Between 1963 and 2012, only 11% of tropical cyclone (hurricane and tropical storm) deaths were due directly to the wind. Yes, hurricane-force winds can be frighteningly destructive and frankly awe-inspiring, but when the numbers are tallied, water is undeniably the deadlier threat. Combined, storm surge, inland flooding due to heavy rains, and high surf are responsible for 88% of tropical cyclone deaths. The storm surge alone kills nearly half of all people who lose their lives during these events.
The reasons for this are simple but not necessarily obvious.
Especially in areas with modern building codes and construction, structures can withstand long duration strong winds. Even when structures are significantly damaged by debris or the wind itself, they continue to offer some shelter and protection from the wind. This is why people in the path of a tornado are advised not to jump in their car and drive away but rather to shelter in place in an interior room on the lowest floor. The roof can be ripped off a building and the exterior walls toppled, yet a tiny bathroom or closet often remains intact and offers a pocket of safety amidst the chaos.
Water is different. It rises inexorably, under doors and through windows. No room is safe. Entire neighborhoods are engulfed at once – there is no accessible safe haven once the water begins to rise. Storm surge water seethes with debris, from toxic waste to power lines to floating vehicles. And unlike the wind, which weakens quickly as a storm departs, storm surge and inland floodwaters can engulf a region for days to weeks. Those who don’t drown during the storm are often trapped without water or food until rescue personnel arrive, and when the impacted area is large and damage is extensive, rescue can be slow coming.
If you were watching news coverage as Hurricane Matthew marched menacingly up the east coast of Florida earlier this month, you probably noticed that meteorologists and local officials were focusing far more on the potential for unprecedented storm surge than on the storm’s maximum winds, despite Matthew being a Category 3 or 4 storm with winds up to 145 mph at times. Major Florida cities along the Atlantic coast and along the St. John’s River (which empties into the Atlantic Ocean just east of Jacksonville, FL) were threatened by a storm surge unseen for at least a century.
Matthew was a major hurricane with destructive winds, but it was the water, not the wind, that led governors, mayors, meteorologists, and emergency managers alike to issue impassioned pleas for those in the path of the storm to evacuate. Like hurricanes Sandy, Ike, and Katrina before it, Matthew testified to the fact wind tells only part of the story of a cyclone’s destructive power.
The rest of that story, and the far deadlier chapters, are told by water.
And starting this year, emergency managers, public officials, and the general public have another tool to evaluate the impact of that water on their communities. Developed by the National Weather Service and made operational for the 2016 hurricane season, Potential Storm Surge Flooding Maps are specific to each tropical cyclone and show a reasonable worst-case scenario for storm surge inundation at the neighborhood level. In other words, it shows the storm surge heights that a person should prepare for before a storm, given the uncertainties in the meteorological forecast.
The Potential Storm Surge Flooding Maps are based on the existing National Weather Service (NWS) Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model. (Modeling involves a dizzying and inescapable array of acronyms.) The SLOSH model takes into account forecast uncertainty and, when run as an ensemble, provides an envelope of possible storm surge outcomes based on the current forecast.
Ensemble modeling involves running a model (or group of models) many different times, each time with small differences in the initial conditions or model assumptions. For the SLOSH model, these differences represent plausible futures for the track and intensity of the hurricane given current observations and historical forecast errors. The result is a set of possible storm surge scenarios, with each member of the set representing a slightly different hurricane track and intensity.
Once this set – or “ensemble” – is assembled, it is analyzed statistically to determine a reasonable worst-case storm surge scenario at each location, and the depth of that storm surge is displayed on the Potential Storm Surge Flooding Maps. In this instance, “reasonable worst-case” is defined as that storm surge depth which has a 1-in-10 chance of being exceeded at each location. (In other words, at any given location, there is a 90% chance that the actual storm surge will be less than or equal to what is displayed on the map, given the current forecast.)
