SOSim-V2：记录了新代码

# SOSim V2 ## Table of Contents 1. [Description](#description) 2. [Downloading](#downloading) 2. [Authors](#authors) 3. [License](#license) 4. [Acknowledgement](#acknowledgement) <a name="descripton"></a> ## Description SOSim is a 3-D publicly available Bayesian probability model that infers and predicts subsurface oil movement based on the limited field observations at one or more sampling dates. The scope of subsurface oil includes sunken oil that resides on the bay or river bottom, or on continental shelves, and oil submerged in ocean water columns. SOSim is intended to be used during spill emergency response, to output a map of the probability of finding subsurface oil and the associated uncertainty in that trajectory. These probabilities can be interpreted as relative oil concentrations. Due to the lack of information on the total oil released as a function of time, the model cannot assess absolute concentrations, but rather relative concentrations showing oil “hotspots” and areas where oil may not be collecting. Uncertainty bounds indicate the potential extent of significant oil patches, generally more disperse than the field observations due to accounting for uncertainty in the advective and dispersive forces acting on the subsurface oil. You can use SOSim to … · Locate and predict the possible locations of sunken oil on a bay bottom or continental shelf or river after an instantaneous or a continuous spill; · Locate and predict the possible locations of submerged oil in the water-column below the thermocline in 3-D after an instantaneous or a continuous spill; · Learn how the predicted trajectories and probability are affected by uncertainty; · Guide oil responders to make sampling plans during emergency response. <a name="downloading"></a> ## Downloading The purpose of this repository is solely a backup for the computational codes used in SOSim. To download and install SOSim V2, please go to: https://data.gulfresearchinitiative.org/data/R6.x812.000:0005 There, you can access the User Manual which will guide you in downloading and installing the model. In the User Manual, there are also descriptions for the functions of each code in the repository. <a name="authors"></a> ## Authors * [Mary Jacketti](https://github.com/maryjacketti) * [Chao Ji](https://github.com/jichaojoyce) <a name="license"></a> ## License Feel free to use it! <a name="acknowledgement"></a> ## Acknowledgements This research is part of the Inferential/parametric Forecasting of Subsurface Oil Trajectory Integrating Limited Reconnaissance Data with Flow Field Information for Emergency Response consortium project supported by Gulf of Mexico Research Initiative Year 18-20 Consortia grants (RFP-VI).