Interannual to decadal variability of the winter Aleutian Low intensity during 1900-2004. Acta Meteor Sinica, 2011, 25(6): 710-724.
    [24]
    施能, 鲁建军, 朱乾根. 东亚冬, 夏季风百年强度指数及其气候变化. 南京气象学院学报, 1996, 19(2): 168-177. https://www.cnki.com.cn/Article/CJFDTOTAL-NJQX199602002.htm

    Shi N, Lu J J, Zhu Q G. East Asian winter/summer monsoon intensity indices with their climatic change in 1873-1989. Journal of Nanjing Institute of Meteorology, 1996, 19(2): 168-177. https://www.cnki.com.cn/Article/CJFDTOTAL-NJQX199602002.htm
    [25]
    邵鹏程, 李栋梁. 东亚冬季风指数的分类和比较. 气象科学, 2012, 32(2): 226-235. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKX201202016.htm

    Shao P C, Li D L. Classification and comparison of East Asian winter monsoon indices. J Meteor Sci, 2012, 32(2): 226-235. https://www.cnki.com.cn/Article/CJFDTOTAL-QXKX201202016.htm
    [26]
    杨洪卿, 范可, 田宝强, 等. 为什么NCEP-CFSv2模式对11月西伯利亚高压强度的预测性能较好. 大气科学, 2021, 45(4): 697-712. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXK202104001.htm

    Yang H Q, Fan K, Tian B Q, et al. Why is the November Siberian high intensity more predictable by NCEP-CFSv2 model. Chinese J Atmos Sci, 2021, 45(4): 697-712. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXK202104001.htm
    [27]
    Wang B, Lee J Y, Kang I S, et al. Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction(1980-2004). Climate Dyn, 2009, 33(1): 93-117.
    [28]
    石世玮, 智海, 林鹏飞, 等. 热带太平洋盐度年际变化对海表温度异常作用比较: 1997/1998、2014/2015和2015/2016年El Niño事件. 大气科学, 2020, 44(5): 1057-1075. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWX201701003.htm

    Shi S W, Zhi H, Lin P F, et al. Contrasting salinity interannual variations in the tropical Pacific and their effects on recent El Niño events: 1997/1998, 2014/2015, and 2015/2016. Chinese J Atmos Sci, 2020, 44(5): 1057-1075. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWX201701003.htm
    [29]
    刘明竑, 任宏利, 张文君, 等. 超强厄尔尼诺事件对中国东部春夏季极端降水频率的影响. 气象学报, 2018, 76(4): 539-553. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXB201804004.htm

    Liu M H, Ren H L, Zhang W J, et al. Influence of super El Niño events on the frequency of spring and summer extreme precipitation over eastern China. Acta Meteor Sinica, 2018, 76(4): 539-553. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXB201804004.htm
    [30]
    Ren H L, Jin F F, Song L C, et al. Prediction of primary climate variability modes at the Beijing Climate Center. J Meteor Res, 2017, 31(1): 204-223.
    [31]
    Ding Y, Krishnamurti T N. Heat budget of the Siberian high and the winter monsoon. Mon Wea Rev, 1987, 115(10): 2428-2449.
    [32]
    National Research Council. Assessment of Intraseasonal to Interannual Climate Prediction and Predictability. National Academies Press, 2010: 192.
    [33]
    程娅蓓, 任宏利, 谭桂荣. 东亚夏季风模式跨季预测的EOF-相似误差订正. 应用气象学报, 2016, 27(3): 285-292. DOI: 10.11898/1001-7313.20160303

    Cheng Y B, Ren H L, Tan G R. Empirical orthogonal function-analogue correction of extra-seasonal dynamical prediction of East-Asian summer monsoon. J Appl Meteor Sci, 2016, 27(3): 285-292. DOI: 10.11898/1001-7313.20160303
    [34]
    谢舜, 孙效功, 张苏平, 等. 基于SVD与机器学习的华南降水预报订正方法. 应用气象学报, 2022, 33(3): 293-304. DOI: 10.11898/1001-7313.20220304