The Potential Storm Surge Flooding Maps are a valuable visual tool to assess storm surge risk as a tropical cyclone approaches land. The SLOSH model that forms the basis of the maps takes into account the factors most critical in determining storm surge:
However, the potential storm surge flooding map does not take into account a number of factors that do not impact storm surge directly but that nonetheless greatly impact overall flooding and water damage. The maps do not account for:
Wave action can significantly increase the impact of storm surge along the immediate coast, overtopping seawalls and sandbags where the storm surge alone would not. The potential storm surge flooding maps show only the potential storm surge – they do not provide any information about expected wave height. In many cases, the height of waves riding atop the storm surge can exceed the height of the storm surge itself.
Information about expected wave height and wave action impacts can be found in hurricane-related text products from the National Weather Service, including the local area forecast discussions and hazards and impacts statements. Interests along the coast and in areas protected by levees should pay particular attention to the impacts of wave action and weigh those impacts in addition to the direct impacts of the storm surge when making hurricane preparations.
Freshwater and Inland Flooding
Flash flooding, areal flooding, and river flooding due to excessive rainfall are responsible for over one quarter of all tropical cyclone-related deaths and can impact areas far inland and outside of the storm surge risk area. Hurricanes and tropical storms can dump tremendous amounts of rain in a short period of time. Even weak tropical systems can produce devastating amounts of rain. For example, the remnants of Tropical Storm Amelia in 1978 flooded central Texas with four feet of rain. Interests in low-lying areas prone to flooding and along creeks and rivers expected to be impacted by a tropical system should pay careful attention to rainfall forecasts and expected impacts.
Forecasting the protection offered by levees during a tropical cyclone is complex and difficult, as Hurricane Katrina tragically demonstrated in 2005. Wave action, the depth and speed of the storm surge, and the strength and construction of the levees all influence the amount of protection they provide. Interests living in leveed areas need to remain especially vigilant as a tropical cyclone approaches, and consider all relevant risks, not just those posed by the storm surge.
The potential storm surge flooding maps issued during Hurricane Matthew’s approach of Florida’s east coast offered a clear and dire assessment of the risk for unprecedentedly severe storm surge inundation.
The maps for Hurricane Matthew were so dire because the worst-case scenario was squarely within the cone of uncertainty. It wasn’t just possible. It was likely that locations along the east coast and the St. John’s River would be under several feet or more of water if the hurricane continued to hug the coast or made landfall in northeast Florida or southeast Georgia.
More than just the beaches were under threat. The potential storm surge flooding maps showed areas along the St. Johns River — inland regions that don’t typically think of themselves as vulnerable to storm surge –- under up to 6 feet of water as Matthew pushed a wall of water at the coast and up the mouth of the St. Johns. Although the worst-case scenario fortunately did not materialize, reports were still received of the St. Johns River flowing backwards on the morning of Saturday, October 8th, as storm surge and hurricane-force onshore winds pushed the sea inland.
“Fortunately” is the correct word in this situation, because it was nothing more or less than luck that prevented a truly worst-case scenario from actualizing. Had Matthew drifted 20 miles farther the west, the Atlantic coast of Florida, and inland river cities like Jacksonville and Palatka would have experienced truly devastating flooding.
The National Weather Service’s new potential storm surge flooding maps provide a graphical, easy-to-understand, quantitative assessment of storm surge risk along the U.S. Gulf and Atlantic coasts. By displaying a reasonable worst-case scenario at each location, they show both local officials and the general public the storm surge depth for which they should prepare themselves, enabling well-informed preparation and evacuation decisions.
However, these maps are not intended to offer a complete picture of water-related risks associated with tropical cyclones. They do not take into account wave action (i.e. waves riding atop the storm surge), rainfall-induced flooding, or potential levee failures. These impacts must be considered separately when assessing the impact of a hurricane or tropical storm in a given area.
And, as always, the output of any model is only as good as its input.
Ultimately, the accuracy of the potential storm surge flooding maps depends on the accuracy of the hurricane track and intensity forecast. Those forecasts – and the storm surge inundation maps derived from them – are continually refined as new data from in-situ and remote sensing platforms (like hurricane hunter aircraft measurements and satellite imagery, respectively) as well as new model guidance become available.
