CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 100-year storm in San Diego County

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with critical storm-hazards information that can be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. Phase 2 data for Southern California include flood-hazard information for the coast from the border of Mexico to Pt. Conception. Several changes from Phase 1 projections are reflected in many areas; please read the model summary and inspect output carefully. Data are complete for the information presented. Details: Model background: The CoSMoS model comprises three tiers. Tier I consists of one Delft3D hydrodynamics FLOW grid for computation of tides, water level variations, flows, and currents and one SWAN grid for computation of wave generation and propagation across the continental shelf. The FLOW and SWAN models are two-way coupled so that tidal currents are accounted for in wave propagation and growth and conversely, so that orbital velocities generated by waves impart changes on tidal currents. The Tier I SWAN and FLOW models consist of identical structured curvilinear grids that extend from far offshore to the shore and range in resolution from 0.5 km in the offshore to 0.2 km in the nearshore. Spatially varying astronomic tidal amplitudes and phases and steric rises in water levels due to large-scale effects (for example, a prolonged rise in sea level) are applied along all open boundaries of the Tier I FLOW grid. Winds (split into eastward and northward components) and sea-level pressure (SLP) fields from CaRD10 (Dr. Dan Cayan, Scripps Institute of Oceanography, San Diego, California, written commun., 2014) that vary in both space and time are applied to all grid cells at each model time-step. Deep-water wave conditions, applied at the open boundaries of the Tier I SWAN model runs, were projected for the 21st century Representative Concentration Pathway (RCP) 4.5 climate scenario (2011-2100) using the WaveWatch III numerical wave model (Tolman and others, 2002) and 3-hourly winds from the GFDL-ESM2M Global Climate Model (GCM). Tier II provides higher resolution near the shore and in areas that require greater resolution of physical processes (such as bays, harbors, and estuaries). A single nested outer grid and multiple two-way coupled domain decomposition (DD) structured grids allow for local grid refinement and higher resolution where needed. Tier II was segmented into 11 sections along the Southern California Bight, to reduce computation time and complete runs within computational limitations. Water-level and Neumann time-series, extracted from Tier I simulations, are applied to the shore-parallel and lateral open boundaries of each Tier II sub-model outer grid respectively. Several of the sub-models proved to be unstable with lateral Neumann boundaries; for those cases one or both of the lateral boundaries were converted to water-level time-series or left unassigned. The open-boundary time-series are extracted from completed Tier