    Xie S, Sun X G, Zhang S P, et al. Precipitation forecast correction in South China based on SVD and machine learning. J Appl Meteor Sci, 2022, 33(3): 293-304. DOI: 10.11898/1001-7313.20220304
    • Related Articles

  • Related Articles

    [1]Zhao Qiang, Yan Huasheng, Cheng Lu. Characteristics of Shaanxi Summer Precipitation Anomalies in ENSO Developing and Decaying Stages[J]. Journal of Applied Meteorological Science, 2013, 24(4): 495-503.
    [2]Zhang Renhe, Yin Yonghong, Li Qingquan, Liu Yimin, Niu Tao. Utilizing ARGO Data to Improve the Prediction of ENSO and Short-term Climate Prediction of Summer Rainfall in China[J]. Journal of Applied Meteorological Science, 2006, 17(5): 538-547.
    [3]Cheng Yanjie, Bian Lingen, Lu Longhua. ANTARCTIC SEA-ICE OSCILLATION AND ITS RELATIONSHIP WITH ENSO[J]. Journal of Applied Meteorological Science, 2002, 13(6): 711-717.
    [4]Wu Aiming, Ni Yunqi. STUDIES OF ENSO-RELATED CLIMATE PREDICTION WITH A HYBRID OCEAN-ATMOSPHERE COUPLED MODEL[J]. Journal of Applied Meteorological Science, 2001, 12(2): 129-139.
    [5]Wu Aiming, Ni Yunqi. ENSO SIMULATED BY A HYBRID COUPLED OCEAN-ATMOSPHERE MODEL AND ITS MECHANISMS[J]. Journal of Applied Meteorological Science, 2000, 11(4): 419-429.
    [6]Xie Ming′en, Zhang Wancheng. RELATIONSHIP BETWEEN ENSO EVENTS AND WINTER TEMPERATURE ANOMALY IN YUNNAN[J]. Journal of Applied Meteorological Science, 2000, 11(1): 115-122.
    [7]Chen Qianjin, Zhao Zhenguo, Wang Lihua. STUDY ON THE FEATURES OF FLOOD/DROUGHT AND ACTIVITIES OF TYPHOONS OVER EAST CHINA SEA AND THEIR LINKAGE TO ENSO IN WARM/COOL SUMMERS[J]. Journal of Applied Meteorological Science, 2000, 11(1): 88-94.
    [8]Ni Yunqi, Shen Xinyong, Yang Xiuqun. A Review of ENSO Dynamics and Its Numerical Simulation[J]. Journal of Applied Meteorological Science, 1998, 9(2): 239-245.
    [9]Guo Yanjun, Zhai Panmao, Ni Yunqi. A New Index for ENSO Monitoring[J]. Journal of Applied Meteorological Science, 1998, 9(2): 169-177.
    [10]Qian Weihong, . Composite Analyses of Monthly Sea Surface Temperature Anomalies Associated with the ENSO Cycle[J]. Journal of Applied Meteorological Science, 1996, 7(2): 145-152.

  • Cited by

    Periodical cited type(3)

    1. 邵祺多，涂钢，布和朝鲁，刘实. 基于海-冰-气系统的东亚冬季风统计预测. 应用气象学报. 2024(02): 168-181 . 本站查看
    2. 王淼淼，丁明虎，吕俊梅，陈军明. 近40年中国冬季寒潮的气候特征及大气环流异常. 应用气象学报. 2024(03): 298-310 . 本站查看
    3. 朱雨晴，薛晓萍. 基于不同驱动因子的番茄生长模型比较. 应用气象学报. 2024(06): 747-758 . 本站查看

    Other cited types(0)

Catalog

    Figures(7)

    Get Citation
    PDF
    XML
    Article views: 1286 PDF downloads: 74 Cited by: 3
    • Received : 2022-08-05
    • Accepted : 2022-10-13
    • Published : 2023-01-30
    Journal Online
    Contact

    © 2020 Journal of Applied Meteorological Science   京ICP备15006967号-1

    Supported by Beijing Renhe Information Technology Co. Ltd

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return