Impact of ENSO on Tropical Cyclone Activities in Northwest Pacific Simulated by the NUIST Earth System Model
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摘要: 地球系统模式已经逐步成为研究热带气旋(TC)活动气候变化的重要工具之一,之前的研究发现南京信息工程大学地球系统模式(NESM)高分辨率版本可以较好地模拟全球海温分布及TC活动的气候特征。本研究进一步分析了NESM地球系统模式模拟西北太平洋TC活动的年际变化,并与1967~2016年观测的TC活动进行对比。NESM模式高分辨率版本能够较好地模拟西北太平洋平均海温及与ENSO事件联系的海温异常变化特点,对El Niño事件发生时西北太平洋TC的生成频数和路径分布的模拟较好,也能模拟El Niño年TC生成位置比La Niña年偏东的特征,但是未能模拟出TC平均生命周期和Niño3.4地区海温的相关性。并且模式模拟的La Niña年TC的生成位置偏东,主要原因是模拟La Niña年季风槽平均位置偏东。研究结果有助于进一步改进NESM模式和利用NESM模式研究TC活动。Abstract: An Earth system model is an important tool for studying the TC (tropical cyclone) activities affected by climate change. Previous studies have shown that the high-resolution version of the NUIST Earth system model (NESM) can simulate the global SST distribution and climate characteristics of the TC activity. Compared to the TC activity observed from 1967 to 2016, this study analyzed the interannual variability of the TC activity in the Northwest Pacific Ocean simulated by the NESM model. The results show that the high-resolution version of the NESM model can simulate the mean SST in the Northwest Pacific and the SST anomalies associated with ENSO events. This model could simulate the generation frequency and the path distribution of TCs in the Northwest Pacific when El Niño events occur. The simulation showed that the position of TCs in El Niño years was more easterly than in the La Niña years. However, the correlation between the mean life of TC and Niño3.4 SST could not be simulated. Moreover, the generation position of TCs in La Niña years simulated by the model is easterly than observation, mainly because the average position of the monsoon trough in the simulated La Niña years is eastward. These results can help improve the NESM model studying TC activities.
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图 1 1967~2016年夏季和秋季(a)观测、(b)模拟的Niño3.4指数时间序列分布。红色实线和蓝色虚线分别为Niño3.4指数1倍和−1倍标准差数值(研究年份分类标准阈值)
Figure 1. Time series distribution of the Niño3.4 index (a) observed, (b) simulated in summer and autumn during 1967–2016. The solid red line and blue dashed line are the value of 1 and −1 standard deviation (threshold value of the classification standard for the study year) of the Niño3.4 index
图 2 1967~2016年El Niño(La Niña)事件发生时西北太平洋夏季平均海温异常(阴影,单位:°C)与TC的生成位置(黑点)分布:(a)观测的El Niño;(b)模拟的El Niño;(c)观测的La Niña;(d)模拟的La Niña。黑色虚线为不同区域的分界线,点状阴影区域为通过5%显著性水平的区域
Figure 2. Average sea surface temperature anomalies (shadings, units: °C) in summer in the Northwest Pacific and the distribution of the TC generation locations (black dots) during the El Niño (La Niña) event during 1967–2016: (a) Observed El Niño, (b) simulated El Niño, (c) observed La Niña, (d) simulated La Niña. The black dashed lines denote the dividing lines of different areas; the dotted shadings represent the area passed the 5% significance level
图 4 1967~2016年夏季(a)观测、(b)模拟的TC年平均生成位置。红色正方形表示El Niño年TC的平均生成位置,蓝色六边形表示La Niña年TC的平均生成位置,黑点表示其他年份TC的平均生成位置
Figure 4. Annual average generation location of TCs (a) observed, (b) simulated in summer during 1967–2016. The red squares represent the average generation positions of TCs in El Niño years, the blue hexagons represent the average generation positions of TCs in La Niña years, and the black dots represent the average generation positions of TCs in the other years
图 6 1967~2016年TC平均生命周期和Niño3.4地区海表面温度异常的相关性:(a)观测;(b)模拟。黑点表示不同年份的结果,虚线为一元线性回归拟合线,其中观测相关系数通过5%的显著性水平
