Predication of Typical Winter Circulation Systems Based on BCC_CSM1.1m Model
-
摘要: 基于国家气候中心气候系统模式1.1版本(BCC_CSM1.1m)的历史回报数据,利用时间相关系数和均方根误差等确定性技巧评分,对西伯利亚高压、阿留申低压、东亚冬季风3种东亚地区冬季典型环流系统的预报技巧进行检验评估,并通过时间序列分析和空间相关系数等方法,分析东亚地区冬季典型环流系统的可预报性来源。结果表明:由于模式对热带海洋和北太平洋海平面气压的预测偏差小、对欧亚大陆的预测偏差大,模式对阿留申低压、东亚冬季风的预测技巧高于西伯利亚高压。进一步分析表明:厄尔尼诺和南方涛动(ENSO)是阿留申低压和东亚冬季风的重要可预报性来源,而土壤温度是西伯利亚高压的重要可预报性来源,并受ENSO调制。此外,东亚冬季风的预报技巧也受到西伯利亚高压预报技巧的制约。
-
关键词:
- BCC_CSM1.1m;
- 冬季典型环流系统;
- 可预报性;
- ENSO
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.-
Key words:
- BCC_CSM1.1m;
- typical winter circulation systems;
- predictability;
- ENSO
-
图 2 BCC_CSM1.1m模式12月至9月(LM0~LM3)起报的冬季海平面气压的TCC技巧
(红色、绿色和蓝色方框分别为SHI, ALI, EAWMI定义区域,黑色打点区域表示相关系数达到0.05显著性水平)
(a)12月(LM0)起报,(b)11月(LM1)起报,(c)10月(LM2)起报,(d)9月(LM3)起报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)图 4 观测以及BCC_CSM1.1m模式12月至8月(LM0~LM4)起报的Niño3.4指数与海平面气压的相关系数
(红色、绿色和蓝色方框分别为SHI,ALI,EAWMI定义区域,黑色打点区域表示相关系数达到0.05显著性水平)
(a)观测, (b)12月(LM0)起报,(c)11月(LM1)起报,(d)10月(LM2)起报,(e)9月(LM3)起报, (f)8月(LM4)起报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)图 6 观测与BCC_CSM1.1m模式10—11月(LM2~LM1)起报的冬季SHI与观测和BCC_CSM1.1m模式10—11月起报的12月、1月0~10 cm土壤温度的相关系数
(红色方框为SHI定义区域,黑色打点表示相关系数达到0.05显著性水平)
(a)观测的冬季SHI与12月土壤温度,(b)观测的冬季SHI与1月土壤温度,(c)10月起报的冬季SHI与12月土壤温度,(d)10月起报的冬季SHI与1月土壤温度,(e)11月起报的冬季SHI与12月土壤温度,(f)11月起报的冬季SHI与1月土壤温度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图 7 BCC_CSM1.1m模式11月(LM1)(a)和12月(LM0)(b)起报的冬季SHI区域海平面气压PCC技巧与观测的12月土壤温度异常散点分布及其线性拟合线
(星型点代表超强厄尔尼诺年冬季结果)
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)
-
[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: 10.11898/1001-7313.20220510Li 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: 10.11898/1001-7313.20150404Dong 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.htmWang 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/20140102Liu 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.1001-7313.2013.05.003Wu 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: 10.11898/1001-7313.20160409Tang 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.htmWu 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/20140110Zhou 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: 10.11898/1001-7313.20210504Cheng 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.htmZhang 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.htmShi 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.htmShao 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.htmYang 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.htmShi 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.htmLiu 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: 10.11898/1001-7313.20160303Cheng 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: 10.11898/1001-7313.20220304Xie 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