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BRUCE HACKETT ET AL.
and forecast model data. Particle information is output to a history file
at hourly intervals for analysis and graphical rendering.
The particle based model described here is very similar to the probabalistic approach used in the SAR model described above. In both
cases, a cloud of particles is spread and advected by geophysical forces.
Aside from some differences in the seeding strategy, the real difference
lies in the peculiarities of the particles and how we interpret the results;
floating object particles are robust but have very special drift characteristics, while oil particles are fairly simple drifters but with complicated
lifelines. The particle approach can be (and is) utilized in models of
other things in the ocean, such as fish eggs and larvae.
4.
Operational services
We have seen that, despite the fact that life rafts, tankers and oil are
quite different things in the ocean, the models that are used to predict
their drift have much in common. Primarily, they share a reliance on
the same kinds of geophysical forcing data. When these models are to be
implemented in an emergency service for real-time response to incidents,
immediate access to prognostic forcing data is essential. The need is
especially acute for SAR services, where minutes saved can mean lives
saved. Consequently, forecast services for SAR, ship and oil drift are
closely allied to operational centers for weather and ocean forecasting.
Forcing data not only need to be available quickly, but also in the form
of products suitable for the drift models. This requires preparation and
testing of the full data production chain. The various drift models also
share a need for efficient interfacing with the users - the crisis response
teams in the field. Attaining optimal performance of the services is
dependent on end-to-end testing and validation of the systems through
regular exercises.
In order to facilitate rapid and reliable national response services
for emergency drift episodes, Norway has implemented drift models for
SAR, ship and oil drift at met.no. These models are directly interfaced to the operational forecast models for the atmosphere, ocean and
waves. Many countries have similar arrangements. The responsibility
for action in an emergency lies with the Joint Rescue Coordination Centres of Norway (JRCC) for SAR and ship drift, and with the Norwegian
Coastal Authority for oil spills; they will request drift forecasts based
on information at hand. A cardinal rule for these services is that a forecast should always be returned to the requesting party, even if the best
available data basis is uncertain. Thus, backup alternatives to opera-
BRUCE HACKETT ET AL.
and forecast model data. Particle information is output to a history file
at hourly intervals for analysis and graphical rendering.
The particle based model described here is very similar to the probabalistic approach used in the SAR model described above. In both
cases, a cloud of particles is spread and advected by geophysical forces.
Aside from some differences in the seeding strategy, the real difference
lies in the peculiarities of the particles and how we interpret the results;
floating object particles are robust but have very special drift characteristics, while oil particles are fairly simple drifters but with complicated
lifelines. The particle approach can be (and is) utilized in models of
other things in the ocean, such as fish eggs and larvae.
4.
Operational services
We have seen that, despite the fact that life rafts, tankers and oil are
quite different things in the ocean, the models that are used to predict
their drift have much in common. Primarily, they share a reliance on
the same kinds of geophysical forcing data. When these models are to be
implemented in an emergency service for real-time response to incidents,
immediate access to prognostic forcing data is essential. The need is
especially acute for SAR services, where minutes saved can mean lives
saved. Consequently, forecast services for SAR, ship and oil drift are
closely allied to operational centers for weather and ocean forecasting.
Forcing data not only need to be available quickly, but also in the form
of products suitable for the drift models. This requires preparation and
testing of the full data production chain. The various drift models also
share a need for efficient interfacing with the users - the crisis response
teams in the field. Attaining optimal performance of the services is
dependent on end-to-end testing and validation of the systems through
regular exercises.
In order to facilitate rapid and reliable national response services
for emergency drift episodes, Norway has implemented drift models for
SAR, ship and oil drift at met.no. These models are directly interfaced to the operational forecast models for the atmosphere, ocean and
waves. Many countries have similar arrangements. The responsibility
for action in an emergency lies with the Joint Rescue Coordination Centres of Norway (JRCC) for SAR and ship drift, and with the Norwegian
Coastal Authority for oil spills; they will request drift forecasts based
on information at hand. A cardinal rule for these services is that a forecast should always be returned to the requesting party, even if the best
available data basis is uncertain. Thus, backup alternatives to opera-