This is part 2 of my article on Big Data.
Let us dive a little deeper and analyse how predictive analysis is being used in tracking weather phenomena.
Hurricane Sandy (unofficially known as “Superstorm Sandy”) was the deadliest and most destructive hurricane of the 2012 Atlantic hurricane season, and the second-costliest hurricane in United States history. Sandy was a Category 3 storm at its peak intensity when it made landfall in Cuba. It was a Category 2 storm off the coast of the Northeastern United States, the storm became the largest Atlantic hurricane on record (as measured by diameter, with winds spanning 1,800 km.
This is the barometric reading of the pressure of air at different times as the storm approached.As you can observe the storm keeps decelerating as it approaches landfall.The landfall at two different at different locations are shown.As soon as landfall, it picks up pace and simultaneously the pressure keeps increasing rising rapidly.
This can be beautifully captured using predictive analysis. As you can see , the blue color parabola can be captured easily using a machine learning algorithm based on different parameters associated with the wind velocity and weather conditions.As the parabola reaches the local minimum we could estimate the place and time of landfall.
This gives us an opportunity to study the patterns of wind and the factors determining the effect of damage caused by a natural phenomena like a tsunami or a sandstorm.All air pressure and wind related phenomenon can be better understood by such detailed trend analysis.
The trend analysis below shows the violent wind activity and gusts that peak at landfall and devastate the surroundings with their force and overwhelming power.
Look at the gust pick up and spike at around 12 AM CDT.If you had noticed the earlier figure, this is when the landfall occurs and wind starts accelerating again.The intuition is that as the landfall occurs, the velocity gets multiplied several times since air pressure increases and this pressure results in a spiraling effect that causes violent storm activity.
By visualizing such phenomena, predictive analysis provides a means to ensure evacuation and safety precautions. A foresight into the kind of national emergency that can be averted in such devastating times.This is not just a scientific study it is much more comprehensive and covers human, financial, administrative and security aspects of an thriving economy.In conclusion, predictive analysis not only wins you elections, it goes way beyond and contributes to the process of social harmony and well being.
In love with Big Data?!, dial in back next week for the concluding part of Big Data series.A new science is born!!