Four ensembles of TAMOC integral oil-gas plume simulations for comparison of uncertainty quantification techniques

Model data used for a comparison of uncertainty quantification techniques, including polynomial chaos and gaussian process regression. This data set consists of oil plume ensemble simulations generated using Texas A&M oil calculator (TAMOC, version 0.1.5, https://github.com/socolofs). We quantify the uncertainty of the model outputs caused by the uncertainty of 5 model inputs parameters in this experiment, including entrainment coefficient, entrainment ratio, gas to oil ratio, 95 percentile of droplet size (d95) and droplet size distribution spreading ratio. We only select the plume trap height and peel height as our model outputs. This dataset supports the following publication: Iskandarani, M., Wang, S., Srinivasan, A., Carlisle Thacker, W., Winokur, J., & Knio, O. M. (2016). An overview of uncertainty quantification techniques with application to oceanic and oil-spill simulations. Journal of Geophysical Research: Oceans, 121(4), 2789–2808. doi:10.1002/2015jc011366