I simulations so that there is no communication from Tier II to Tier I. Because this one-way nesting could produce erroneous results near the boundaries of Tier II and because data near any model boundary are always suspect, Tier II sub-model extents were designed to overlap in the along-coast direction. In the landward direction, Tier II DD grids extend to the 10-m topographic contour; exceptions exist where channels (such as the Los Angeles River) or other low-lying regions extend very far inland. Space- and time-varying wind and SLP fields, identical to those used in Tier I simulations, are applied to all Tier II DD grids to allow for wind-setup and local inverse barometer effects (IBE, rise or depression of water levels in response to atmospheric pressure gradients). A total of 42 time-series fluvial discharges are included in the Tier II FLOW domains in an effort to simulate exacerbated flooding caused by backflow at the confluence of high river seaward flows and elevated coastal surge levels migrating inland. Time-varying fluvial discharges are applied either at the closed boundaries or distributed as point sources within the relevant model domains. Wave computations are accomplished with the SWAN model using two grids for each Tier II sub-model: one larger grid covering the same area as the outer FLOW grid and a second finer resolution two-way coupled nearshore nested grid. The nearshore grid extends from approximately 800-1,000 m water depth up to 8-10 m elevations onshore. The landward extension is included to allow for wave computations of the higher SLR scenarios. Time- and space-varying 2D wave spectra extracted from previously completed Tier I simulations are applied approximately every kilometer along the open boundaries of the outer Tier II sub-model SWAN grids. The same space- and time-varying wind fields used in Tier I simulations are also applied to both Tier II SWAN grids to allow for computation of local wave generation. Tier III for the entire Southern California Bight consists of 4,802 cross-shore transects (CST) spaced approximately 100 m apart in the along-shore direction. The profiles extend from the -15 m isobath to at least 10 m above NAVD88. The CSTs are truncated for cases where a lagoon or other waterway exists on the landward end of the profile. Time-varying water levels and wave parameters (significant wave heights, Hs; peak periods, Tp; and peak incident wave directions, Dp), extracted from Tier II grid cells that coincide with the seaward end of the CSTs, are applied at the open boundary of each CST. The XBeach model is run in a hydrostatic (no vertical pressure gradients) mode including event-based morphodynamic change. Wave propagation, two-way wave-current interaction, water-level variations, and wave runup are computed at each transect. XBeach simulations are included in the CoSMoS model to account for infragravity waves that can significantly extend the reach of wave runup (Roelvink and others, 2009) compared to short-wave incident waves. The