Figure 6. Correlation between the TC average lifespan and sea surface temperature anomalies in Niño3.4 area during 1967–2016: (a) Observation; (b) simulation. The black dots represent results of different years; the dashed line is the one-variable linear regression line; the correlation coefficient of the observation passed the 5% significance level
图 7 1967~2016年El Niño(La Niña)事件发生时西北太平洋夏季TC路径频数分布:(a)观测的El Niño;(b)模拟的El Niño;(c)观测的La Niña;(d)模拟的La Niña
Figure 7. Frequency distribution of TC paths in summer in Northwest Pacific during the El Niño (La Niña) event during 1967–2016: (a) Observed El Niño; (b) simulated El Niño; (c) observed La Niña; (d) simulated La Niña
图 9 1967~2016年(a、c)观测的、(b、d)模拟的La Niña事件发生时西北太平洋海表温度异常(阴影、等值线,单位:°C)、850 hPa平均风场(箭头,单位:m s−1):(a、b)夏季;(c、d)秋季。黑色实线为季风槽槽线
Figure 9. Sea surface temperature anomalies (shadings and contours, units: °C), 850-hPa average wind (arrows, units: m s−1) in the Northwest Pacific during the La Niña event (a, c) observed, (b, d) simulated in summer during 1967–2016: (a, b) Summer; (c, d) autumn. The solid black lines represent the monsoon trough lines
表 1 1967~2016年夏季和秋季观测和模拟的El Niño(La Niña)典型年的分类结果
Table 1. Classification results of El Niño (La Niña) typical years observed and simulated in summer and autumn during 1967–2016
观测 模拟 强暖年 弱暖年 正常年 弱冷年 强冷年 标准差 强暖年 弱暖年 正常年 弱冷年 强冷年 标准差 夏季 1972、1982、1987、1997、2002、2015 1977、1991、1993、1994、2004、2009、2012 1967、1968、1969、1976、1979、1980、1981、1983、1986、1990、1992、1995、1996、2001、2003、2005、2006、2008、2013、2014、2016 1974、1978、1984、1985、1989、
1998、2000、2007、20111970、1971、1974、1978、1983、1984、1985、1995、2000、2011、2016 0.66 2、8、21、22、27、33、34、48 9、19、29、31、32、38、39、41 1、6、7、10、12、13、14、15、18、
26、28、30、36、37、40、42、443、5、16、20、43、45、47、49 4、11、17、23、24、25、35、46、50 0.77 秋季 1972、1982、1987、1997、2002、2009、2015 1969、1976、1977、1979、1986、
1991、1994、2004、2006、20141967、1968、1980、1981、1989、
1990、1992、1993、1996、2001、
2003、2005、2008、2012、20131970、1971、1973、1975、1988、1999、2010 1973、1975、1988、1998、1999、2007、2010 0.99 8、21、27、30、33、34、39、48 2、14、18、22、28、38、41、44 3、5、6、7、9、12、13、15、19、
20、26、29、31、32、36、37、421、10、11、23、40、43、47 4、16、17、24、25、35、45、46、49、50 0.79 注:标准差指的是不同年份Niño3.4指数的标准差。 表 2 1967~2016年夏季和秋季观测和模拟的El Niño年和La Niña年西北太平洋不同子区域TC的生成频数
Table 2. Frequency of TC generation in different subregions of Northwest Pacific in El Niño and La Niña years observed and simulated in summer and autumn during 1967–2016
西北太平洋子区域 TC的生成频数 夏季观测 夏季模拟 El Niño年 La Niña年 总数 El Niño年 La Niña年 总数 西北象限(120°~140°E,20°N以北) 6 11 17 19 17 36 东北象限(140°E~180°,20°N以北) 4 10 14 11 10 21 西南象限(120°~140°E,20°N以南) 19 11 30 11 9 20 东南象限(140°E~180°,20°N以南) 30 1 31 23 14 37 总数 59 33 92 64 50 114 秋季观测 秋季模拟 El Niño年 La Niña年 总数 El Niño年 La Niña年 总数 西部区域(120°~140°E) 12 33 45 9 36 45 东部区域(140°E~180°) 28 9 37 15 27 42 总数 40 42 82 24 63 87 表 3 1967~2016年夏季、秋季的观测、模拟的El Niño年和La Niña年TC平均生成位置的平均偏差
Table 3. The mean deviations of the average generation positions of TCs in El Niño and La Niña years observed and simulated in summer and autumn during 1967–2016
El Niño年(观测) La Niña年(观测) El Niño年(模拟) La Niña年(模拟) 纬度偏差 经度偏差 纬度偏差 经度偏差 纬度偏差 经度偏差 纬度偏差 经度偏差 夏季 −2.6° 6.7° 3.4° −3.8° −0.3° 4.8° −0.8° −2.2° 秋季 −0.4° 8.8° 1.3° −8.8° −0.3° 5.3° 0.0° −6.4° 注:加粗的数字表示通过5%显著性水平的t检验。 -
