170 likes | 178 Views
Forecasting Drifting Objects. Dr Øyvind Breivik Norwegian Meteorological Institute. Objective. To generate search areas for the Norwegian Search and Rescue Service based on the best available wind and current information. Challenge. To paraphrase Einstein:
E N D
Forecasting Drifting Objects Dr Øyvind Breivik Norwegian Meteorological Institute Norwegian Meteorological Institute
Objective • To generate search areas for the Norwegian Search and Rescue Service based on the best available wind and current information Challenge • To paraphrase Einstein: • Make search areas as small as possible, but not smaller Norwegian Meteorological Institute
The Uncertainties Involved • Where and when did the accident take place? • Which object should we look for (life raft, person in water, …)? • What are the wind conditions like in the area? • What are the surface currents in the area? Norwegian Meteorological Institute
Search Maths POS = POD x POC • POS: Probability of success (do we find what we are looking for?) • POD: Probability of detection (the keen eyes of the rescuers) • POC: Probability of containment (are we searching in the right place?), our business Norwegian Meteorological Institute
Forces on a Drifting Object • Wind (leeway) • Surface current • Wave motion (damping and excitation) The motion of an object of arbitrary shape is extremely difficult to model, thus approximations are needed Norwegian Meteorological Institute
Empirical leeway data • 63 classes of SAR objects have been compiled by the U.S. Coast Guard through extensive field campaigns and were generously made available to the project. Norwegian Meteorological Institute
Approximations Approximations Wind speed and object drift is approximately linearly related Different objects drift differently Undrogued life raft Life raft with drogue Norwegian Meteorological Institute
Leeway divergence • Objects drift at an angle to the wind (the leeway divergence angle) • Symmetry allows stable drift left and right of downwind. • This leads to a diverging search area as time progresses Norwegian Meteorological Institute
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 Norwegian Meteorological Institute
Search areas and ensemble modelling A search area is found by computing an ensemble of trajectories with slight changes in • drift properties • wind field • initial position & time of incident Individual trajectory Norwegian Meteorological Institute
leeway.met.no • Search area simulations are ordered via the web • Results are returned to the Rescue Co-ordination Centres and presented as a layer on an electronic sea chart Norwegian Meteorological Institute
Bjarne – RCC test dummy • Regular exercises • Daily tests Norwegian Meteorological Institute
Icelandic exercise 2003 Norwegian Meteorological Institute
Faroe exercise May 4th 2004 Liferaft release position Manual search areas Ensemble search area (10nm x 10nm) Liferaft pickup +16h Norwegian Meteorological Institute
The flora of SAR objects • Redo older leeway categories with new field methods • Refine the taxonomy for different parts of the world – in close collaboration with RCCs Norwegian Meteorological Institute
Fedje – a potential testbed • Three HF radars • currents • wave measurements • Weather station • 8 km wave model • 4 km ocean model • Drifters (IMR) Norwegian Meteorological Institute
Conclusions & outlook • The model yields realistic search areas, but further model evaluation is needed (more field campaigns) to thoroughly assess its forecasts capabilities for specific S&R objects • More leeway categories are needed to cover the range of typical S&R objects found in Norwegian and European waters • Error model for estimating uncertainties in winds and currents should be improved Norwegian Meteorological Institute