Putting Monte Carlo Software in Reverse

Question for today: What do you get when you run Monte Carlo software back in time? 
Answer: You get closer and closer to the wreckage of Air France Light 447.
The U.S. Coast Guard’s search for the crash site of the doomed Air France plane was the first major test of its "reverse-drift" modeling  program SAROPS (Search and Rescue Optimal Planning System).  Earlier this year I reported on one of its first reality tests, the search for two football players whose boat capsized in the Gulf of Mexico, which apparently took place before the software was formally adopted by the Coast Guard.  For this search, a Coast Guard team in Portsmouth, Virginia, managed the modeling in close cooperation with French and Braziian rescue teams.
At last report, the reverse risk analysis was performing admirably.  Starting with the location of the first object sighted in the water, in this case a seat cushion and some smaller debris, team using SAROPS established the location and the immediate wind and current conditions  and then used the history of weather and water since the plane disappeared to estimate thousands of possible paths the seat cushion could have traveled to reach its location.  When the next piece of debris surfaced, its data were fed into the program, and the Monte Carlo software spun out a slightly narrower range of retrospectively possible routes.  
Although the reconstruction of the crash location sounds laborious, the simulations are extremely fast.  The software can spin out ten thousand possible routes in fifteen minutes, and as the possible routes of a number of objects begin to converge, they focus with increased probability on the crash site.

 A picture–always worth a thousand words–of this clustering of simulated pathways can be found on the Virginian-Pilot website.  If you take a clook at that online graphic, you can see how, in the case of SAROPs, hindsight gets close to twenty-twenty . 

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