RAPID: Collaborative Research: Deepwater Horizon: Simulating the three dimensional dispersal of aging oil with a Lagrangian approach

知识价值：模拟墨西哥湾石油在地下和地面的扩散，目的是产生不同大小的石油随着时间的推移而扩散的概率包络。所建议的模型系统已准备好响应。SABGOM墨西哥湾和南大西洋湾的流体动力学模型已经成功地与LTRANS相结合，LTRANS是一种全三维拉格朗日粒子跟踪模型，能够模拟亚网格尺度的湍流运动，以及随时间变化的粒子属性，如直径、密度和上升/下沉速度。在距离深水源几百米以上的地方（取决于周围的水流速度和分层），石油的扩散主要取决于油滴的行为，油滴被分成不同的大小。这些油滴在上升速率上可能有数量级的差异（例如，直径为300微米和30微米的颗粒分别为6毫米/秒和0.06毫米/秒），并且随着年龄的增长，直径也会发生变化。乳化、与悬浮颗粒物的相互作用、溶解等过程也会影响液滴的行为。我们的拉格朗日方法非常适合模拟油的扩散，因为初始液滴特性和随时间变化的液滴行为的差异很容易被纳入。在该项目中，SABGOM/LTRANS耦合模型系统将在深水地平线漏油事件期间运行，并生成模型输出的地图和动画。该模型的结果将与现有的观测结果进行比较，并将提供给溢油应急社区。近期，将使用SABGOM模型模拟的现有流场进行一系列LTRANS模拟。拉格朗日色散运行将用代表井上方近场羽流的连续粒子源初始化。每次运行都将基于一组关于粒子行为的特定假设来模拟这些粒子的远场色散。随着有关气泡和油滴的大小和组成的更完整信息的出现，将从LTRANS的运行集合中选择最真实的颗粒分布。作为这项工作的一部分，将编制一个改进的SABGOM模式的后预报，供LTRANS使用，并将根据海洋物理观测对模式技能进行量化。此外，欧拉和拉格朗日的石油扩散预测将与观测结果进行定量比较，以便利用这两种方法的优势，为石油响应社区提供最现实的预测。更广泛的影响：中期结果将是开源模型和模型结果，使用现有的和可能新的粒子跟踪技术，用于地球科学和溢油响应社区。将该模型纳入社区表面动力学建模系统（CSDMS）的框架，将确保编码结构适合与其他模型耦合，并在未来用于研究和教育目的的分发。此外，来自美国地质勘探局的团队成员将确保LTRANS能够与符合cf标准的模型输出一起运行，使其能够与超过17个沿海模型一起运行，从而可以在整个美国沿海水域进行模拟和预测。除了为石油泄漏救援人员提供及时的信息外，该项目还将为未来调查墨西哥湾石油与商业和生态重要生物幼虫运输之间的相互作用奠定基础。

Intellectual Merit: Simulation of the subsurface and surface dispersal of oil in the Gulf of Mexico will be conducted with the objective of producing probabilistic envelopes of the spread of different size classes of oil as they age over time. The proposed model system is ready to respond. The SABGOM hydrodynamic model of the Gulf of Mexico and South Atlantic Bight has been successfully coupled with LTRANS, a fully three-dimensional Lagrangian particle tracking model capable of simulating sub-grid scale turbulent motion as well as time-varying particle attributes like diameter, density, and rise/sinking velocities. At distances greater than a few hundred meters above the deepwater source (depending on ambient current speed and stratification), the dispersal of oil depends mainly on the behavior of oil droplets which are fractionated into different sizes. These oil droplets can have orders of magnitude differences in ascent rates (e.g., 6 mm/s and 0.06 mm/s for 300 micron and 30 micron diameter particles, respectively) and change in diameter as they age. Emulsification, interaction with suspended particulate matter, dissolution and other processes can also affect droplet behavior. Our Lagrangian approach is ideally suited for simulating oil dispersal because differences in initial droplet characteristics and time-varying droplet behavior are readily incorporated. In this project, the coupled SABGOM/LTRANS model system will be run for the time period of the Deepwater Horizon oil spill, maps and animations of model output will be produce. The model results will be compared with available observations and will be made available to the oil spill response community. In the near-term, a series of LTRANS simulations will be run using the existing flow field from recent SABGOM model simulations. The Lagrangian dispersion runs will be initialized with a continuous source of particles representing the near-field plume above the well. Each run will simulate the far-field dispersion of those particles based on a specific set of assumptions about particle behavior. As more complete information on the size and composition of gas bubbles and oil droplets emerge, the most realistic particle distributions from the LTRANS ensemble of runs will be selected. As part of this effort, an improved hindcast from the SABGOM model for use with LTRANS will be prodiced and the model skill will be quantified against physical oceanographic observations. In addition, Eulerian and Lagrangian predictions of oil dispersal will be quantitatively compared with observations in order to use the strengths of both approaches to provide the most realistic predictions for the oil response community. Broader Impacts: Mid-term results will be open-source models and model results using existing and likely new, particle-tracking technology for the geosciences and oil-spill response communities. Incorporation of the model into the framework of the Community Surface Dynamics Modeling System (CSDMS) will ensure that the coding structures are suitable for coupling with other models and future distribution for research and educational purposes. In addition, the team members from the USGS will ensure that LTRANS can run with CF-compliant model output, making it functional with over seventeen coastal models, allowing simulations and forecasts to be made throughout the US coastal waters. In addition to providing timely information for oil spill responders, this project will lay the ground work for future efforts that investigate the interaction between oil and larval transport of commercially and ecologically important organisms in the Gulf of Mexico.