Article(id=1246840123606851776, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1246840121887187126, articleNumber=null, orderNo=null, doi=10.3969/j.issn.0253-4193.2019.09.014, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1536681600000, receivedDateStr=2018-09-12, revisedDate=1544457600000, revisedDateStr=2018-12-11, acceptedDate=null, acceptedDateStr=null, onlineDate=1775199450636, onlineDateStr=2026-04-03, pubDate=1569340800000, pubDateStr=2019-09-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1775199450636, onlineIssueDateStr=2026-04-03, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1775199450636, creator=13701087609, updateTime=1775199450636, updator=13701087609, issue=Issue{id=1246840121887187126, tenantId=1146029695717560320, journalId=1149651085930835976, year='2019', volume='41', issue='9', pageStart='1', pageEnd='190', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1775199450227, creator=13701087609, updateTime=1775200621889, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1246845036290265802, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1246840121887187126, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1246845036290265803, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1246840121887187126, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=145, endPage=155, ext={EN=ArticleExt(id=1246840124013699273, articleId=1246840123606851776, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=Study and application of the refined tsunami real time warning system including tsunamigenic wave and current, columnId=1243954929497387113, journalTitle=Haiyang Xuebao, columnName=Marine Technology, runingTitle=null, highlight=null, articleAbstract=

Based on the Okada model, nonlinear shallow water equation, and nested grid with high resolution, a real-time tsunami warning system of transoceanic-offshore-local is built for Wenzhou and Taizhou’s coastal region of Zhejiang Province. The grid resolution of the refined layer is 900 m. The tsunami warning system includes parallel numerical calculation module, visualization module based on Python 2D library (matplotlib), and product integration module which integrates all numerical graphical products on a web page by Python. Once an earthquake occurs, the system could complete the numerical calculation, visualization processing and graphic product integration within 10 minutes. Firstly, the system has been validated by the 2011 Japan tsunami with the magnitude of M w 9.0. Then, the extreme potential tsunami from Nankai Trough and Okinawa Trough is simulated by the system in terms of tsunami amplitude and currents. The results show that the tsunami warning system can improve the efficiency and accuracy of tsunami early warning in the coastal region, and provide a scientific basis for tsunami early warning, disaster reduction and decision supporting.

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基于Okada模型和非线性浅水波模型,结合高精度多层嵌套网格针对我国浙江沿海的温州和台州地区建立了越洋–近海–局部的精细化地震海啸波流实时预警系统,近岸的分辨率为900 m。该预警系统包括了并行化的数值计算模块,基于Python 2D绘图库的计算结果可视化处理模块,以及通过Python语言将所有经过数值计算的图形与动画产品集成在一个网页上的产品集成模块。一旦地震发生,该系统可根据地震的震源参数信息在10 min内完成数值计算、可视化处理,以及产品集成。选取2011年日本东北9.0级地震海啸结合实测数值对该系统进行模拟验证,进一步应用该系统模拟计算了日本南海海槽和琉球海沟潜在极端海啸的影响规律。结果表明,该预警系统可有效地提高地震海啸实时预警的时效性和准确度,为海啸的预警、减灾,以及辅助决策提供科学依据。

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任智源(1986—),男,陕西省西安市人,博士,主要从事水动力学的研究。E-mail:zhyren@foxmail.com

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任智源(1986—),男,陕西省西安市人,博士,主要从事水动力学的研究。E-mail:zhyren@foxmail.com

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任智源(1986—),男,陕西省西安市人,博士,主要从事水动力学的研究。E-mail:zhyren@foxmail.com

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journalId=1149651085930835976, articleId=1246840123606851776, language=EN, label=Fig. 15, caption=Time series of surface elevation and speed at Dachen and Kanmen, figureFileSmall=SesYYAk3GQowkwTgq23zZg==, figureFileBig=xhANVRUhD6S40LySDvTNIw==, tableContent=null), ArticleFig(id=1254506262469734709, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246840123606851776, language=CN, label=图15, caption=大陈与坎门的波面、流速时间序列, figureFileSmall=SesYYAk3GQowkwTgq23zZg==, figureFileBig=xhANVRUhD6S40LySDvTNIw==, tableContent=null), ArticleFig(id=1254506262675255607, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246840123606851776, language=EN, label=Table 1, caption=