Last spring we wrote about the capabilities of dual-polarization radar to identify and distinguish between regions of different types of precipitation within thunderstorms and winter weather events (see “Seeing in the Dark”). This powerful technology provides valuable information to operational meteorologists deciding whether to issue a warning for damaging weather and to forensic meteorologists reconstructing that weather and its impact.
It is also used by the dozens of online hail track products marketed to both construction contractors and insurance claims investigators. These automated hail track products can provide a useful first estimate of hail impact, but they are far from perfectly accurate.
Megan Walker Radtke, chief meteorologist and climatologist here at Blue Skies, recently published an article in Claims Magazine discussing the use of hail track products for insurance claims investigation, including when they should be used with caution.
Check out the article in Claims Magazine’s July digital edition.
Weather radar works by emitting microwave radiation into the sky and then listening for the signal that’s reflected back. It’s a meteorological game of Marco Polo.
All sorts of targets reflect the microwaves – raindrops, snowflakes, hailstones, bats, airplanes, and even swarms of insects. How well a given target reflects microwaves depends on its composition, size, and shape. For instance, liquid water is a better reflector of radar energy than ice.
When a meteorologist looks at a radar display, she’s seeing the reflected signal from all those targets in a given slice of sky. The radar doesn’t “know” which piece of reflected energy came from a bird and which piece came from the hailstone that moments later cracked your car windshield. The radar simply aggregates the reflected signal. It’s up to the meteorologist to interpret the results.
Until just a few years ago, the National Weather Service’s network of weather radars collected information about only two quantities: the reflected energy from a given section of sky (reflectivity) and the velocity of the targets within that section (mean radial velocity and spectrum width). In complex meteorological situations like winter weather events or severe storms, these two pieces of information provide only an incomplete picture of the type of precipitation that’s falling. When you’re just looking at reflectivity and velocity data, for instance, it can be difficult to tell the difference between hail and heavy rain. Yet on the ground, knowing the difference can be critical.
Enter dual-polarization radar technology. If you’ve ever owned polarized sunglasses, you’re already familiar with the principle of polarization. The short-n-sweet version is that electromagnetic waves (like radio waves emitted by radar or visible light waves emitted by the sun) can be oriented along a certain axis.
Tilt your head from side to side while wearing polarized sunglasses, and you’ll notice that the image you see changes – the color of the sky darkens and lightens, glare off the pavement appears and disappears. As you tilt your head, you’re actually changing the polarization of the light that’s being let through your sunglasses, and that gives you additional information about the world around you.
The same is true with weather radar. Conventional radar sends out radio pulses polarized only in the horizontal direction, so the reflected signal carries only 1-dimensional information. Dual-polarization (or “dual-pol”) radar, on the other hand, sends out both horizontally polarized pulses and vertically polarized pulses, so the reflected signal carries 2-dimensional data.
This may seem rather trivial until you consider that precipitation types have characteristic shapes. Small raindrops are spherical, while big raindrops flatten out like a Frisbee. Hailstones are roughly spherical when they’re dry but can become oblong as their outer layers melt. The two-dimensional data provides invaluable insight into what types of precipitation are present within a storm.
Here in Florida, we don’t have to worry too much about winter weather, but hail is another matter. In the lightning capital of the United States, thunderstorms are part of the scenery for much of the year, and most thunderstorms, if they are strong enough and reach high enough into the atmosphere, produce hail.
But that hail doesn’t always reach the ground. In warm, moist atmospheres, hail melts as it falls toward the ground. If the hail starts out small or if the freezing level is high in the atmosphere, hail can melt completely before reaching the ground. Dual-pol radar data can reveal whether a storm is producing hail aloft, and by examining radar data at different heights within the storm, meteorologists can determine whether and how much that hail is melting before it reaches the surface (and people’s cars and houses).
Dual-pol radar adds three more tools to the meteorologist’s kit. Each of these tools provides unique information about the size, shape, and mixture of precipitation types within a storm.