U.S. west coast is particularly susceptible to infragravity waves at the shore due to breaking of long-period swell waves (Tp > 15). Resulting water levels (WLs) from both Delft3D (high interest bays and marshes) and open-coast XBeach (CSTs) were spatially combined and interpolated to a 10 m grid. These WL elevations are differenced from the originating 2 m digital elevation model (DEM) to determine final flooding extent and depth of flooding. Events: The model system is run for pre-determined scenarios of interest such as the 1-yr or 100-yr storm event in combination with sea-level rise. Storms are first identified from time-series of total water level proxies (TWLpx) at the shore. TWLpx are computed for the majority of the 21st century (2010-2100), assuming a linear super-position of the major processes that contribute to the overall total water level. TWLpx time-series are then evaluated for extreme events, which define the boundary conditions for subsequent modeling with CoSMoS. Multiple 100-yr events are determined (varying Hs, Tp, Dp) and used for multiple model runs to better account for regional and directional flooding affects. Model results are combined and compiled into scenario-specific composites of flood projection. Digital Elevation Model (DEM): Our seamless, topobathymetric digital elevation model (DEM) was based largely upon the Coastal California TopoBathy Merge Project DEM, with some modifications performed by the USGS Earth Resources Observation and Science (EROS) Center to incorporate the most recent, high-resolution topographic and bathymetric datasets available. Topography is derived from bare-earth light detection and ranging (lidar) data collected in 2009-2011 for the CA Coastal Conservancy Lidar Project and bathymetry from 2009-2010 bathymetric lidar as well as acoustic multi- and single-beam data collected primarily between 2001 and 2013. The DEM was constructed to define the shape of nearshore, beach, and cliff surfaces as accurately as possible, utilizing dozens of bathymetric and topographic data sets. These data were used to populate the majority of the Tier I and II grids. To describe and include impacts from long-term shoreline evolution, including cumulative storm activity, seasonal trends, ENSO, and SLR, the DEM was modified for each SLR scenario. Long-term shoreline (Vitousek and Barnard, 2015) and cliff (Limber and others, 2015) erosion projections were efficiently combined along the cross-shore transects to evolve the shore-normal profiles. Elevation changes from the profiles were spatially-merged for a cohesive, 3D depiction of coastal evolution used to modify the DEM. These data are used to generate initial profiles of the 4,802 CSTs used for Phase 2 Tier III XBeach modeling and determining final projected flood depths in each SLR scenario. All data are referenced to NAD83 horizontal datum and NAVD88 vertical datum. Data for Tiers II and III are projected in UTM, zone 11. Outputs include: Projected flood-hazard depth and duration for the storm and