Using Forensic Meteorology to Verify Hurricane-Related Insurance Claims
2017 was a record-setting year for global insured (and un-insured) losses due to natural disasters, driven in no small part by the costliest hurricane season in U.S. history. Most of the estimated $200 billion in U.S. damages resulted from the wraths of hurricanes Harvey, Irma, and Marie during August and September 2017; and while nature required only a few weeks to wreak such havoc, assessing, tallying, and ultimately rebuilding from the damage will take far longer.
Although assessing hurricane-related claims may seem fairly straightforward to those unfamiliar with the process – “Hey, the building was either hit by a hurricane or it wasn’t, am-I-right?” – meteorologists and experienced claims adjusters know that often isn’t the case, especially as one moves farther from the eye of the storm and therefore farther from the most extreme and obvious impacts.
It is with these more ambiguous claims that forensic meteorology offers valuable insight – reconstructing conditions at the loss location to identify and quantify hurricane-related hazards.
Almost without exception, damage due to tropical cyclones (hurricanes and tropical storms) can be attributed to high winds, extreme rainfall, and/or storm surge. The magnitude of these impacts at any given location depends on numerous factors beyond simply the closest approach of the eye of the storm. The strength, size, and speed of the tropical cyclone; coastal topography; orientation of the coast relative to the storm’s wind field; distance from the coast; and the relative location of landfall all play determining roles.
Failure to understand and account for these factors can lead to under- or over-estimation of impacts, and ultimately to poor coverage decisions.
What follows is a discussion of each major impact (wind, rain, and storm surge) and the data and analytical tools available to reconstruct conditions at a given location. The following discussion specifically addresses tropical cyclone-related hazards, but many of the same analytical methods can be applied to other types of weather events, including severe thunderstorms.
In the 45 years since the Saffir-Simpson scale was introduced, hurricane wind speeds have become nearly synonymous with hurricane intensity and damage potential. A Category 1 storm with sustained surface winds of 74-95 mph is described as producing “some damage,” mainly to roofs, fences, trees, and telephone poles; while a Category 5 storm with sustained winds above 157 mph is described as producing “catastrophic damage,” completely destroying a large percentage of framed structures and leaving the impacted area uninhabitable for weeks to months.
While there is value to the Saffir-Simpson scale – increasing winds do indeed produce increasing damage – the maximum sustained surface wind speed near the eye of a hurricane does not capture the whole story of that storm’s destructive potential.
Two storms with similar maximum wind speeds can produce vastly different amounts of damage – the size of the storm, and therefore the size of its wind field, as well as the forward speed of the storm greatly influence its destructive potential, as Category 3 hurricanes Ivan ($18.8 billion in damages) and Dennis ($2.5 billion in damages) demonstrated when they impacted the same areas along the Gulf Coast just 10 months apart in 2004 and 2005. Despite similar maximum wind speeds, Ivan – a larger storm – produced seven and a half times more damage. In other words, size matters with hurricanes.
Recognizing that maximum wind speed isn’t the best measure of a hurricane’s destructive potential, the tropical meteorology community has been developing new, more comprehensive indices. Such indices include the Cyclone Damage Potential (CDP) index as well as Integrated Kinetic Energy, both of which account for a tropical cyclone’s size as well as its maximum sustained winds.
Although these metrics have not yet seen widespread use outside the meteorology community, expansion to the emergency management community and ultimately to the media and the general public is likely in coming years as these groups seek a more accurate understanding of – and more effective way to communicate – hurricane-related dangers.
Winds within a hurricane – both sustained winds and gusts – are generally strongest in and near the eye wall, with wind speeds decreasing with distance from the center of the storm. The smaller the hurricane, the more quickly winds decrease with distance.
For example, Hurricane Andrew was a very compact storm whose sustained hurricane-force winds extended outward only 30-45 miles, while Hurricane Irma – a much larger storm – had hurricane-force winds extending outward nearly 100 miles. Despite similar maximum wind speeds near the eye of the storm, if a property were 50 miles from the center of Hurricane Irma, it would have experienced significantly higher wind speeds than a property 50 miles from the center of Hurricane Andrew.
Tornadoes can and most often do occur far removed from the center of a hurricane, in the outer bands of discrete thunderstorms that rake counterclockwise away from the eye of the storm. The vast majority of these tornadoes develop in the right-front quadrant of the hurricane, relative to its direction of motion. During Hurricane Irma, 23 tornadoes were identified across the state of Florida. All occurred in areas impacted by Irma’s right-front quadrant.
Tornadoes that form in association with hurricanes are generally short-lived and relatively weak, occurring most often near the coast where wind shear is strongest as the discrete thunderstorms move ashore. However, tornadoes in tropical cyclones can occur further inland: more than two dozen tornadoes were reported in and around the Houston metro area during Hurricane Harvey, some nearly 80 miles from the coast.
If significant wind damage is observed at a property located 50-200 miles from the center of a tropical cyclone, tornadic impact should be investigated as a possible explanation.
Straight-line wind speeds are assessed through both in-situ (weather station) observations as well as post-storm damage surveys. For locations near a weather radar site, radar velocity data of near-surface winds can also be extrapolated to estimate surface winds (this method is less useful for locations far from the radar, where extrapolation becomes less accurate).
Hurricane wind gusts can and often do cause even the most robust weather station anemometers to stop working. During Hurricane Irma, many of the weather stations located at Miami-area airports stopped reporting wind speeds during the peak of the storm.