[1] Camargo S J, Sobel A H. 2005. Western North Pacific tropical cyclone intensity and ENSO [J]. J. Climate, 18(15): 2996−3006. doi: 10.1175/JCLI3457.1 [2] Camargo S J, Emanuel K A, Sobel A H. 2007. Use of a genesis potential index to diagnose ENSO effects on tropical cyclone genesis [J]. J. Climate, 20(19): 4819−4834. doi: 10.1175/JCLI4282.1 [3] Cao J, Wang B, Xiang B Q, et al. 2015. Major modes of short-term climate variability in the newly developed NUIST Earth System Model (NESM) [J]. Adv. Atmos. Sci., 32(5): 585−600. doi: 10.1007/s00376-014-4200-6 [4] Chan J C L. 1985. Tropical cyclone activity in the Northwest Pacific in relation to the El Niño/Southern Oscillation phenomenon [J]. Mon. Wea. Rev., 113(4): 599−606. doi:10.1175/1520-0493(1985)113<0599:TCAITN>2.0.CO;2 [5] Chan J C L. 2000. Tropical cyclone activity over the western North Pacific associated with El Niño and La Niña events [J]. J. Climate, 13(16): 2960−2972. doi:10.1175/1520-0442(2000)013<2960:TCAOTW>2.0.CO;2 [6] Chan J C L. Shi J E, Lam C M 1998. Seasonal forecasting of tropical cyclone activity over the western North Pacific and the South China Sea [J]. Wea. Forecasting, 13(4): 997−1004. doi:10.1175/1520-0434(1998)013<0997:SFOTCA>2.0.CO;2 [7] Chen T C, Wang S Y, Yen M C, et al. 2004. Role of the monsoon gyre in the interannual variation of tropical cyclone formation over the western North Pacific [J]. Wea. Forecasting, 19(4): 776−785. doi:10.1175/1520-0434(2004)019<0776:ROTMGI>2.0.CO;2 [8] Chia H H, Ropelewski C F. 2002. The interannual variability in the genesis location of tropical cyclones in the Northwest Pacific [J]. J. Climate, 15(20): 2934−2944. doi:10.1175/1520-0442(2002)015<2934:TIVITG>2.0.CO;2 [9] Graham N E, Barnett T P. 1987. Sea surface temperature, surface wind divergence, and convection over tropical oceans [J]. Science, 238(4827): 657−659. doi: 10.1126/science.238.4827.657 [10] Kim H S, Vecchi G A, Knutson T R, et al. 2014. Tropical cyclone simulation and response to CO2 doubling in the GFDL CM2.5 high-resolution coupled climate model [J]. J. Climate, 27(21): 8034−8054. doi: 10.1175/JCLI-D-13-00475.1 [11] Krishnamurthy L, Vecchi G A, Msadek R, et al. 2016. Impact of strong ENSO on regional tropical cyclone activity in a high-resolution climate model in the North Pacific and North Atlantic Oceans [J]. J. Climate, 29(7): 2375−2394. doi: 10.1175/JCLI-D-15-0468.1 [12] Lander M A. 1993. Comments on “A GCM simulation of the relationship between tropical storm formation and ENSO” [J]. Mon. Wea. Rev., 121(7): 2137−2143. doi:10.1175/1520-0493(1993)121<2137:COGSOT>2.0.CO;2 [13] Lander M A. 1994a. An exploratory analysis of the relationship between tropical storm formation in the western North Pacific and ENSO [J]. Mon. Wea. Rev., 122(4): 636−651. doi:10.1175/1520-0493(1994)122<0636:AEAOTR>2.0.CO;2 [14] Lander M A. 1994b. Description of a monsoon gyre and its effects on the tropical cyclones in the western North Pacific during August 1991 [J]. Wea. Forecasting, 9(4): 640−654. doi:10.1175/1520-0434(1994)009<0640:DOAMGA>2.0.CO;2 [15] Landsea C W. 2000. El Niño–Southern Oscillation and the seasonal predictability of tropical cyclones [M]//Diaz H F, Markgraf V. El Niño: Impacts of Multiscale Variability on Natural Ecosystems and Society. Cambridge: Cambridge University Press, 149–181. [16] Manganello J V, Hodges K I, Dirmeyer B, et al. 2014. Future changes in the western North Pacific tropical cyclone activity projected by a multidecadal simulation with a 16-km global atmospheric GCM [J]. J. Climate, 27(20): 7622−7646. doi: 10.1175/JCLI-D-13-00678.1 [17] Murakami H, Sugi M, Kitoh A. 2013. Future changes in tropical cyclone activity in the North Indian Ocean projected by high-resolution MRI–AGCMs [J]. Climate Dyn., 40(7-8): 1949−1968. doi: 10.1007/s00382-012-1407-z [18] Murakami H, Vecchi G A, Underwood S, et al. 2015. Simulation and prediction of category 4 and 5 hurricanes in the high-resolution GFDL HiFLOR