sea-level rise indicated. Data correspond to the areas vulnerable to coastal flooding due to storm surge, sea-level anomalies, tide elevation, and wave run-up during the same storm and sea-level rise simulation. References Cited: Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, The vertical fingerprint of earthquake cycle loading in southern California: Nature Geoscience, v. 9, p. 611-614, doi:10.1038/ngeo2741. Limber, P., Barnard, P.L. and Hapke., C., 2015, Towards projecting the retreat of California’s coastal cliffs during the 21st Century: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0245 Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, Modeling storm impacts on beaches, dunes and barrier islands: Coastal Engineering, v. 56, p. 1,133–1,152, doi:10.1016/j.coastaleng.2009.08.006. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, Development and implementation of wind generated ocean surface wave models at NCEP: Weather and Forecasting, v. 17, p. 311-333. Vitousek, S. and Barnard, P.L., 2015, A non-linear, implicit one-line model to predict long-term shoreline change: in, Wang, P., Rosati, J.D., and Cheng, J., (eds.), The Proceedings of the Coastal Sediments: 2015, World Scientific, 14 p., doi:10.1142/9789814689977_0215.### 预估灾害 预估灾害：针对指定的风暴情景与海平面上升（Sea-Level Rise, SLR）情景，当前海岸线向陆地区域因该风暴事件发生淹水的最大洪水表面深度（单位：厘米）。 ### 模型概述 海岸风暴模拟系统（Coastal Storm Modeling System, CoSMoS）可针对当前及未来海平面上升（Sea-Level Rise, SLR）情景，在大范围地理尺度（数百千米）上对风暴引发的海岸淹水与侵蚀开展米级精度的详细预测。针对南加州的CoSMoS v3.0版本可针对未来气候情景（海平面上升与风暴）生成预测结果，为应急响应人员与海岸规划者提供关键的风暴灾害信息，助力提升公共安全、减轻物理损失，并在复杂海岸环境中更高效地管理与调配资源。 ### 南加州第二阶段数据 南加州第二阶段数据涵盖了从墨西哥边境至康塞普申角（Pt. Conception）沿岸的洪水灾害信息。多个区域的结果相较于第一阶段预测存在多处调整，请仔细阅读模型说明并核查输出结果。本次呈现的数据信息完整。 ### 详细说明 #### 模型背景 CoSMoS模型包含三个层级。第一层级（Tier I）包含一套用于计算潮汐、水位变化、流场与洋流的Delft3D水动力FLOW网格，以及一套用于计算陆架区域波浪生成与传播的SWAN网格。FLOW与SWAN模型采用双向耦合方式，使得波浪传播与成长过程中会考虑潮汐流的影响，同时波浪产生的轨道流速也会改变潮汐流。第一层级的SWAN与FLOW模型采用完全一致的结构化曲线网格，覆盖从远海至沿岸的区域，分辨率从远海的0.5千米逐步提升至近岸的0.2千米。在第一层级FLOW网格的所有开边界处，均施加了空间分布变化的天文潮汐振幅与相位，以及由大尺度效应（例如长期海平面上升）引发的水位比容上升量。在每个模型时间步长内，所有网格单元均会加载由CaRD10（加州大学圣迭戈分校斯克里普斯海洋研究所Dan Cayan博士，2014年私人通信）提供的时空变化风场（分解为东向与北向分量）与海平面气压（Sea-Level Pressure, SLP）场。针对第一层级SWAN模型开边界的深水波浪条件，采用WaveWatch III数值波浪模型（Tolman等，2002）与来自GFDL-ESM2M全球气候模型（Global Climate Model, GCM）的3小时分辨率风场，对21世纪典型浓度路径（Representative Concentration Pathway, RCP）4.5情景（2011-2100年）下的波浪条件进行了预估。 第二层级（Tier II）在近岸区域以及需要更高物理过程分辨率的区域（例如海湾、港口与河口）采用更高的网格分辨率。通过一套嵌套的外部网格与多套双向耦合的区域分解（Domain Decomposition, DD）结构化网格，可实现局部区域的网格加密与按需提升分辨率。为缩短计算时长并在计算资源限制内完成模拟，第二层级沿南加州湾被划分为11个分区。 从第一层级模拟结果中提取的水位与诺依曼（Neumann）时间序列，分别加载至每个第二层级子模型外部网格的沿岸平行开边界与侧向开边界。部分子模型在采用侧向诺依曼边界时出现不稳定情况，针对这些场景，将一个或两个侧向边界转换为水位时间序列，或保留为未赋值状态。由于开边界时间序列均从已完成的第一层级模拟结果中提取，第二层级与第一层级之间不存在数据交互。由于这种单向嵌套方式可能在第二层级边界附近产生错误结果，且任何模型边界附近的数据均存在不确定性，因此第二层级子模型的范围在沿岸方向上存在重叠。在向陆方向，第二层级DD网格延伸至10米等深线的地形等高线，仅在部分区域存在例外：例如洛杉矶河等河道或其他低洼区域可延伸至更内陆的位置。所有第二层级DD网格均加载与第一层级模拟完全一致的时空变化风场与SLP场，以模拟风增水与局部逆气压效应（Inverse Barometer Effect, IBE，即响应大气压力梯度的水位上升或下降）。 为模拟高河道向海径流与沿海风暴潮水位升高向内陆迁移交汇时产生的回流加剧淹水情况，第二层级FLOW区域共包含42套河道径流量时间序列。时变河道径流量加载至闭合边界，或作为点源分布至相关模型区域内。 