Therefore, to obtain the most comprehensive and rigorous reconstruction of wind conditions, all three data sources should be used. Weather station data provide on-the-ground observations, while damage surveys assess the aftermath to determine the wind speeds necessary to produce the observed damage. In areas removed from weather stations or population centers, weather radar offers data on winds aloft and insight into winds near the surface.
Tornadoes, which are small-scale phenomena that rarely happen to impact a weather station, are assessed through damage surveys and radar data. The storm cells that produce tornadoes in tropical cyclones are generally shallow, so radar data is most useful for locations within 60-70 miles of the radar site. Beyond that distance, the radar beam may overshoot the top of the storm.
As Hurricane Harvey demonstrated to devastating effect in August of last year, rainfall-induced flooding can be at least as destructive as extreme winds during tropical cyclones. Harvey is estimated to have caused more than $100 billion in damages, primarily due to widespread flooding in and around the Houston metropolitan area – far more damage than was wrought by the storm’s winds.
Although the more-than-four-feet of rain that Harvey squeezed out of the skies over Texas were truly unprecedented, most tropical cyclones produce intense, heavy rainfall that can lead to flooding both during and after the storm, often far inland of the landfall location. Over the last 30 years, such inland flooding has been responsible for more than a quarter of the deaths associated with tropical cyclones in the United States.
In-situ rain gauge data provide measured rainfall totals at specific locations. In urban areas rain gauges may be less than 5 miles apart, while in rural areas, they can be 50 or more miles apart. Radar data can fill in the gaps between rain gauges by providing rainfall estimates anywhere within the radar’s coverage area.
Radars estimate rainfall using an algorithm that associates radar reflectivity values with rainfall rates. The exact relationship between reflectivity and rainfall rate can differ between storm events; so to determine whether the radar rainfall estimates are accurate for a given event, in-situ measurements should be compared to the radar estimate of rainfall at those locations. Confidence in the radar estimate increases when the radar-estimated rainfall total is similar to what was measured at a rain gauge at the same location.
Rain gauges and weather radar can tell us how much it rained but not whether that rainfall actually caused flooding. To determine the locations and extent of flooding, we turn to storm reports and damage surveys. The National Weather Service collects storm reports for all tropical cyclones, and the US Geological Survey conducts damage surveys for most major flooding events. For prolonged, widespread flooding events like Hurricane Harvey, satellite data can also reveal which areas were impacted.
Along the coast, storm surge is often the greatest threat to life and property when a hurricane strikes. As with hurricane winds, the most severe storm surge typically accompanies the right-front quadrant of the storm, where the storm’s wind field and forward motion act to push water onshore. But unlike hurricane winds, which tend to be similar in nearby areas and gradually decrease with distance from the eye, storm surge can vary greatly even within the span of a few miles.
The reason for this variability is that storm surge is a complex phenomenon dependent on characteristics of both the hurricane and the local landscape.
Among the local variables that impact storm surge are the width and slope of the continental shelf as well as the geometry of the coast, bays and estuaries. All else being equal, storm surge along a coast fronted by a wide, shallow continental shelf – as exists along much of the Gulf Coast – will be significantly greater than along a coast where the continental shelf drops away quickly.
Among the storm-specific variables that impact storm surge are hurricane intensity, size, forward speed, and angle of approach to the coastline. The slightest change to any one of these characteristics can significantly increase or decrease storm surge potential. Despite popular belief, it is the winds of the hurricane that generate the vast majority of its storm surge – less than 5% of the surge is due to the low-pressure effect of the storm “sucking up” the ocean toward its center.
In addition to storm surge – formally defined as the abnormal rise of water generated by a storm – one must also consider the local astronomical tide. Storm surge rides atop the normal tidal flow, creating a combined “storm tide” that ultimately determines the depth and extent of inundation. A storm that strikes at high tide can result in inundation several feet deeper than if that same storm strikes at low tide.
A final factor that influences damage along the immediate coast is wave action. Neither the storm surge nor the storm tide take into account the effects of large, wind-drive waves that batter the coast during a hurricane. Wave action can significantly increase the impact of storm tide along the immediate coast, overtopping seawalls and sandbags where the storm tide alone would not. Often, the height of waves riding atop the storm tide can exceed the height of the storm tide itself.
As a recent example, during Hurricane Irma, wave wash marks in the lower Florida Keys were observed 10 – 15 feet above the storm tide. Water has a weight of 1,700 pounds per cubic yard, so prolonged pounding by large waves can cause substantial structural damage.
Ahead of a hurricane, the United States Geological Survey (USGS) typically deploys a network of temporary storm-tide sensors along the immediate coast in the projected path of the storm. These sensors record the depth of the storm tide throughout the event, and comparison of the maximum storm tide at nearby sensors provides insight into the range of water levels experienced along a particular stretch of coastline.
In those areas not covered by the storm tide sensor network, the USGS often performs surveys of visible high-water marks in the immediate aftermath of the storm. High-water marks are created when small, light debris carried along the top of the water is deposited on vertical surfaces like walls and doorways, and as with storm tide sensors, they provide data about the maximum water height at a given location.
The National Weather Service also performs post-storm damage surveys that include findings regarding storm surge, maximum inundation, and wave height, if available.
The Bottom Line
Tropical cyclones tend to be well-documented extreme weather events. Data from weather stations and radar sites generally become available within a few days of the event, while post-tropical cyclone reports and summary storm reports require weeks to months of processing before they are released. Forensic meteorological analysis of site-specific storm impacts can therefore begin almost immediately and can be updated as new data becomes available.
If you are involved in a weather-related investigation and would like to discuss how a forensic meteorologist could support that work, please reach out to Blue Skies Meteorological Services for a free, no-obligation consultation.
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.