CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 20-year storm in San Diego County

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario.
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 wave height for the storm and sea-level rise scenario indicated. Data correspond to the near-shore region including 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.

预估灾害参数：基于模型推导的给定风暴条件与海平面上升（Sea-Level Rise, SLR）情景下的有效波高（单位：米）。

模型概述：海岸风暴模拟系统（Coastal Storm Modeling System, CoSMoS）可在数百公里的大地理尺度上，针对当前及未来海平面上升（Sea-Level Rise, SLR）情景，精细预测风暴引发的海岸洪水与侵蚀过程，空间分辨率可达米级。南加州地区的CoSMoS v3.0版本可针对未来气候情景（含海平面上升与风暴过程）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。多个区域的预测结果相较于第一阶段存在多处调整，请仔细阅读模型概述并仔细检查输出结果。本次呈现的数据信息完整无误。

模型细节：CoSMoS模型包含三个层级。第一层级（Tier I）包含一套Delft3D水动力FLOW网格，用于计算潮汐、水位变化、水流与流场；以及一套SWAN波浪网格，用于计算大陆架区域的波浪生成与传播。FLOW与SWAN模型采用双向耦合方式，因此潮汐流会被纳入波浪传播与成长过程，反之，波浪产生的轨道流速也会改变潮汐流场。第一层级的SWAN与FLOW网格采用完全一致的结构化曲线网格，覆盖范围从远海至近岸，分辨率从远海的0.5公里逐步提升至近岸的0.2公里。在第一层级FLOW网格的所有开边界处，均加载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）引发的比容水位升高。时空变化的风场（分解为东向与北向分量）与海平面气压（Sea-Level Pressure, SLP）场源自CaRD10数据集（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），将在每个模型时间步长内加载至所有网格单元。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GFDL-ESM2M全球气候模型（Global Climate Model, GCM）的3小时间隔风场数据，针对21世纪典型浓度路径（Representative Concentration Pathway, RCP）4.5情景（2011-2100年）进行了预测。

第二层级（Tier II）在近岸区域及需要更高分辨率物理过程解析的区域（例如海湾、港口与河口）采用更高的空间分辨率。采用一套嵌套外网格与多套双向耦合区域分解（Domain Decomposition, DD）结构化网格，可在需要的区域实现局部网格加密与更高分辨率。为缩短计算时间并在算力限制内完成模拟，第二层级被划分为南加州湾沿岸的11个分段。从第一层级模拟结果中提取的水位与诺伊曼时间序列，分别加载至每个第二层级子模型外网格的岸线平行边界与侧向开边界。部分子模型在侧向诺伊曼边界处出现不稳定情况，针对此类情况，将一个或两个侧向边界转换为水位时间序列，或保持未赋值状态。由于开边界时间序列源自已完成的第一层级模拟，第二层级与第一层级之间不存在数据交互。考虑到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，且模型边界附近的数据通常存在不确定性，第二层级子模型的范围在沿岸方向设置为相互重叠。在向陆方向，第二层级区域分解网格延伸至10米等深线；仅在河道（例如洛杉矶河）或其他低洼区域向内陆延伸极远的情况下存在例外。与第一层级模拟中使用的时空变化风场与SLP场完全一致的数据集，将加载至所有第二层级区域分解网格，以模拟风增水与局部逆气压效应（Inverse Barometer Effect, IBE，即水位随大气压强梯度变化而升降）。为模拟高河流向海流量与向内陆迁移的海岸风暴潮高位叠加引发的回流加剧洪水过程，第二层级FLOW域中共包含42套时间序列河流流量数据。时变河流流量将加载至闭合边界处，或作为点源分布于相关模型域内。波浪计算采用SWAN模型，每个第二层级子模型对应两套网格：一套覆盖范围与外FLOW网格一致的大网格，以及一套更高分辨率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，设置向陆边界是为了实现更高SLR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，将沿第二层级子模型外网格的开边界约每1公里加载一次。与第一层级模拟中使用的时空变化风场完全一致的数据集，将同时加载至两套第二层级SWAN网格，以模拟局地波浪生成过程。