波浪计算采用SWAN模型，每个第二层级子模型均配备两套网格：一套覆盖范围与外部FLOW网格一致的大尺度网格，以及一套分辨率更高的双向耦合近岸嵌套网格。近岸网格的覆盖范围从约800-1000米水深区域延伸至陆上8-10米高程区域，该向陆延伸范围可支持更高海平面上升情景下的波浪计算。从已完成的第一层级模拟结果中提取的时空变化二维波浪谱，沿外部第二层级子模型SWAN网格的开边界每约1千米加载一次。第一层级模拟中使用的时空变化风场也同时加载至两套第二层级SWAN网格，以支持局部波浪生成过程的计算。 针对整个南加州湾的第三层级（Tier III）包含4802条跨岸断面（Cross-Shore Transects, CST），沿沿岸方向的间距约为100米。这些断面从-15米等深线延伸至至少高于北美垂直基准面1988（North American Vertical Datum 1988, NAVD88）10米的位置。当断面向陆端存在泻湖或其他水道时，跨岸断面将被截断。从与跨岸断面向海端重合的第二层级网格单元中提取的时变水位与波浪参数（有效波高（significant wave heights, Hs）、峰值周期（peak periods, Tp）与入射波峰值方向（peak incident wave directions, Dp）），加载至每条跨岸断面的开边界。XBeach模型采用静水压模式（不考虑垂直压力梯度）运行，包含基于事件的地形动力变化。每个断面上均会计算波浪传播、双向波流相互作用、水位变化与波浪爬高。 CoSMoS模型中加入XBeach模拟的目的是考虑亚重力波（infragravity waves）的影响：相较于短波入射波，亚重力波可显著提升波浪爬高的影响范围（Roelvink等，2009）。由于长周期涌浪（峰值周期Tp>15秒）的破碎作用，美国西海岸沿岸区域对亚重力波尤为敏感。 将Delft3D模型（高关注度海湾与沼泽区域）与开放海岸XBeach模型（跨岸断面）得到的最终水位（Water Levels, WLs）进行空间合并，并插值至10米分辨率的网格中。将这些水位高程值与原始的2米分辨率数字高程模型（Digital Elevation Model, DEM）进行差值计算，以确定最终的淹水范围与淹水深度。 #### 模拟事件 本模型系统针对预设的感兴趣情景开展模拟，例如结合海平面上升的1年一遇或100年一遇风暴事件。首先通过沿岸总水位代理（Total Water Level proxies, TWLpx）时间序列识别风暴：假设对构成总水位的主要过程进行线性叠加，可计算得到21世纪大部分时段（2010-2100年）的TWLpx时间序列。随后对TWLpx时间序列进行极端事件评估，这些极端事件将作为后续CoSMoS建模的边界条件。本次共确定多个100年一遇风暴事件（有效波高、峰值周期、入射波方向各有差异），并开展多组模型模拟，以更好地反映区域与方位对洪水淹水的影响。将模型结果整合并汇编为针对特定情景的洪水预测合成结果。 #### 数字高程模型（Digital Elevation Model, DEM） 本研究的无缝地形水深一体化数字高程模型（DEM）主要基于加州海岸地形水深合并项目DEM构建，由美国地质调查局地球资源观测与科学（Earth Resources Observation and Science, EROS）中心进行了部分修改，以纳入最新的高分辨率地形与水深数据集。地形数据来自2009-2011年加州海岸保护局激光雷达（Light Detection and Ranging, lidar）项目采集的裸地激光雷达数据，水深数据来自2009-2010年的水深激光雷达数据，以及2001年至2013年采集的声学多波束与单波束测深数据。本DEM通过整合数十套地形与水深数据集，尽可能精准地刻画近岸、海滩与崖岸的地表形态，这些数据被用于填充大部分第一与第二层级网格。为描述并纳入长期海岸线演变的影响，包括累积风暴活动、季节趋势、厄尔尼诺南方涛动（ENSO）与海平面上升，本DEM针对每个海平面上升情景进行了修改。通过沿跨岸断面整合长期海岸线（Vitousek与Barnard，2015）与崖岸（Limber等，2015）侵蚀预测结果，可更新沿岸垂直断面。将断面的高程变化进行空间合并，得到连贯的海岸演变三维可视化结果，用于修改DEM。这些数据被用于生成第二层级与第三层级XBeach模拟所用的4802条跨岸断面的初始剖面，并确定每个海平面上升情景下的最终预估洪水深度。所有数据均采用北美大地基准面1983（North American Datum 1983, NAD83）作为水平基准面，北美垂直基准面1988（NAVD88）作为垂直基准面。第二与第三层级的数据采用通用横轴墨卡托投影第11带（Universal Transverse Mercator, UTM, Zone 11）进行投影。 #### 输出结果 输出内容包括：指定风暴与海平面上升情景下的预估洪水灾害深度与持续时间。数据对应了同一风暴与海平面上升模拟期间，因风暴潮、海平面异常、潮汐高程与波浪爬高导致的海岸淹水脆弱区域。 ### 参考文献 1. Howell, S., Smith-Konter, B., Frazer, N., Tong, X., and Sandwell, D., 2016, 《自然·地球科学（Nature Geoscience）》，第9卷，第611-614页，doi:10.1038/ngeo2741. 2. Limber, P., Barnard, P.L. and Hapke., C., 2015, 21世纪加州海岸崖岸后退的预估研究：收录于Wang, P., Rosati, J.D., and Cheng, J.（编辑），《2015年海岸沉积物会议论文集》，World Scientific出版社，共14页，doi:10.1142/9789814689977_0245. 3. Roelvink, J.A., Reniers, A., van Dongeren, A.R., van Thiel de Vries, J., McCall, R., and Lescinski, J., 2009, 《海岸工程（Coastal Engineering）》，第56卷，第1133-1152页，doi:10.1016/j.coastaleng.2009.08.006. 4. Tolman, H.L., Balasubramaniyan, B., Burroughs, L.D., Chalikov, D.V., Chao, Y.Y., Chen H.S., Gerald, V.M., 2002, 《天气预报（Weather and Forecasting）》，第17卷，第311-333页. 5. Vitousek, S. and Barnard, P.L., 2015, 预测长期海岸线变化的非线性隐式单线模型：收录于Wang, P., Rosati, J.D., and Cheng, J.（编辑），《2015年海岸沉积物会议论文集》，World Scientific出版社，共14页，doi:10.1142/9789814689977_0215.