dr Øyvind breivik norwegian meteorological institute · 2005. 4. 5. · generously made available...
TRANSCRIPT
Norwegian Meteorological Institute
Forecasting Drifting Objects
Dr Øyvind BreivikNorwegian Meteorological Institute
Norwegian Meteorological Institute
Objective• To generate search areas for the Norwegian
Search and Rescue Service based on thebest available wind and current information
To paraphrase Einstein:• Make search areas as small as possible, but
not smaller
Challenge
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The Uncertainties Involved
• Where and when did the accident takeplace?
• Which object should we look for (life raft,person in water, …)?
• What are the wind conditions like in thearea?
• What are the surface currents in the area?
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Search Maths
POS = POD x POC
• POS: Probability of success (do we findwhat we are looking for?)
• POD: Probability of detection (the keeneyes of the rescuers)
• POC: Probability of containment (are wesearching in the right place?), our business
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Forces on a Drifting Object
• Wind (leeway)• Surface current• Wave motion (damping and excitation)
The motion of an object of arbitrary shape isextremely difficult to model, thusapproximations are needed
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Empirical leeway data• 63 classes of SAR objects have been
compiled by the U.S. Coast Guard throughextensive field campaigns and weregenerously made available to the project.
Aanderaa Current Meter
Survival Suit
6 foot mannequin ��������
GPS/ARGOS antennae
light
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ApproximationsApproximations
Wind speed and object drift is approximatelylinearly relatedDifferent objects drift differently
Life raft with drogue
Undrogued life raft
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Wind to Wind to
WindDirection
From
WindDirection
From
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Wind to
Lα = -25o Lα = +25o
RWD = -135o RWD = +135o
Leeway DriftDirection
Leeway DriftDirection
Leeway divergence
• Objects drift at anangle to the wind (theleeway divergenceangle)
• Symmetry allowsstable drift left andright of downwind.
• This leads to adiverging search areaas time progresses
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Forcing• Wind from 20 km res. atmospheric model (HIRLAM 20)• Surface currents from 4 km res. ocean model with tides and wind forcing (POM)• Archived winds and currents go 7 days back – forecasts up to +60 h
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Search areas and ensemble modelling
A search area is foundby computing anensemble oftrajectories withslight changes in
• drift properties• wind field• initial position &
time of incident
Individualtrajectory
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leewayleeway.met..met.nono
•• SearchSearch area area simulationssimulationsare orderedare ordered via via the the webweb
•• Results areResults are returnedreturned to to the theRescueRescue Co- Co-ordinationordinationCentresCentres and and presentedpresented as asaa layer on layer on an an electronicelectronicsea chartsea chart
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Bjarne – RCC test dummy
• Regular exercises • Daily tests
Norwegian Meteorological InstituteIcelandic exercise 2003
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Liferaft release positionLiferaft release position
Liferaft Liferaft pickup +16hpickup +16h
Ensemble search area (10nm x 10nm)
Manual Manual search search areasareas
Faroe exercise May 4th 2004
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•• RedoRedo older older leeway categories with new field methods leeway categories with new field methods•• Refine the taxonomyRefine the taxonomy for for different different parts parts of the of the world – in world – in
close collaboration with RCCsclose collaboration with RCCs
The flora of SAR objects
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Fedje – a potential testbed
••Three Three HF radarsHF radars•• currentscurrents•• wave measurementswave measurements
••Weather stationWeather station••8 km 8 km wave modelwave model••4 km 4 km ocean modelocean model••Drifters (IMR)Drifters (IMR)
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Conclusions & outlook• The model yields realistic search areas, but
further model evaluation is needed (morefield campaigns) to thoroughly assess itsforecasts capabilities for specific S&Robjects
• More leeway categories are needed to coverthe range of typical S&R objects found inNorwegian and European waters
• Error model for estimating uncertainties inwinds and currents should be improved