Correlation Coefficient (CC)
Correlation coefficient measures how similarly the returned horizontal and vertical pulses are behaving. It’s like looking at the world under a strobe light. From one flash to the next, how much does the image change? When the targets within a given region are of the same shape and type (for example, all medium-sized raindrops), one pulse will look much like the next, and the correlation coefficient will be high. If, on the other hand, precipitation types are mixed (like rain and hail swirling together), correlation coefficient values will be lower. Generally, the larger the hail, the lower the correlation coefficient.
Differential Reflectivity (ZDR)
Differential reflectivity compares the reflectivity values returned in the horizontal and vertical directions, like comparing how much the image through your polarized sunglasses changes as you tilt your head. Targets that are wider than they are tall (like large raindrops) have higher differential reflectivity – they reflect more horizontally polarized energy than vertically polarized energy. Hailstones, on the other hand, are more spherical and tend to tumble as they fall, reflecting roughly equal amounts of horizontally and vertically polarized energy. Hail typically has low to near-zero ZDR values.
Specific Differential Phase (KDP)
Specific differential phase is a bit more complicated than correlation coefficient and differential reflectivity. Physically, KDP measures the phase shift of the returned horizontal and vertical signals. In practice, this means that specific differential phase responds to both the shape and the density of liquid water targets. Frozen precipitation, like dry hail and snow, do not contribute to KDP – KDP “ignores” frozen precipitation and sees only liquid precipitation. Specific differential phase is therefore useful for determining rainfall rate.
As part of the dual-polarization upgrade, National Weather Service weather radars now incorporate an algorithm that estimates precipitation type from the dual-pol variables discussed above. Numerous automated hail report websites use the National Weather Service algorithm or a custom one to identify regions of hail. While such algorithms provide a useful first-pass to identify regions within a storm where hail is likely being produced aloft, they do not provide information about whether that hail is reaching the ground and at what size.
When Blue Skies Meteorological Services investigates the presence of hail for a forensic meteorology case, we don’t just run an algorithm and depend on the radar to “know” what was happening in the storm and to assume what was happening on the ground. We examine official storm reports, severe weather warnings and advisories, the atmospheric profile, and dual-polarization radar data at multiple heights and throughout the lifetime of the storm to reconstruct a comprehensive picture of the weather situation – both high in the storm and on the ground, where it matters.
Even Florida got in on this week’s pre-holiday winter chill, with Blue Skies’ home base of Gainesville, FL, breaking records for lowest maximum temperature (53 degrees on Nov 18) and lowest minimum temperature (24 degrees on Nov 20). (Yes, yes, the world’s tiniest violin is playing the world’s saddest song for the poor, shivering Floridians while upstate New Yorkers roll their eyes and stoically shovel out from 6+ feet of snow.)
This fierce onset of winter caught many people across the country by surprise. After all, it’s not even Thanksgiving. Although temperatures will be moderating over the weekend for much of the US – bringing the risk of flooding to many affected by this week’s snowstorm in the northeast and a welcome and benign warm-up to many others – the annual rollercoaster of winter weather is just beginning.
If you’ve ever wondered why winter weather fluctuates so dramatically, you’re not alone. And you can place much of the blame on the location of the polar jet stream. Yeah, we know – it’s easier to blame the meteorologist messenger. But hear the messenger out on this one.
Jet streams are like fast-moving rivers of air in the upper troposphere, at approximately the same altitudes that commercial aircraft cruise. And just as rivers of water flow faster when the elevation change is dramatic and steep, jet streams become more vigorous during the winter, when the temperature difference (“gradient”) between the poles and the equator is more dramatic (it’s beach weather year round in Key West, but come January in Maine, you’re going to want to be wearing more than just a swimsuit).
As winter progresses, the pool of cold air at the poles expands and sinks southward. Since jet streams are found where the temperature gradient is largest – at the boundary between cold and warm air – the polar jet slides southward along with the expanding pool of cold air. Although in summer, the polar jet is typically pinned near the US-Canada border, in winter it can plunge as far south as Florida.
The polar jet isn’t straight, either, but rather meanders from north to south, bringing that characteristic wintertime rollercoaster of relatively warm and sunny weather (under ridges) followed by cold, dreary, and occasionally downright miserable weather (in troughs).