Risk level of tsunami hazard

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等级 最大波幅/m 最大流速/m·s–1
Ⅳ(蓝色) H≤0.3 V≤0.5
Ⅲ(黄色) 0.3<H≤1.0 0.5<V≤1.0
Ⅱ(橙色) 1.0<H≤3.0 1.0<V≤3.0
Ⅰ(红色) H≥3.0 V≥3.0
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海啸灾害风险等级

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等级 最大波幅/m 最大流速/m·s–1
Ⅳ(蓝色) H≤0.3 V≤0.5
Ⅲ(黄色) 0.3<H≤1.0 0.5<V≤1.0
Ⅱ(橙色) 1.0<H≤3.0 1.0<V≤3.0
Ⅰ(红色) H≥3.0 V≥3.0
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Grid resolution

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第一层/ 分辨率/(′) 第二层/ 分辨率/(′) 第三层/ 分辨率/(′) 网格数 计算时间/s
网格1 2 1 0.25 138万 4 378
网格2 4 2 0.5 34万 581
网格3 4 2 1 30万 490
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计算网格配置

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第一层/ 分辨率/(′) 第二层/ 分辨率/(′) 第三层/ 分辨率/(′) 网格数 计算时间/s
网格1 2 1 0.25 138万 4 378
网格2 4 2 0.5 34万 581
网格3 4 2 1 30万 490
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精细化地震海啸波流实时预警系统研究与应用
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任智源 1, 2 , 侯京明 1, 2 , 王培涛 1, 2 , 李涛 1 , 原野 1, 2 , 赵联大 1, 2
海洋学报 | 海洋技术 2019,41(9): 145-155
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海洋学报 | 海洋技术 2019, 41(9): 145-155
精细化地震海啸波流实时预警系统研究与应用
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任智源1, 2, 侯京明1, 2, 王培涛1, 2, 李涛1, 原野1, 2, 赵联大1, 2
作者信息
  • 1 国家海洋环境预报中心,北京 100081
  • 2 自然资源部海啸预警中心,北京 100081
  • 任智源(1986—),男,陕西省西安市人,博士,主要从事水动力学的研究。E-mail:zhyren@foxmail.com

Study and application of the refined tsunami real time warning system including tsunamigenic wave and current
Zhiyuan Ren1, 2, Jingming Hou1, 2, Peitao Wang1, 2, Tao Li1, Ye Yuan1, 2, Lianda Zhao1, 2
Affiliations
  • 1 National Marine Environmental Forecast Center, Beijing 100081, China
  • 2 National Tsunami Warning Center, Ministry of Natural Resources, Beijing 100081, China
出版时间: 2019-09-25 doi: 10.3969/j.issn.0253-4193.2019.09.014
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基于Okada模型和非线性浅水波模型,结合高精度多层嵌套网格针对我国浙江沿海的温州和台州地区建立了越洋–近海–局部的精细化地震海啸波流实时预警系统,近岸的分辨率为900 m。该预警系统包括了并行化的数值计算模块,基于Python 2D绘图库的计算结果可视化处理模块,以及通过Python语言将所有经过数值计算的图形与动画产品集成在一个网页上的产品集成模块。一旦地震发生,该系统可根据地震的震源参数信息在10 min内完成数值计算、可视化处理,以及产品集成。选取2011年日本东北9.0级地震海啸结合实测数值对该系统进行模拟验证,进一步应用该系统模拟计算了日本南海海槽和琉球海沟潜在极端海啸的影响规律。结果表明,该预警系统可有效地提高地震海啸实时预警的时效性和准确度,为海啸的预警、减灾,以及辅助决策提供科学依据。

