Improved prediction of oil drift pattern using ensemble of ocean currents

ABSTRACT

Indian Coast Guard and oil spill responders utilise the operational oil spill advisory services of the Indian National Centre for Ocean Information Services (INCOIS) during the event of oil spills for setting up spill response operations. Oil drifts in marine zones are dominated by ocean currents. Ocean currents generated by numerical models have errors and uncertainties due to model approximations, inaccurate initial and boundary conditions in the model setup. An attempt was made to generate an oil spill advisory using a weighted ensemble of ocean currents. In this study, the oil spill trajectory model, General National Oceanic and Atmospheric Administration (NOAA) Operational Modeling Environment (GNOME) was forced using a weighted ensemble of ocean currents for the Heavy Furnace Oil (HFO) spill reported off Ennore port during 0400 hours (IST) of 28 January 2017. The inverse-variance weighting method was used to estimate weights by comparing zonal and meridional components of individual model ocean currents, with that of High Frequency (HF) Radar currents. The zone of HFO spread obtained while using an ensemble of ocean currents was compared with oil slick signatures obtained from Synthetic Aperture Radar (SAR) data on 0600 hours (IST) of 29 January 2017. It was noted that the trajectory patterns obtained from the weighted ensemble of ocean currents were well within the observed zone of oil slicks, compared to that of individual model ocean currents.

Acknowledgements

The authors express their sincere gratitude to Director, INCOIS for extending the support in carrying out this study. We thank the National Institute of Ocean Technology, Ministry of Earth Sciences, Government of India, for providing funds for the establishment and maintenance of the Indian Coastal Ocean Radar Network (HF Radar network) along the Indian coast. We also thank the data management team of INCOIS for providing the HF Radar data. The authors acknowledge that the executable oil spill model GNOME is adopted from NOAA and set in a diagnostic mode for simulating oil spill trajectories of the Indian Ocean. Thanks are due to the developers of NOAA GNOME. Dr. Francis and Dr. Hasibur Rahaman are thanked for providing the modelled ocean currents of ROMS and GM4p1 respectively. The authors also thank the NOAA HYCOM consortium from which HYCOM currents are utilised. The authors thank the officials of the Indian Coast Guard, Chennai, for their information on the oil spill and support in validating the trajectory predictions of spilled HFO. The reviewer’s comments and suggestions have significantly improved the quality of this paper. The authors are grateful for this. ArcMap tool was used to plot and generate the trajectory output in native format. Origin pro was used to perform the statistical analysis.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Notes on contributors

Prasad S.J

Dr.Prasad Seliamedu Jayaramachandran has been working as a scientist on Oil spill Trajectory Forecast at Indian National Centre for Ocean Information Services (INCOIS) located in Hyderabad, India. He established an operational online oil spill advisory (OOSA) system for the first time in India that has been used nationwide. He advised Indian Coast Guard, offshore industries, and oil spill responders on 25 oil spill events including the real, hypothetical, marine mocks and during pollution response exercises. He also advised the neighboring countries such as Srilanka, Mauritius, and Maldives on oil spill drift patterns. He earned his bachelor’s degree in chemical engineering from Periyar University, India. Prasad obtained his post-graduation in Environmental Management from Anna University, Chennai, India. He was awarded the Doctorate in the Faculty of Environmental Sciences and Technology at Jawaharlal Nehru Technological University, Hyderabad. He was previously employed in Environmental consultancies carrying out Environmental Impact Assessment studies. He taught several sessions on oil spill modeling and enlightened researchers, students, officials of the Indian Coast guard, Ports, and oil spill responders and trained them too under International Training Centre for Operational Oceanography (ITCOocean). His research includes the sensitivity analysis of the Met-ocean forcings in the oil drift, Satellite-based Oil Spill Surveillance (SOSS), and Synthetic Aperture Radar data analysis.

Balakrishnan Nair T.M

Dr. Balakrishnan Nair Thayannur Mullachery is a Senior Scientist and Group Head at the Indian National Centre for Ocean Information Services (INCOIS), Ministry of Earth Sciences, Government of India. He did a Ph.D. degree in Marine Science and his research interests include Wave modeling, Operational Oceanography, Ocean Services and Real-time Ocean observation systems. He published more than 75 papers in international and national SCI journals of high impact factor, in addition to many technical reports and popular articles. He is the Fellow of the Telangana Academy of Sciences (FTASc). He is a reviewer for many national and international journals. He is also a recognized research guide in many Indian universities and guided students for attaining their Ph.D. degrees. He has been instrumental in establishing real-time operational ocean observing systems and developing an ocean forecast system for India and some of the Indian Ocean rim countries. He is a recipient of the prestigious NATIONAL GEOSCIENCE AWARD (NGA) 2014, which was conferred by the Honorable President of India his Excellency Shri. Pranab Mukherjee in 2016.

Balaji B

Balaji Baduru is working in the Ocean Modeling and Data Assimilation Group at the Indian National Centre for Ocean Information Services (INCOIS), a leading organization in the field of ocean state forecast, ocean observation, information, and advisory services under the Ministry of Earth Sciences (MoES), Government of India. He is a graduate of Electronics and Communications Engineering from Sri Venkateswara University College of Engineering. He obtained his post-graduation from the Department of Electrical Engineering, Indian Institute of Technology Madras. Presently he is pursuing a Ph.D. from Mangalore University on ‘“Assimilation of in-situ and remote sensing data in Regional Ocean Modeling System for the Indian Ocean”. He was involved in developing RAIN (Regional Analysis of Indian OceaN) which is a data assimilation system, wherein ROMS (Regional Ocean Modeling System) is used as a forecast model and Local Ensemble Transform Kalman Filter (LETKF) as an assimilation scheme. His research interests include Ocean Modelling, Data Assimilation, and Machine learning techniques in the field of ocean and atmospheric sciences.