coupled climate model [J]. J. Climate, 28(23): 9058−9079. doi: 10.1175/JCLI-D-15-0216.1 [19] Murakami H, Vecchi G A, Delworth T L, et al. 2017. Dominant role of subtropical Pacific warming in extreme eastern Pacific hurricane seasons: 2015 and the future [J]. J. Climate, 30(1): 243−264. doi: 10.1175/JCLI-D-16-0424.1 [20] Oouchi K, Satoh M, Yamada Y, et al. 2010. Change of tropical cyclone and seasonal climate state in a global warming experiment with a global cloud-system-resolving model [M]//Elsner J B, Hodges R E, Malmstadt J C, et al. Hurricanes and Climate Change. Dordrecht: Springer, 25–37. doi: 10.1007/978-90-481-9510-7_2 [21] Ritchie E A, Holland G J. 1999. Large-scale patterns associated with tropical cyclogenesis in the western Pacific [J]. Mon. Wea. Rev., 127(9): 2027−2043. doi:10.1175/1520-0493(1999)127<2027:LSPAWT>2.0.CO;2 [22] Tao L, Wu L G, Wang Y Q, et al. 2012. Influence of tropical Indian ocean warming and ENSO on tropical cyclone activity over the western North Pacific [J]. J. Meteor. Soc. Japan, 90(1): 127−144. doi: 10.2151/jmsj.2012-107 [23] Wang B, Li T M. 1993. A simple tropical atmosphere model of relevance to short-term climate variations [J]. J. Atmos. Sci., 50(2): 260−284. doi:10.1175/1520-0469(1993)050<0260:ASTAMO>2.0.CO;2 [24] Wang B, Chan J C L. 2002. How strong ENSO events affect tropical storm activity over the western North Pacific [J]. J. Climate, 15(13): 1643−1658. doi:10.1175/1520-0442(2002)015<1643:HSEEAT>2.0.CO;2 [25] Wang C Z, Li C X, Mu M, et al. 2013. Seasonal modulations of different impacts of two types of ENSO events on tropical cyclone activity in the western North Pacific [J]. Climate Dyn., 40(11-12): 2887−2902. doi: 10.1007/s00382-012-1434-9 [26] Wu G X, Lau N C. 1992. A GCM simulation of the relationship between tropical storm formation and ENSO [J]. Mon. Wea. Rev., 120(6): 958−977. doi:10.1175/1520-0493(1992)120<0958:AGSOTR>2.0.CO;2 [27] Wu L, Wen Z P, Huang R H, et al. 2012 Possible linkage between the monsoon trough variability and the tropical cyclone activity over the western North Pacific [J]. Mon. Wea. Rev., 140(1): 140–150. doi: 10.1175/MWR-D-11-00078.1 [28] Wu L G, Zong H J, Liang J. 2013. Observational analysis of tropical cyclone formation associated with monsoon gyres [J]. J. Atmos. Sci., 70(4): 1023−1034. doi: 10.1175/JAS-D-12-0117.1 [29] 吴启蒙, 吴立广, 曹剑. 2019. NUIST地球系统模式模拟热带气旋活动的气候特征分析 [J]. 气候变化研究进展, 15(2): 107−118. doi: 10.12006/j.issn.1673-1719.2018.116Wu Q M, Wu L G, Cao J. 2019. Analysis of climate characteristics of tropical cyclone activities simulated by the NUIST Earth system model [J]. Climate Change Research, 15(2): 107−118. doi: 10.12006/j.issn.1673-1719.2018.116 [30] Yamada Y, Oouchi K, Satoh M, et al. 2010. Projection of changes in tropical cyclone activity and cloud height due to greenhouse warming: Global cloud-system-resolving approach [J]. Geophys. Res. Lett., 37(7): L07709. doi: 10.1029/2010GL042518 [31] Yamada Y, Satoh M, Sugi M, et al. 2017. Response of tropical cyclone activity and structure to global warming in a high-resolution global nonhydrostatic model [J]. J. Climate, 30(23): 9703−9724. doi: 10.1175/JCLI-D-17-0068.1 [32] Zhao H K, Wu L G, Zhou W C. 2010. Assessing the influence of the ENSO on tropical cyclone prevailing tracks in the western North Pacific [J]. Adv. Atmos. Sci., 27(6): 1361−1371. doi: 10.1007/s00376-010-9161-9 [33] Zhao H K, Wu L G, Zhou W C. 2011. Interannual changes of tropical cyclone intensity in the western North Pacific [J]. J. Meteor. Soc. Japan, 89(3): 243−253. doi: 10.2151/jmsj.2011-305 -