Where the jet stream ends up draping itself and how strong it is determines much about the winter’s weather. Certain large-scale factors (like the presence of an El Niño or La Niña), can exert a powerful influence on the average position of the jet stream and therefore on seasonal temperatures and precipitation.
Despite indications this summer of a developing strong El Niño, it hasn’t materialized. Forecasters at the Climate Prediction Center are now calling for about a 60% chance of a weak El Niño developing this winter. This lack of a strong climate driver, like El Niño, makes seasonal forecasts somewhat less certain.
Although seasonal forecasts will never be able to predict daily high temperatures or the probability of afternoon precipitation months in advance, they can offer insight into general patterns and trends, like whether this winter is likely to be warmer or cooler than average. The strength of those patterns and trends, and therefore the skill of the seasonal forecast, is highest when strong, large-scale climate drivers dominate.
So, what about this winter’s weather? NOAA forecasters at the Climate Prediction Center are anticipating cooler than average temperatures across much of the Southeast and Southern Plains, with above average temperatures favored in the western US and throughout Alaska. Wetter than normal conditions are more likely throughout the southern US and along much of the East Coast, while drier than normal conditions are favored in the Northwest and Upper Midwest.
Given the fairly weak El Niño signal this year, forecast confidence isn’t particularly high, but for those folks in the northeast still reeling from this week’s snowstorm, take heart. That winter pummeling isn’t likely to be the season’s norm. But for those of us in Florida, it might be worth picking up another couple of ugly holiday sweaters from the sale racks… you know, for layering.
Typically, forensic meteorology is applied to weather events a few years old at most – Did damaging hail really strike that commercial facility in April of last year? Was it a tornado or a microburst that ripped off roofs and uprooted trees last week? Did a lightning strike start that house fire a few months back?
Occasionally, though, forensic meteorologists look decades or even centuries into the past. Such has been the case with Tropical Cyclone (TC) Mahina, which struck Bathurst Bay, Australia, on 5 March 1899 as a Category 5 storm. Since the publication of a research paper by H.E. Whittingham in 1958 titled “The Bathurst Bay Hurricane and associated storm surge” reported that TC Mahina produced a storm surge of 13 meters (or over 42 feet), that storm has generally been credited with the largest ever-recorded storm surge.
Contemporary accounts of the storm reported a waist-deep wall of water inundating a 40 ft tall ridge where several law enforcement officers were camped during the storm, dolphins being found stranded atop 15 m high cliffs after the storm had passed, and fragments of Aboriginal canoes being deposited 70 to 80 feet above the normal high tide.
TC Mahina was a undoubtedly a monster storm. With sustained winds of over 175 mph, it sank 54 ships (mostly pearling vessels) and killed more than 300 people, sweeping devastation across the Bathurst Bay region of northeastern Australia.
Yet despite its impressive statistics and a number of contemporary (albeit generally third-person) accounts of storm-related inundation, meteorologists have long regarded the 13 m storm surge record skeptically. It just didn’t seem possible. The commonly reported central pressure of 27 inches of mercury (914 mb), while extremely low, just doesn’t support a storm surge as high as a four-story building.
Previous studies that used computer models to estimate storm surge given the most likely track and intensity of the cyclone over this topographically complex region had come up well short of 13 m, and field work in the region had not found evidence of debris deposits to the reported 13 m height.
Something was amiss – either the central pressure was lower than 27 inHg or the storm surge wasn’t actually 13 m high. Possibly both.
Despite the contradictory evidence, little research had been done to set the record straight, until recently. In the May 2014 issue of the Bulletin of the American Meteorological Society (BAMS), several Australian scientists revealed the results of their forensic analysis of TC Mahina’s storm surge.
In that analysis, they utilized methods that forensic meteorologists often use to evaluate much more recent weather events: they investigated historical records, examined the physical evidence, and modeled the event. What they learned is that, as is often the case, the devil is in the details.
