. Tracking Uncertainty in Search and Rescue Planning Art Allen U.S. Coast Guard Office of Search and Rescue

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Presentation transcript:

. Tracking Uncertainty in Search and Rescue Planning Art Allen U.S. Coast Guard Office of Search and Rescue

. The basic steps for SAR Planning 1.Initial Conditions 2.Drift Predictions 3.Resource Allocation 4.Actual search effectiveness 5.Updating search conditions

. Build a SAR Case Build a SAR Case Assemble Search Plan Assemble Search Plan Databases Environmental Now & Forecasts Environmental Now & Forecasts Disseminate Search Plan Disseminate Search Plan Capture Search Results Capture Search Results Rescue or Suspend Search Results Search Plans Results Field

. Initial Conditions Uncertainties 1.Scenarios Subjective relative weights between scenarios (e.g. 80%A or 20%B) Each scenarios will have its own set of initial conditions

. Initial Conditions Uncertainties 1.Where did the incident occur? 2.When did the incident occur? 3.What are we looking for? 4.How long will they survive?

. Capture Initial Case Data (Input and weight Scenarios) Capture Initial Case Data (Input and weight Scenarios) Databases Store Case Info. Initial POC Initial POSv Initial States User inputs Background Search object info.

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. Build a SAR Case Build a SAR Case Assemble Search Plan Assemble Search Plan Databases Environmental Now & Forecasts Environmental Now & Forecasts Disseminate Search Plan Disseminate Search Plan Capture Search Results Capture Search Results Rescue or Suspend Search Results Search Plans Results Field

(2) Assemble Search Plan A) Compute Probability Density Distributions Now and Forecast Winds, Currents, Waves, SST & Air T, Visibility, etc. Now and Forecast Winds, Currents, Waves, SST & Air T, Visibility, etc. Databases (Case, SRU’s) Drifted POC Updated POSv Initial POC Initial POSv Search Results Drift/ Survival/State of Replications (Leeway / Drift Model) (Survival Model) (Detection Model) Drift/ Survival/State of Replications (Leeway / Drift Model) (Survival Model) (Detection Model) Initial States Updated States

. Probability Distributions 1.Drift uncertainties 2.Survival uncertainties 3.Detection uncertainties

. Drift Uncertainties 1.Surface current errors & dispersion (u’,v’) 2. Target uncertainty What are we looking for? 3.Leeway uncertainty 4.Wind and Waves

. Surface Currents Self-Locating Datum Marker Buoys SLDMBs – Air-deployable 7/10 th CODE drifter, GPS positions & SST via Argos 1.Sources: Historical ship-drift global data sets Global, regional & coastal models Direct on-scene measurements 2.Dispersion Random walk – 0 th order Markov model Random flight – 1 st order Markov model

. SLDMBs Self-Locating Datum Marker Buoys Air- deployable 7/10 th CODE drifter, GPS positions & SST via Argos

. Surface currents from CODAR

. CODAR / SLDMBs Black: Actual SLDMB Trajectory Red: Trajectory Predicted From NOAA Tidal station Blue: Trajectory Predicted From CODAR Data

. CODAR / SLDMBs Black: Actual SLDMB Trajectory Blue: Trajectory Predicted From CODAR Data Red: Trajectory Predicted From STPS predictions

. Leeway classes 1.Statistical analysis of field experiments: Indirect and Direct methods US, Canadian, Japanese & Korean 2. Leeway taxonomy by Allen and Plourde (1999) combined results into 63 categories.

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Approximations Wind speed and object drift is approximately linearly related Different objects drift differently Life raft with drogue Undrogued life raft

Objects do not drift exactly downwind!

Constrained or Unconstrained Linear Equations Used in Monte Carlo Simulations

. Winds and Waves 1.Global, regional & coastal models 2.Direct on-scene measurements Both wind and waves act through leeway

. Probability Distributions 1.Drift uncertainties 2.Survival uncertainties 3.Detection uncertainties

. Survival Modeling 1.UK Immersion statistics 2. CESM Hypothermia model Mathematical model Physiological data

. Survival Uncertainties 1.CESM / UK statistics limited to cold water survival 2.Warm water survival factors: 1.Still hypothermic (loss of heat) 2.Dehydration (lost of water) 3.Sleeplessness (lost of sleep / restoration) 4.Fatigue (loss of available energy) 5.Circadian rhythms (cycles in all above) 6.Predation (loss of blood)

. Probability Distributions 1.Drift uncertainties 2.Survival uncertainties 3.Detection uncertainties

. Detection Uncertainties Lateral range curves & sweep widths based upon limited field tests and MSPP Limited environmental conditions Limited Target sets Limited SRU / sensor combinations

. Build a SAR Case Build a SAR Case Assemble Search Plan Assemble Search Plan Databases Environmental Now & Forecasts Environmental Now & Forecasts Disseminate Search Plan Disseminate Search Plan Capture Search Results Capture Search Results Rescue or Suspend Search Results Search Plans Results Field

(2) Assemble Search Plan B) Capture Resources Capture SRU Availability (Position, Status Capabilities, Limitations) Capture SRU Availability (Position, Status Capabilities, Limitations) Databases Background SRU info. Users inputs Winds,Waves, SST & Air T, Visibility, etc. Winds,Waves, SST & Air T, Visibility, etc. SRU Risks SRUs called

(2) Assemble Search Plan C) Allocate Resources Drifted POC Updated POSv 1)Suggest Optimal Survivor Search Plan 2) Modify Plan to suit 3) Capture Plan to execute 1)Suggest Optimal Survivor Search Plan 2) Modify Plan to suit 3) Capture Plan to execute Updated States SRUs called Forecasted Winds,Waves, SST, Air T, & Sensor Environmentals Forecasted Winds,Waves, SST, Air T, & Sensor Environmentals Databases Search PLANS

(3) Disseminate Search Plans Support various output methods to disseminate search plans. Support various output methods to disseminate search plans. Search PLANS To Shore To Vessels To Aircraft

(4) Capture Search Results Capture description of completed searches including both positive and negative results. USCG Vessels USCG Aircraft Other searchers Rescue or Suspend Search Results Nowcasted/Observed Winds,Waves, SST, Air T, & Sensor Environmentals Nowcasted/Observed Winds,Waves, SST, Air T, & Sensor Environmentals Databases