CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 1-year storm in Los Angeles County

Projected Hazard: Model-derived ocean current velocities (in meters per second) 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, Los Angeles, 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 ocean current velocities for the 100-year storm and 0.0 m sea-level rise scenario. 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：针对给定风暴情景与海平面上升（Sea-Level Rise, SLR）情景，由模型推演得到的洋流速度（单位：米每秒）。 模型概述：海岸风暴建模系统（Coastal Storm Modeling System, CoSMoS）可在数百公里的大地理尺度上开展米级精度的精细化预测，模拟当前及未来海平面上升情景下风暴引发的海岸洪水与海岸侵蚀。针对南加州的CoSMoS v3.0版本可生成未来气候情景（海平面上升与风暴）下的预估结果，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：该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估存在多处调整，请仔细阅读模型概述并核查输出结果。本次呈现的数据信息完整。 详细说明： 模型框架：CoSMoS模型包含三个层级。 第一层级（Tier I）包含1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1套用于计算陆架海域波浪生成与传播的SWAN网格。FLOW与SWAN模型采用双向耦合模式：潮汐环流会影响波浪传播与生长，反之，波浪产生的轨道流速也会改变潮汐环流。第一层级的SWAN与FLOW模型采用相同的结构化曲线网格，网格范围从远海延伸至岸线，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）引发的比容水位抬升。 在每个模型时间步长内，均将时空变化的风场（分解为东向与北向分量）与海平面气压（Sea-Level Pressure, SLP）场施加至所有网格单元，该数据来自CaRD10（加州大学斯克里普斯海洋研究所Dan Cayan博士，2014年私人通信）。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小时分辨率风场数据，对21世纪代表性浓度路径（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）：第二层级在近岸及需要更高分辨率物理过程模拟的区域（例如海湾、港口与河口）采用更高的网格分辨率。通过1套嵌套的外层网格与多套双向耦合的区域分解（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。第二层级沿南加州湾被划分为11个分区，以降低计算量并在算力限制内完成模拟。 从第一层级模拟结果中提取的水位与诺依曼（Neumann）时间序列，分别施加至每个第二层级子模型外层网格的岸线平行开边界与侧向开边界。部分子模型在侧向诺依曼边界处出现不稳定，针对此类情况，将一侧或两侧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均来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双向通信。鉴于这种单向嵌套可能在第二层级边界附近产生误差，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上存在重叠。在向陆方向，第二层级区域分解网格延伸至10米地形等高线，仅在洛杉矶河等河道或其他低洼区域大幅向内陆延伸的情况下存在例外。与第一层级模拟使用的时空变化风场与SLP场完全一致的数据集，被施加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抬升或降低）。 为模拟高河道向海径流与沿岸风暴潮水位抬升在内陆交汇引发的回流加剧洪水，第二层级FLOW域共包含42套河川径流时间序列。时变河川径流被施加至闭合边界，或作为点源分布至相关模型域内。 波浪计算采用SWAN模型，每个第二层级子模型对应两套网格：1套覆盖范围与外层FLOW网格一致的粗网格，以及1套分辨率更高的双向耦合近岸嵌套网格。近岸网格的范围从水深约800-1000米的区域延伸至陆上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，每隔约1千米施加至第二层级子模型外层SWAN网格的开边界处。与第一层级模拟使用的时空变化风场完全一致的数据集，同时被施加至两套第二层级SWAN网格，以计算局地波浪生成。 第三层级（Tier III）：针对整个南加州湾的第三层级包含4802条跨岸断面（Cross-Shore Transects, CST），断面沿沿岸方向间距约100米。剖面范围从-15米等深线延伸至至少高于NAVD88基准面10米的区域，若剖面向陆端存在泻湖或其他水道，则对断面进行截断。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Hs、峰值周期Tp、峰值入射波向Dp），被施加至每条跨岸断面的开边界。XBeach模型采用静水压模式（不考虑垂直压强梯度）运行，包含基于事件的形态动力变化。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。 XBeach模拟被纳入CoSMoS模型，以模拟低频重力波（infragravity waves）的影响：相较于短波入射波，低频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（Tp>15秒）的破碎，美国西海岸沿岸尤其容易受到低频重力波的影响。 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（topobathymetric DEM）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测深数据集。地形数据来自2009-2011年加州海岸保护局激光雷达（lidar）项目采集的裸地激光雷达数据，测深数据来自2009-2010年的测深激光雷达数据，以及2001-2013年采集的多波束与单波束声学数据。本DEM旨在尽可能精准地刻画近岸、海滩与崖壁的形态，整合了数十套地形与测深数据集，用于填充第一与第二层级的大部分网格。 为描述并纳入长期岸线演化的影响，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岸线（Vitousek与Barnard，2015）与崖壁（Limber等，2015）侵蚀预估结果，实现岸线垂直剖面的演化。将剖面产生的高程变化进行空间合并，得到统一的海岸演化三维可视化结果，用于修改DEM。这些数据被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，并确定每个海平面上升情景下的最终预估洪水深度。所有数据均采用NAD83水平基准面与NAVD88垂直基准面。第二与第三层级的数据采用UTM投影11区坐标系。 模拟事件：本模型系统针对预设的感兴趣情景运行，例如1年一遇或100年一遇的风暴事件叠加海平面上升情景。首先从岸线处的总水位代理值（Total Water Level Proxies, TWLpx）时间序列中识别风暴。假设总水位由主要过程线性叠加而成，针对21世纪大部分时段（2010-2100年）计算了TWLpx时间序列。随后对TWLpx时间序列进行极端事件识别，这些极端事件将作为后续CoSMoS模拟的边界条件。共确定多组100年一遇事件（有效波高、峰值周期、入射波向各不相同），并用于多轮模型模拟，以更好地考量区域与方向对洪水的影响。将模型结果进行整合与汇编，得到针对特定情景的洪水预估合成结果。 输出结果：输出结果包含100年一遇风暴与0.0米海平面上升情景下的预估洋流速度。数据对应近岸区域，包括在相同风暴与海平面上升模拟中，因风暴潮、海平面异常、潮汐水位与波浪爬高而易受海岸洪水影响的区域。 参考文献： 1. Howell S, Smith-Konter B, Frazer N, Tong X, Sandwell D. 2016. The vertical fingerprint of earthquake cycle loading in southern California: *Nature Geoscience*, 9: 611-614. doi:10.1038/ngeo2741. 2. Limber P, Barnard PL, Hapke C. 2015. Towards projecting the retreat of California’s coastal cliffs during the 21st Century. In: Wang P, Rosati JD, Cheng J, eds. *Coastal Sediments: 2015*. World Scientific, 14p. doi:10.1142/9789814689977_0245 3. Roelvink JA, Reniers A, van Dongeren AR, van Thiel de Vries J, McCall R, Lescinski J. 2009. Modeling storm impacts on beaches, dunes and barrier islands: *Coastal Engineering*, 56: 1133-1152. doi:10.1016/j.coastaleng.2009.08.006 4. Tolman HL, Balasubramaniyan B, Burroughs LD, Chalikov DV, Chao YY, Chen HS, Gerald VM. 2002. Development and implementation of wind generated ocean surface wave models at NCEP: *Weather and Forecasting*, 17: 311-333. 5. Vitousek S, Barnard PL. 2015. A non-linear, implicit one-line model to predict long-term shoreline change. In: Wang P, Rosati JD, Cheng J, eds. *Coastal Sediments: 2015*. World Scientific, 14p. doi:10.1142/9789814689977_0215