地震海啸  /  预警系统  /  精细化预报  /  数值模拟

Based on the Okada model, nonlinear shallow water equation, and nested grid with high resolution, a real-time tsunami warning system of transoceanic-offshore-local is built for Wenzhou and Taizhou’s coastal region of Zhejiang Province. The grid resolution of the refined layer is 900 m. The tsunami warning system includes parallel numerical calculation module, visualization module based on Python 2D library (matplotlib), and product integration module which integrates all numerical graphical products on a web page by Python. Once an earthquake occurs, the system could complete the numerical calculation, visualization processing and graphic product integration within 10 minutes. Firstly, the system has been validated by the 2011 Japan tsunami with the magnitude of M w 9.0. Then, the extreme potential tsunami from Nankai Trough and Okinawa Trough is simulated by the system in terms of tsunami amplitude and currents. The results show that the tsunami warning system can improve the efficiency and accuracy of tsunami early warning in the coastal region, and provide a scientific basis for tsunami early warning, disaster reduction and decision supporting.

earthquake tsunami  /  tsunami warning system  /  refined forecast  /  numerical simulation
任智源, 侯京明, 王培涛, 李涛, 原野, 赵联大. 精细化地震海啸波流实时预警系统研究与应用. 海洋学报, 2019 , 41 (9) : 145 -155 . DOI: 10.3969/j.issn.0253-4193.2019.09.014
Zhiyuan Ren, Jingming Hou, Peitao Wang, Tao Li, Ye Yuan, Lianda Zhao. Study and application of the refined tsunami real time warning system including tsunamigenic wave and current[J]. Haiyang Xuebao, 2019 , 41 (9) : 145 -155 . DOI: 10.3969/j.issn.0253-4193.2019.09.014
近十几年来,以2004年印度洋海啸和2011年日本地震海啸为代表的特大地震海啸事件对沿海地区造成了极大的人员伤亡、财产损失和环境破坏。2004年12月26日,印度尼西亚的苏门答腊附近发生了9.1级地震海啸袭击了印度、印度尼西亚、马尔代夫、孟加拉国、泰国、斯里兰卡等多个国家,共造成了超过20万人的死亡[1-2]。2011年3月11日,日本东北部海域发生了M w=9.0级特大地震,地震引发的海啸共造成近3万人死亡或失踪。根据灾后的实地调查,海啸的最大爬高达到了40 m[3]。此次海啸对我国的沿海也造成了一定影响,浙江沿海的最大波幅达到50 cm[4-5]。我国位于太平洋板块与亚欧板块相互作用的地震活跃地带,环太平洋产生的越洋海啸,以及琉球海沟、马尼拉海沟可以发生的区域海啸,均对我国造成潜在的威胁[6-8]。因此,针对重点区域建立准确和快速的地震海啸实时预警系统显得非常迫切和必要。
