Numerical model of floating oil on seawater, in situ thermal structure, thickness, and remote sensing

Abstract

Thermal infrared (TIR) remote sensing provides oil slick remote sensing for oil spill response. Herein, we derive oil thickness, h, from thermal contrast, ΔT, using a numerical, three-media heat-transfer model that solved the convection–diffusion equation, verified against laboratory measurements of high spatial-resolution thermal profiles for a heavy Texas Raw Crude and a light Colorado Crude, τ = 2.0 and 0.25 mm, respectively. τ is the oil attenuation length and ΔT is the temperature difference between the oil slick and adjacent oil-free water.The model studied processes and factors underlying ΔT, that arise from differing insolation absorption and the resultant heat flows and radiative emissions. The model found that the thermal profile decreased linearly through optically thin oil with and without illumination and through thick oil without illumination. For illuminated, optically-thick, oil under illumination, an internal temperature peak (greater than the air and water temperature) develops in the oil. Insolation absorption was confirmed to drive this temperature peak and thus depends on the oil τ. The model reproduced an expected asymptotic relationship of ΔT to h in the thick h limit and scales with τ. Sensitivity studies found ΔT linearly sensitive to insolation. In contrast, the air–water temperature gradient is insensitive to h for large τ and is strongly and non-linearly dependent on h for small τ,This sensitivity underlies the critical role of τ in TIR oil slick remote sensing.The model provides an investigative oil spill tool that extends existing measurements to different ambient conditions, scene illumination, and crude oils.