Hurricanes and Disaster Resilience: Does Data Present New Solutions?
On August 24, 2019, a tropical wave in the Central Atlantic developed into an extremely powerful, long-lived cyclone, Hurricane Dorian. Hurricane Dorian caused catastrophic damage to the northwestern Bahamas and caused significant destruction in the southeastern United States, and later Atlantic Canada. The hurricane left an estimated 70,000 people homeless and caused billions of dollars in material destruction.
Many felt powerless facing the tenacity and ferocity of Hurricane Dorian. In an age where Amazon or Uber Eats can offer a near-instant gratification of a need, those in evacuation zones in the United States wondered how we still currently lack the technology to just make the hurricane “go away”. Axios news reported that even the President suggested “nuking hurricanes to stop them from hitting the US.”
It is true that we have a tremendous amount of technological innovation and information at our disposal that has yet to be integrated with larger decision making bodies. This discrepancy is especially apparent in regions that don’t have the financing, resources, and infrastructure to assimilate new technology and data into their disaster resilience and response structures. While we do not have established mechanisms for changing the course of hurricanes and other major natural disasters currently, we do have more data and information on these climate patterns than we have ever had before.
In the wake of Hurricane Dorian and the oncoming hurricane season, the team at Planet OS worked to obtain and provide access to the Météo France Global Ocean Wave Analysis and Forecast datasets on the Planet OS Datahub. The operational global ocean analysis and forecast system of Météo-France with a resolution of 1/12 degree provides daily analysis and five-day forecasts for the global ocean sea surface waves. It includes 3-hourly instantaneous fields of integrated wave parameters from the total spectrum (significant height, period, direction, Stokes drift, etc.), as well as the wind wave, primary and secondary swell wave partitions.
Applying the Data
Using those datasets, our Data Integration Engineer, Eneli Toodu, created a powerful visual of Hurricane Dorian as it moved through the Atlantic. Pictured below, the GIF utilizes the Météo France Global Ocean Wave Analysis and forecast datasets to show wave height within the Hurricane in meters. If you are interested in creating a visualization using these datasets like the one below, Eneli also created a tutorial through Github Notebook that can be found here.
As you may know, hurricanes are large, swirling storms consisting of high-speed winds (119 kilometers per hour or 74 mph +)that push walls of ocean water ashore once they have reached land. The visualization above shows Hurricane Dorian and its accompanying waves travel through the Bahamas, up to Florida, and then past South and North Carolina. The hurricane later moved along open water and brought high strength winds and rain to Halifax, Nova Scotia. By September 8th, Dorian was in the Gulf of Saint Lawrence, continuing on its northeastern path into the North Atlantic Ocean. Growing from a single wave off the coast in the Atlantic, Hurricane Dorian transformed into a massive, global storm.
Although Hurricane Dorian has just finished its nearly two-week period of destruction, more natural disasters loom over the horizon. While we are currently unable to stop upcoming storms in their tracks, we do have more advanced technology and data that monitors and predicts these weather events. With agencies such as NASA and the National Oceanic and Atmospheric Administration (NOAA) already leveraging big data technology to predict hurricane landfalls and coordinate emergency response personnel, data shows promise in reducing risk and damages from natural disasters.
Accessibility of Data during Disasters
In the face of dangerous weather and climate patterns, the dissemination and improved accessibility of climate and weather data are incredibly important. It can help agencies choose ideal disaster response staging locations, choose evacuation routes, pinpoint likely flooding areas to prepare accordingly, and more. Additionally, agencies throughout the storm impact area can use machine learning algorithms to dictate the trajectory of the storm and its potential damage. This information can make a substantial difference, and can improve the safety and resilience of communities worldwide.
At Planet OS, we provide streamlined access to high-quality weather, climate, and environmental data from the world’s leading providers. We also make it our mission to ensure that this invaluable information is easily accessible and usable for both individuals and larger organizations. Greater data accessibility can mean more informed decision making and ultimately, less risk and destruction in the midst of colossal climate phenomena.
Many of the datasets made available through the Planet OS Datahub have been at the request of our users. For those who require a consolidated, easy to use, resource for accessing large and complex material that the Datahub does not already offer, please reach out to the team and we will work toward bringing it onboard. For more information check out the Planet OS Datahub.