全球的海啸监测预警系统是在2004年印度洋海啸之后得到高度重视并快速发展的。它是基于地震监测信息、海啸的实测波面数据以及数值模拟技术进行海啸预警。我国的海啸预警是从2006年开始逐步发展,目前建立了基于SeisComP3软件的全球地震监测系统、60个海啸浮标与800余个潮位站组成的水位实测系统,以及基于高性能计算机的数值模拟系统[6],可以开展海啸对我国整体性影响的预警工作。但目前,针对重点区域的精细化海啸预警研究在国内还属于空白。
地震海啸主要是由于海底地震引起海底地形的大变形进而引起水面的扰动并在海水表面快速传播,属于浅水长波。因此,在海啸预警[9-10]、数值模拟[11-12],以及灾害评估[13-14]中,海啸的波高及其演化过程受到了重点关注。但是,Fritz等[15]基于视频数据与雷达技术发现在2011年日本海啸过程中产生的流场的最大流速达到11 m/s。Lynett等[16]通过数值模拟证实由于受到非线性和湍流效应的影响,由海啸诱发的近岸流场表现出更显著的时间与空间分布的不均一性,同时给出了海啸诱发流场的风险评估等级标准。尽管采用的非线性浅水方程和Boussinesq模型均未考虑湍流模型,但与实测数据的比较表明它们也可以计算得到较为准确的近岸垂向平均流场。基于数值模拟与实测数据,Arcos和LeVeque[17]利用非线性浅水波模型计算了2011年日本海啸传播至夏威夷附近的流场规律。王培涛等[18]进一步基于数值计算得到的流场信息分析了其相应的平面二维的涡度特征(流场的旋度)。Ren等[19]在对南海潜在极端海啸的模拟中发现海啸诱发的流场是伴随海啸波的传播过程,而最大流速主要集中在近岸区域,对港口、码头均有可能产生灾害。因此,在海啸预警中提供海啸波和流场等关键信息,有助于全面了解海啸灾害和防灾减灾。
目前,海洋动力灾害的精细化预报的研究与应用主要是针对风暴潮和台风浪,而地震海啸的精细化预警尚没有涉及。王培涛等[20]采用基于非线性浅水波方程和非结构网格的数值模型(ADCIRC)在台湾海峡和福建沿海区域建立了台风风暴潮数值预报模型。刘秋兴等[21]将该模型扩展到覆盖中国沿海地区,利用128核的超级计算机可在28 min内完成数值计算。罗锋等[22]和刘秋兴等[23]分别在江苏沿海和浙江温州沿海开展了精细化预报研究。后者采用风暴潮–波浪耦合模型(ADCIRC+SWAN)建立了天文潮–风暴潮–近岸波浪的精细化耦合预报系统。冯芒等[24]与潘锡山等[25]分别在台湾海峡和江苏沿海建立了海浪的精细化数值预报系统,可满足海浪的近岸精细化预报要求。这些工作明确了海洋动力灾害的精细化预报的重要意义,同时对海啸的精细化预警提供了有益的参考。
为了实现对地震海啸的准确和快速预警,科学认识海啸在生成后的传播过程及对我国近岸重点区域的精细化影响,本文以温州和台州为研究区域,基于非线性浅水波模型和多层嵌套网格,建立了越洋–近岸–局部的精细化地震海啸波流实时预警系统。首先针对2011年日本海啸对我国近岸的影响进行验证,选择合适的网格分辨率;进一步针对日本南海海槽和琉球海沟,应用该系统模拟计算潜在极端地震海啸对温州–台州地区的波–流精细化影响。
精细化地震海啸实时预警系统包括了地震海啸的数值计算、灾害分级与可视化处理,以及利用网页集成图形、动画产品得到的预警产品一页通。整个系统组成与流程参见图1。一旦地震发生,在得到震中、震级和震源几何特征等基本参数后。首先由Okada模型根据震源的特征参数计算得到海底地形的变形,进而基于瞬时响应假设得到水面初始扰动。基于非线性浅水波模型和多层嵌套网格,计算得到海啸在生成之后的传播以及对近岸的影响情况。在计算完成后,利用Python程序调用Matplotlib绘图库对计算结果进行图形化处理,包括海啸传播过程中的波面演化与流场演化过程,全场和近岸的最大波幅分布和最大流速分布,近场监测点的波面与流场时间序列。再根据海啸灾害等级将不同的测点进行危险性等级分类。最后,将所有的图形与动画产品集合成一个网页形式,便于查看与嵌套在公众网站上,参见图2
