EGU21-6543
https://doi.org/10.5194/egusphere-egu21-6543
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Integrated analysis of remote sensing and numerical oil drift simulations for improved oil spill preparedness capabilities

Camilla Brekke1, Martine Espeseth1, Knut-Frode Dagestad2, Johannes Röhrs2, Lars Hole2, and Andreas Reigber3
Camilla Brekke et al.
  • 1UiT The Arctic University of Norway, Tromsø, Norway
  • 2The Norwegian Meteorological Institute, Oslo, Norway
  • 3DLR, Microwaves and Radar Institute, Oberpfaffenhofen-Weßling, Germany

Integrated analysis of remote sensing and numerical oil drift simulations for improved oil spill preparedness capabilities

Camilla Brekke1, Martine M. Espeseth1, Knut-Frode Dagestad2, Johannes Röhrs2, Lars Robert Hole2, and Andreas Reigber3

 

1UiT The Arctic University of Norway, Tromsø, Norway

2The Norwegian Meteorological Institute, Oslo, Norway

3DLR, Microwaves and Radar Institute, Oberpfaffenhofen-Weßling, Germany

 

We present results from a successfully conducted free-floating oil spill field experiment followed by an integrated analysis of remotely sensed data and drift simulations. The experiment took place in the North Sea in the summer of 2019 during Norwegian Clean Seas Association for Operating Companies’ annual oil-on-water exercise. Two types of oils were applied: a mineral oil emulsion and a soybean oil emulsion. The dataset collected contains a collection of close-in-time radar (aircraft and space-borne) and optical data (aircraft, aerostat, and drone) acquisitions of the slicks. We compare oil drift simulations, applying various configurations of wind, wave, and current information, with observed slick positions and shape. We describe trajectories and dynamics of the spills, slick extent, and their evolution, and the differences in detection capabilities in optical instruments versus multifrequency quad-polarimetric synthetic aperture radar (SAR) imagery acquired by DLRs large-scale airborne SAR facility (F-SAR). When using the best available forcing from in situ data and forecast models, good agreement with the observed position and extent are found in this study. The appearance in the optical images and the SAR time series from F-SAR were found to be different between the soybean and mineral oil types. Differences in mineral oil detection capabilities are found between SAR and optical imagery of thinner sheen regions. From a drifting perspective, the biological oil emulsions could replace the viscous similar mineral oil emulsion in future oil spill preparedness campaigns. However, from a remote sensing and wildlife perspective, the two oils have different properties. Depending on the practical application, further investigation on how the soybean oil impact the seabirds must be conducted in order to recommend the soybean oil as a viable substitute for mineral oil.

 

This study is published as open access in Journalof Geophysical Research: Oceans[1], and we encourage the audience to read this article for detailed acquaintance with the work.

 

Reference:

[1]Brekke, C., Espeseth, M. M., Dagestad, K.-F., Röhrs, J., Hole, L. R., & Reigber,A. (2021). Integrated analysis of multisensor datasets and oil driftsimulations—a free-floating oil experiment in the open ocean. Journalof Geophysical Research: Oceans, 126, e2020JC016499. https://doi.org/10.1029/2020JC016499

How to cite: Brekke, C., Espeseth, M., Dagestad, K.-F., Röhrs, J., Hole, L., and Reigber, A.: Integrated analysis of remote sensing and numerical oil drift simulations for improved oil spill preparedness capabilities, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6543, https://doi.org/10.5194/egusphere-egu21-6543, 2021.

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