Previous modeling studies had relied upon a thirdhand account of Mahina’s central pressure published in an anonymously authored report several months after the cyclone made landfall. That central pressure – 27 inches of mercury (or 917 mb) – was simply too high to produce a 42 foot storm surge.
By combing through the historical record, though, the authors of the May 2014 study found several references to the storm’s central pressure as an astonishing 26 inHg (880 mb). All of those accounts ultimately were traceable to the same man – a ship captain whose schooner was the only vessel to experience – and survive – the eye of the cyclone. That captain, William Field Porter, also happened to write a letter to his parents recounting his harrowing experience. In it, he stated plainly that “the barometer was down to 26 [inches of mercury].”
So it would seem that the central pressure that had been used in previous modeling studies – studies that had failed to reproduce anything nearing a 13 m storm surge – had been too high. Perhaps the lower pressure of 26 inHg would create the reported record storm surge?
Before jumping straight into the modeling, though, the authors also re-examined the physical evidence – debris that was washed up and deposited by the storm. They found wave-deposited sandy sediments 6.6 meters above mean sea level at Ninian Bay, the location where law enforcement officers reported the 13 m storm surge, but they found no evidence of inundation above that.
This doesn’t necessarily rule out the 13 m water level, however. During tropical cyclones, the highest debris tends to consist of biological material that floats, like leaves, sea grasses, and small marine animals. This material also tends to biodegrade after a few years or decades, leaving no trace for forensic meteorologists peering 115 years into the past. Observations after more recent tropical cyclones suggest that sandy sediments can be deposited at only half the height of maximum inundation, so it is quite possible that the water did reach a height of 13 m above mean sea level at Ninian Bay, where those sandy deposits were found at 6.6 m.
Once the authors had concluded that there was a decent probability that the storm’s central pressure really was 26 inHg and that the waves at Ninian Bay really did reach 13 m above mean sea level, they set about to model the storm surge based on a range of storm forward speeds and storm tracks suggested by ships’ wind and pressure recordings as well as damage assessments after the storm passed.
What they discovered was that even in a worst-case scenario (Mahina approached Bathurst Bay from the northeast with a central pressure of 26 inHg), the storm surge would “only” be about 9 m.
And here is where the devil is in the details. You see, there’s a difference between storm surge and maximum inundation. Storm surge is the abnormal rise of water generated by a tropical cyclone, over and above the natural (astronomical) tides. Click here for an animation of storm surge in an area of steep topography, similar to Bathurst Bay. Storm surge is influenced by the size of the storm, winds speed within the storm, the forward speed of the storm as it approaches land, the angle of approach to the coast, the topography of the sea floor and coast, and the storm’s central pressure.
Maximum inundation, on the other hand, is just what it sounds like – the maximum height that water reaches above mean sea level. Maximum inundation is influenced by the height of the storm surge, the timing of astronomical tides, and various types of wave action like wave setup and wave run-up. It’s the high water mark.
And the high water mark is almost always higher than the storm surge. In fact, in severe tropical cyclones in northeastern Australia, wave and tidal effects have added approximately 25% to the height of maximum inundation.
What this means for Tropical Cyclone Mahina is that the 1899 accounts of a monster cyclone that brought the sea to the top of a 40 ft high cliff may in fact have been accurate. If the central pressure was actually 26 inHg and the storm approached from the northeast, it could have generated a storm surge of up to 9 meters (30 feet). Mahina struck during astronomical high tide, and that combined with wave setup and run-up could have added an additional 4 m (12 feet) of water on top of the storm surge.
So, the record for highest storm surge may have to be revised downward (Mahina’s storm surge was probably 9 meters or less), but its maximum inundation may still take the gold. It is entirely possible that on March 5th, 1899, men waded through seawater atop a 40 ft high cliff and dolphins swam through the tops of 50 ft tall trees.
Blue Skies Meteorological Services offers forensic meteorological analyses of a wide range of weather events — from hail storms to lightning strikes, from flooding to tornadoes, from fog to sun glare. We typically don’t look 115 years into the past, but we’re always up for unique and interesting challenges! Give us a call or send us an email to discuss your weather-impacted legal case, insurance claim, or investigation.