针对地震激发的海底地形变形,可采用弹性半空间位错理论。该理论首先由Steketee[26]提出,并经过许多学者的深入研究,最后经过Okada[27]的发展,得到在弹性半空间内断层滑动引起的位错及应变表达式,并在其后得到不断完善[28]。在各向同性的条件下,根据弹性半空间位错理论,某一矩形几何面发生滑移引发地表某点的动力响应所产生的位移,与滑移面的滑动量成正比。比例系数由滑移面的深度、倾角、几何尺寸,以及该点与滑移面的相对位置确定。根据弹性半空间位错理论,断层滑移在地表观测点(x y)产生的形变fxy)可以表示为
$f\left( {x,y} \right) = f\left( {L,W,d,\delta ,\alpha ,{\xi _1},{\xi _2},{U_1},{U_2},{U_3},x,y} \right),$
式中,断层面的走滑、倾滑和张性错动分量分别用U 1U 2U 3表示;断层的深度为d;长与宽分别为LW;走向角为α;(ξ 1ξ 2)表示滑移面下方区域的平面直角坐标;δ表示倾角。
在得到海啸波的初始条件后,再利用基于非线性浅水方程的数值模型GeoClaw[29]模拟计算海啸的传播过程。非线性浅水方程可表示为
$\frac{{\partial H}}{{\partial t}} + \frac{{\partial \left( {Hu} \right)}}{{\partial x}} + \frac{{\partial \left( {Hv} \right)}}{{\partial y}} = 0,$
$\frac{{\partial \left( {Hu} \right)}}{{\partial t}} + \frac{{\partial \left( {H{u^2} + {1/2}g{H^2}} \right)}}{{\partial x}} + \frac{{\partial \left( {Huv} \right)}}{{\partial y}} = - gH\frac{{\partial b}}{{\partial x}} - {\tau _x},$
$\frac{{\partial \left( {Hv} \right)}}{{\partial t}} + \frac{{\partial \left( {Huv} \right)}}{{\partial x}} + \frac{{\partial \left( {H{v^2} + {1/2}g{H^2}} \right)}}{{\partial y}} = - gH\frac{{\partial b}}{{\partial y}} - {\tau _y},$
式中,H为总水深;uvxy方向的速度分量;b表示地形。τ x τ y 表示底摩擦项,
${\tau _x} = \frac{{g{m^2}}}{{{H^{7/3}}}}Hu\sqrt {{{\left( {Hu} \right)}^2} + {{\left( {Hv} \right)}^2}},$
${\tau _y} = \frac{{g{m^2}}}{{{H^{7/3}}}}Hv\sqrt {{{\left( {Hu} \right)}^2} + {{\left( {Hv} \right)}^2}} ,$
式中,m为曼宁系数,表示底边界的粗糙程度。该模型利用了基于Godunov格式的有限体积方法进行数值离散,同时考虑了二阶修正项来减小数值震荡。自适应网格技术是该模型的一个特色,可以根据海啸波波高进行追踪判断是否对网格进行加密。该方法可以实现在海啸波未传播到的区域使用粗网格,减小计算量,提高计算效率,同时也可以用于网格嵌套,通过网格边界的传递实现海啸的越洋传播和局部高精度数值模拟相结合。该模型已在多个海啸事件中得到验证[5-6, 12]
根据《海啸灾害风险评估和区划技术导则》,将计算得到的测点的最大波幅和最大流速进行灾害分级,参见表1
为了实现对温州和台州地区的地震海啸精细化预警,选取的计算区域如图3所示。该区域包括了太平洋板块、鄂霍次克板块、阿默尔板块、扬子板块、菲律宾板块,以及巽他板块等多个板块的交界区域。因此可以针对西北太平洋地区发生的地震海啸进行预警。第一层网格的计算范围为15°~45°N,115°~150°E,地形数据分辨率为1′(https://maps.ngdc.noaa.gov/viewers/wcs-client/);第二层网格如图3a中的黑色线框表示,计算范围为25°~32°N,120°~128°E,地形数据分辨率为1′;第三层网格如图3b所示,包含了温州和台州的近岸区域,计算范围为27.2°~29.1°N,120.1°~122.2°E,地形数据分辨率为0.5′(全球地形SRTM30_PLUS数据)。第二层网格覆盖了从水深2 000 m到近岸的区域,可以完全描述海啸从深海到东海大陆架传播过程中的非线性效应。在近岸选择了5个潮位站,如图3b红点所示。
