Korean tanker No 3 oil spill incident simulation Wind drift model with 112 SW Japan Sea OCM correcti

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Korean tanker No 3 oil spill incident
simulationWind drift model with 1/12 SW Japan
Sea OCM correction empirical surface wind drift
(?0.06, ?0), Delvigne Sweeney particles size
distribution, dmax/dmin25/250 ?m
Click on the buttons below to start animations
Particles
Concentration
Tidal current
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Routine oil spill simulation and prediction
system parameters

• Meteorological analysis and forecasts data are
  received once a day. Total 3.7 Mb are received,
  and at 1800 UTC (local night) it usually takes
  approximately 7 - 8 minutes
• SW OCM is started and run the currents simulation
  and prediction for 126 h (5 days). With 10s time
  step it takes 1 h 03 min on 667 MHz Alpha
  processor (GFDL MOM 1/12 - 25 min)
• Oil spill simulation could be run by operator and
  for 5 days with 10000 droplets it will takeless
  then 14 min

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Conclusion
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• Oil spill numerical simulation system could
  provide important information for long term
  environmental protection planning as well as for
  the short term (at least up to 4-5 days) planning
  of accidental oil spill recovery operations

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Conclusion
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• As follows from large number of spill simulation
  experiments, the ocean currents simulation
  subsystem is an important part of the oil spill
  analysis and prediction system, especially for
  the Sea of Japan. Single wind drift model cannot
  reproduce the observed wide oil spreading along
  the Japanese coast.

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Conclusion
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• To respond the incidental oil spill and to
  predict its fate, the meteorological subsystem
  and the Ocean Circulation Model as parts of the
  oil spill simulation system have to be operated
  routinely

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Conclusion
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• Oil spill remote monitoring system providing the
  corrections for the spill simulation model will
  strongly improve the forecasts of spill spreading

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Conclusion
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• Results of simulations depend from large number
  of model parameters and from initial oil spill
  characteristics (e.g. spill position, intensity,
  spilled oil properties). These parameters are
  often unknown or are known approximately

The parallel computation of different spill
scenarios and the probability analysis of the oil
spill simulation results are desirable
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Conclusion
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• Any oil spill simulation and prediction system
  will produce the best forecast ifno oil spills
  will happen

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