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SmartData Collective > Big Data > Data Mining > Big Data For Big Weather
AnalyticsData MiningData VisualizationDecision ManagementPredictive AnalyticsRisk Management

Big Data For Big Weather

LatticeEngines
Last updated: 2012/11/01 at 6:55 PM
LatticeEngines
4 Min Read
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Courtesy of hint.fm/wind

Courtesy of hint.fm/wind

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Weather data

Big Data Brings Stunningly Accurate Weather Predictions To Windows

Big Data Can Help Predict Weather Patterns

The east coast is slowly recovering from the devastating impact of hurricane Sandy and we all here at Lattice wish our clients, prospects, friends, families and colleagues a healthy and speedy recovery.  Sandy certainly showed that there is nothing more powerful than Mother Nature and despite our best efforts, big weather can have horrible consequences.

However, one positive thing to take away from Sandy is that our resources, be it state, federal or local authorities were well informed and well prepared.  Precautions were taken up and down the east coast to minimize or at least manage safety concerns as much as possible.  And many of the predictions and precautions used by authorities were assisted by big data.

Weather professionals across the US were letting people know of the potential of a significant storm and where the eventual landfall would occur and all of this was getting more detailed and more accurate as more data points were available.  Back on Tuesday 10/23, the folks at Weather Underground showed the various paths that the young tropical storm Sandy could have taken.  While the majority of models suggested that Sandy would move out to the Atlantic, enough of them suggested a more direct impact to warrant preparations along the US coast.

Courtesy of Weather Underground

As people and authorities began planning for coastal flooding and all the consequences associated with a major storm, power companies and utilities up and down the coast had to start planning for massive projected outages.  Local utilities needed to understand where the likely points of need would be and make appropriate staffing decisions to help the most likely impacted areas first.  The image below is from the John Hopkins University showing how many projected people would be without power by analyzing data from outages on 11 previous hurricanes and modeling wind speed, wind gusts and population density.

Courtesy of John Hopkins University

And finally, as the storm was hitting hardest, Google, perhaps the original Big Data company, was quick to supply helpful mapping capabilities with its Superstorm Sandy utility.  Google was able to overlay power outage information along with weather details as well as map out exactly the locations of shelters, traffic conditions and other helpful information.  The helpful map made it easy for people without power to check their smart phones for continued updates on the storm and instructions on where to go and what to do.

Courtesy of Google Crisis Map

And so while Big Data can’t yet alter or stop a catastrophic storm like Sandy, it can certainly provide the capability to perform some key advance planning to lessen the devastating impacts of a storm as well as give key real-time capabilities to those caught up in the havoc.

 



TAGGED: storms, weather
LatticeEngines November 1, 2012
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