2011年日本东北9.0级地震海啸是近些年对我国沿海影响较大的一次海啸事件。震中位于宫城县首府仙台市以东的太平洋海域。据日本警察厅统计,截止到2011年4月6日,地震与海啸共造成12 554人死亡、15 077人失踪以及2 866人受伤,近20万栋建筑受损[30]。美国地质调查局(USGS)迅速给出了此次地震的WPhase矩张量解,包括走向角、倾角、滑移角,震源深度以及地震矩M 0=3.9×1022 N·m。本文采用Shao等[31]提供了此次地震的一种高精度震源,该震源被划分为190个长宽分别为25 km和20 km的单元板块,他们利用27个P波的波形、23个SH波,以及53个长周期表面波反演得到震源参数。总的地震矩达到5.84×1022 N·m。由于该地震矩比USGS的结果大了约1/3,因此对其进行一定的修正。利用Okada模型计算得到每个单元板块产生的地形变化,并将他们进行线性叠加得到海底的初始变形。利用该震源模型计算得到的数值结果已经与深海浮标和中国近岸的多个站点的实测数据进行了对比验证[5]
在数值计算中,计算网格的数量是制约计算时间的主要因素,而计算网格的数量是由网格分辨率所决定。如果网格分辨率过低,会降低计算精度,影响数值预警系统的准确性;如果网格分辨率较大,计算耗时较长,无法满足实时预警的要求。为了解决该预警系统的准确性和时效性问题,本文选取了3套不同的网格分辨率配置,如表2所示。利用3套不同的网格进行模拟计算,与实测的比较结果如图4所示。整体来看,数值计算结果都可以较准确计算得到海啸的到达时间和最大波幅。在石砰的计算结果相对较好,前3个海啸波都可以模拟到,而在坎门结果相对差一些,但也基本可以计算得到海啸的首波和次波。以石砰和坎门实测数据中首波的最大波幅为基准,3套网格的计算结果在石砰和坎门的误差率分别是9.4%、0.2%、13.1%和13.5%、23.4%、8.4%。网格1的整体计算精度最高,但计算时间也最长,无法满足海啸实时预警的需求。网格2和网格3的计算精度相比于网格1较低,但在潮位站的模拟结果与实测结果基本接近,同时可在10 min内完成计算。因此满足海啸实时预警的时效性和准确性的要求,在后面的计算中选择网格2进行系统构建。
图5a图5b分别为第一层网格计算得到的最大波幅和最大流速分布,对应图2产品一页通中的最大波幅分布和最大流速分布。海啸波主要影响日本近岸、太平洋,以及东海、黄海;海啸诱发的流场主要分布在日本近岸,以及东海、黄海的近岸。图6图7分别是海啸在传播到温州、台州近海的波面与最大波幅分布、流场与最大流速分布。此次海啸在日本东北海域生成后,在7 h左右抵达温州、台州海域,最大波幅在0.5 m左右。当海啸传播至近岸时,受复杂地形的影响流场也表现出了复杂多变的情况:由于海啸在受近岸的反射,流场也表现出向岸和离岸过程;同时还伴随沿岸流动的过程。海啸在近岸诱发的流场也较大,许多地区超过0.5 m/s。整体来看,该系统可以在较短时间内基于震源参数快速、准确地计算得到海啸的整体传播过程和近岸的海啸波与流场影响特征,满足地震海啸的实时预警要求。
日本南海海槽位于太平洋板块、菲律宾板块,以及欧亚板块的边缘交界处,其中菲律宾板块以43 mm/a的速度向下俯冲。1707年,该处曾发生了宝永地震,产生的最大的海啸波达到10 m[32]。在2011年日本东北发生9.0级地震海啸之后,由于这里的板块活跃性,日本南海海槽的潜在地震海啸再次得到了国际的关注[33-34]。国内学者也通过数值模拟,分析了日本南海海槽不同情境的潜在地震海啸对我国的影响[35-37]。本文应用该系统在三层计算网格条件下,模拟计算日本南海海槽发生9.0级特大地震海啸的传播过程及对温州–台州地区的精细化影响。
图8a图8b分别为第一层网格计算得到的最大波幅和最大流速分布。由于与2011年日本海啸的震中位置不同,日本南海海槽的潜在海啸不需要经过较多的绕射过程即可抵达中国沿海,因此对中国东南沿海的影响更大。海啸诱发的流场主要集中在日本近岸以及我国近岸,而在深水区域相对较小。图9图10分别是海啸在传播到温州和台州近海的波面与最大波幅分布,以及流场与最大流速分布。海啸在6 h抵达温州和台州近海,最大波幅超过1 m。近岸的流场过程也较为复杂多变。在未受到近岸的反射影响前,流向基本满足微小振幅前进波的速度分布特征,即波峰到静水面的流速与波浪前进方向一致,而波谷到静水面的流速与波浪传播方向相反。当受到近岸的反射和复杂地形的影响之后,流场的方向也变的更为复杂。图11是基于海啸风险等级的大陈和坎门的波面与流速的时间过程曲线,两处的波幅和流速均达到了橙色风险等级。
