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07 Sep 16 11:50

Hermine is a name unlikely to be retired from the National Hurricane Center's (NHC) list of hurricane names. It won't be discussed in the same vein as Sandy, Ike, Andrew, Katrina or Wilma. Sure, in its early life, it was perhaps the most tracked invest (an area designated by the NHC as having the potential to develop into a tropical cyclone) on Twitter, with the hashtag #99L trending for days. But it didn't develop as early as expected, and never became a major hurricane. Sure, the storm made landfall as a category 1 in Florida, ending the state's nearly 11 year hurricane drought, which was unprecedented in the records. But it hit a sparsely populated area.  Sure, it came off the North Carolina coast and transitioned into a powerful extratropical storm, pummeling the Mid-Atlantic and Northeast for days with high surf, gusty winds and beach erosion. But it proved to be no worse than a nasty nor'easter.

However, Hermine will be a storm studied, analyzed and debated by the weather community for years to come. It has sparked an intense debate about how to communicate risk and uncertainty, and how to forecast for an event that simply has no similar event in history. How do you strike the balance between preparing people for the worst, relating uncertainty, and hoping for the best? 

Social media has made striking such a delicate balance even more challenging. Many armchair meteorologists share a single result from a single forecast model (even very reliable ones) with little in the way of context or explanation; these results are traditionally the worst case scenario among all the forecast models. Also, it is always entirely possible that the worst case scenario is what eventually plays out. You can't rule it out, but how much weight do you give to it?

During Hermine's lifecycle, many possibilities were on the table: A hurricane hitting Miami-Dade County, where the population has increased by 350,000 people since Wilma in 2005, a major hurricane with a dead on strike to New Orleans, where memories of Katrina remain fresh after 11 years, and a hybrid storm brushing the coast of New Jersey and lingering for days, driving surge into places where people are still recovering from
Sandy. Adding to the complicated forecast was the timing: Labor Day Weekend, a critical economic holiday for many seasonal businesses. 
 
The possibilities could not be ignored or go unmentioned; the scenarios outlined above had the potential to affect millions of people and cause billions of dollars in damage. At the same time, weather models aren't crystal balls, and despite the worst-case scenario going viral on Twitter, there wasn't a terrible amount of consistency from one model simulation to the next, from weather model to weather model. 

Therefore, hurricane, tropical storm and storm surge warnings were raised for potentially affected areas, with the NHC highlighting in discussion after discussion how uncertain the forecast was, particularly for the Northeast US. A shift of 50 or 75 miles would be the difference between record-breaking storm surge and nuisance flooding. 

But, despite the disappointment in what some perceive as a busted forecast, it is better to be overprepared than underprepared. September is Disaster Preparedness Month (https://www.ready.gov/september), and Hermine serves as an important reminder than we always must have a plan in place and be ready to protect lives and property.


Category: Climate/natural disasters: Disaster risk, Floods/storms

Location: Florida, United States


1 Comment

Urs Leimbacher - 7 Sep 2016, 5:45 p.m.

Thanks for sharing your thoughts, Megan. Close calls like Hermine's certainly remind us that its all about when, not if! Even a very rare event can happen tomorrow! As taxpayers, we expect from our governments to look ahead, systematically analyse large risks that may affect their communities and economies, and prepare accordingly. That's tax money well invested. Hermine hopefully has woken up those public sector representatives in Florida who may have started to slumber away during the long interval that you describe...


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