覆盖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。若断面向陆端存在泻湖或其他水道，则对断面进行截断处理。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Hs、峰值周期Tp、峰值入射波向Dp），将加载至每条跨岸断面的开边界。XBeach模型采用静水压力模式（不考虑垂直压强梯度）运行，包含基于事件的地貌动力学变化过程。每个断面上均可计算波浪传播、双向波流相互作用、水位变化与波浪爬高。CoSMoS模型中加入XBeach模拟模块，用于计算可显著延长波浪爬高影响范围的亚重力波（Roelvink等，2009），相较于短波入射波的情况。美国西海岸由于长周期涌浪（Tp>15秒）的破碎作用，岸线区域对亚重力波尤为敏感。Delft3D模型（针对高关注度海湾与沼泽区域）与开放海岸XBeach模型（针对跨岸断面）得到的最终水位（Water Levels, WLs）将进行空间合并与插值，生成10米分辨率的网格数据。将这些水位高程与原始的2米分辨率数字高程模型（Digital Elevation Model, DEM）进行差值计算，即可确定最终的洪水淹没范围与淹没深度。

模型事件模拟：模型系统将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。首先从岸线处的总水位代理指标（Total Water Level Proxies, TWLpx）时间序列中识别风暴事件。假设贡献于总水位的主要过程为线性叠加，可计算21世纪绝大多数时段（2010-2100年）的TWLpx时间序列。随后对TWLpx时间序列进行极端事件筛选，以此作为后续CoSMoS建模的边界条件。确定多组100年一遇风暴事件（有效波高、峰值周期、入射波向存在差异），并开展多组模型模拟，以更全面地考量区域与方向对洪水淹没的影响。将模型结果进行合并与整理，生成针对特定情景的洪水预测合成结果。

数字高程模型（DEM）：本研究的无缝海岸地形水深一体化数字高程模型主要基于加州海岸地形水深合并项目DEM构建，美国地质调查局地球资源观测与科学（Earth Resources Observation and Science, EROS）中心对其进行了部分修改，以纳入最新的高分辨率地形与水深数据集。地形数据源自2009-2011年加州海岸保护局激光雷达项目采集的裸地激光雷达（light detection and ranging, lidar）数据，水深数据源自2009-2010年的水深激光雷达数据，以及2001-2013年采集的声学多波束与单波束测深数据。本DEM的构建旨在尽可能精准地刻画近岸、海滩与崖岸的地表形态，整合了数十套地形与水深数据集。这些数据被用于填充绝大多数第一与第二层级网格。为描述并纳入长期岸线演变的影响，包括累积风暴活动、季节趋势、厄尔尼诺南方涛动（El Niño-Southern Oscillation, ENSO）与SLR，本DEM将针对每个SLR情景进行修改。将长期岸线（Vitousek与Barnard，2015）与崖岸（Limber等，2015）侵蚀预测结果沿跨岸断面进行高效合并，以更新岸线垂直断面。将断面的高程变化进行空间合并，生成连贯的三维海岸演变结果，用于修改DEM。这些数据将用于生成第二阶段第三层级XBeach模拟所用的4802条跨岸断面初始剖面，并确定每个SLR情景下的最终预测洪水深度。所有数据均采用NAD83水平基准面与NAVD88垂直基准面。第二与第三层级数据采用通用横轴墨卡托投影（Universal Transverse Mercator, UTM）11带。

模型输出包含：指定风暴与海平面上升情景下的预估波高。数据覆盖近岸区域，包含在同一场风暴与海平面上升模拟过程中，易受风暴潮、海平面异常、潮汐高程与波浪爬高影响的区域。

引用文献：
1. 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.
2. 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
3. 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. 1133–1152, 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, Development and implementation of wind generated ocean surface wave models at NCEP: "Weather and Forecasting", v. 17, p. 311-333.
5. 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.