琉球海沟位于欧亚板块与菲律宾海板块之间的边界地带,海沟西坡是大陆性质的琉球岛弧,东坡是大洋性质的菲律宾海地壳。一旦这里发生大地震,产生的海啸会直接威胁我国东南沿海。基于高阶完全非线性Boussinesq方程,Zhao等[38-39]模拟计算了琉球海沟发生9.0级地震海啸对东海和近岸的影响。毛献忠等[36]、林法玲[40]、温燕林等[41]基于浅水波模型分别计算了琉球海沟发生不同场景的地震海啸对我国的影响。沿着琉球海沟的走向,本文将其分成了6个断裂带,如图3所示(RL1–RL6)。假设RL2–RL4共同发生8.8级地震,利用该系统在10 min完成海啸传播的数值模拟与计算结果的可视化。
图12a图12b分别为第一层网格计算得到的最大波幅和最大流速分布。由于其走向正对我国东南沿海,因此产生的海啸对我国东南沿海影响很大。海啸诱发的流场主要集中在我国近岸,而在深水区域相对较小。图13图14分别是海啸在传播到温州、台州近海时的波面与最大波幅分布、流场与最大流速分布。海啸在4 h抵达温州和台州近海,最大波幅超过1 m,最大流速超过1 m/s。与日本南海海槽潜在海啸的情况不同,由于海啸的先导波是波谷,因此靠近海岸的流场的方向与海啸的传播方向相反;进而受到近岸的影响,在温州海域进一步增强。图15是基于海啸风险等级的大陈和坎门的波面与流速的时间序列曲线。大陈的波幅达到橙色风险等级,流速为黄色风险等级;坎门的波幅和流速均达到了橙色风险等级。
本文主要基于Okada模型和非线性浅水波模型,针对我国浙江沿海的温州和台州地区建立了越洋–近海–局部的精细化地震海啸波流实时预警系统,近岸的分辨率为900 m。该系统通过并行化的数值计算、自动化的灾害分级和结果可视化,以及图形与动画的网页化集成,可在10 min得到地震海啸对近岸影响的精细化预报结果。利用2011年日本东北9.0级地震海啸在温州、台州的实测数据,对该系统的计算效率与可靠性进行验证。进一步应用该系统模拟计算了日本南海海槽和琉球海沟潜在极端海啸对近岸影响的精细化结果。
目前,该系统仅采用了4核的Intel(R) Xeon(R) CPU E5-1607 v3 @ 3.10GHz处理器进行数值计算,可通过提升计算机性能和近岸的计算精度,实现对港口、码头,以及重大海洋工程的精细化预警。在该系统中仅考虑了5个典型的潮位站,可通过在沿岸增加更多测点实现对岸段的精细化预报,且并不增加计算负荷。总体来说,该系统可有效地实现高效、准确的地震海啸精细化预警,为海啸的预警、减灾,以及辅助决策提供科学依据。
  • 国家重点研发计划(2016YFC1402000);海洋工程国家重点实验室(上海交通大学)开放课题(1604);留学人员科技活动项目择优资助。
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2019年第41卷第9期
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doi: 10.3969/j.issn.0253-4193.2019.09.014
  • 接收时间:2018-09-12
  • 首发时间:2026-04-03
  • 出版时间:2019-09-25
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  • 收稿日期:2018-09-12
  • 修回日期:2018-12-11
基金
国家重点研发计划(2016YFC1402000);海洋工程国家重点实验室(上海交通大学)开放课题(1604);留学人员科技活动项目择优资助。
作者信息
    1 国家海洋环境预报中心,北京 100081
    2 自然资源部海啸预警中心,北京 100081
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2种不同金属材料的力学参数

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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