In our last storm surge post, we talked about the need for a storm surge graphic and why we use “above ground level” to communicate storm surge forecasts. Now we’ll discuss how we create the new storm surge graphic.
But first, we need to touch on how forecast uncertainty relates to storm surge forecasting.
Putting All Your Eggs in One Basket
The exact amount of storm surge that any one particular location will get from a storm is dependent on a number of factors, including storm track, storm intensity, storm size, forward speed, shape of the coastline, and depth of the ocean bottom just offshore. Needless to say, it’s a complex phenomenon. Although we’re getting better on some aspects of hurricane forecasting, we still aren’t able to nail down the exact landfall of the storm or exactly how strong and big the storm will be when it reaches the coast. This means that there is a lot of uncertainty involved in storm surge forecasting. Here’s an illustration showing why all of this is important.
Here’s the forecast track for a Category 4 hurricane located southeast of Louisiana and only about 12 hours away from reaching the northern Gulf Coast:
Here’s the question: how much storm surge could this hurricane produce in Mobile, Alabama, and Pensacola, Florida (marked on the map)? If we take this forecast and run it through SLOSH (the National Weather Service’s operational storm surge model), here’s what you get:
The forecast has this hurricane making landfall near Dauphin Island, with the center moving northward just west of Mobile Bay along the black line. You can see from this map that water levels will rise to at least 14 ft. above NGVD29 (the particular reference level we are using in this scenario) in the upper reaches of Mobile Bay while they will rise to about 2 ft. above NGVD29 in the Pensacola area. What’s the problem with this storm surge forecast? It assumes that the track, intensity, and size forecasts of the hurricane will all be perfect. This is rarely, if ever, the case.
Here’s what actually happened with this hurricane. The storm turned ever so slightly toward the east and made landfall about 30 miles east of where the earlier forecast had shown it moving inland. Despite the shift, this was a good track forecast–30 miles is more or less typical for a 12-hour error. So, what kind of storm surge resulted from the actual track of this hurricane? If we take the actual track of the storm and run it through SLOSH, here’s what we get:
Since the center of the hurricane actually moved east of Mobile Bay, winds were pushing water out of the bay, and the water was only able to rise about 4-5 ft. above NGVD29 near Mobile. On the other hand, significantly more water was pushed toward the Pensacola area, with values as high as 12 ft. above NGVD29 in the upper reaches of Pensacola Bay.
This scenario was an actual storm–Hurricane Ivan in 2004. If emergency managers in Pensacola at the time had relied on that single SLOSH map that was based on a perfect forecast (or, put all their eggs in one basket), they would have been woefully unprepared and may not have evacuated enough people away from the coast. Granted, such decisions would have been made more than 12 hours away from landfall, but at that time, forecast errors are even larger and make storm surge forecasting even more difficult.
If you’re going to put all your eggs in one basket, you might as well scramble them beforehand so that they don’t break when you drop the basket. In a sense, that’s what we do when trying to assess an area’s storm surge risk before a tropical cyclone. Instead of assuming one perfect forecast, we generate many simulated storms weighted around the official forecast–some to the left, some to the right; some faster, some slower; some bigger, some smaller–and then run each of those storms through SLOSH. We then “scramble” the SLOSH output from all storms together and derive statistics that tell us the probability of certain storm surge heights at given locations along the coast.
If we go back to our example from Hurricane Ivan, we can see the value of this method in assessing storm surge risk. The image below shows the probability that the storm surge would reach at least 8 ft. above the reference level (NGVD29) for Ivan from the NHC Tropical Cyclone Storm Surge Probability product. The first thing that should jump out at you is that the probability of at least 8 ft. of surge was just about equal in Mobile Bay (60-70% chance) and Pensacola Bay (50-60% chance). The probabilistic approach indicates that both areas were at a significant risk of storm surge, and both areas should have been preparing similarly for the arrival of the storm. Because we accounted for the uncertainty in the official forecast, we were able to assess the true storm surge risk for all areas near the coast.
The Tropical Cyclone Storm Surge Probability product provides the data that are used to create the Potential Storm Surge Flooding map that will be available experimentally beginning in the 2014 hurricane season. In other words, the Potential Storm Surge Flooding map accounts for the uncertainties associated with NHC’s tropical cyclone forecasts. In Part 3 of this storm surge series, we’ll talk more about the map itself and how it should be interpreted.