Thursday NOAA updated its forecast to an “extremely active” Atlantic hurricane season. That has some news outlets linking the 19-25 predicted named storms to Earth’s future—even warmer—global climate. The future looks like it will indeed bring high levels of overall “activity” due to the intense, damaging hurricanes of a warming world (regardless of whether the frequency of storms overall changes). And, of course, settling into a new “norm” isn’t going to happen while warming is ongoing. But the huge number of storms forming? That’s a lot of what the public takes away from the forecast, and that profusion of named storms is not projected to be characteristic of seasons to come.
As we blogged here in May, recent research published in the Bulletin of the American Meteorological Society finds there’s no evidence to support an increasing trend in tropical cyclone frequency.
In that assessment of the current literature, Tom Knutson (NOAA) and other top tropical experts reviewed a number of peer-reviewed studies and determined that a majority found the numbers of named storms actually decrease in climate projections as we move deeper into this century. But there was no consensus among the authors to either support or refute those studies since their research also showed that “there is no clear observational evidence for a detectable human influence on historical global TC frequency.”
Their assessment did find that we can expect stronger and wetter hurricanes in our warming world and, notably, a possible uptick in the number of intense (Category 4 and 5) hurricanes. It’s these storms that have Knutson and his colleagues most concerned since a majority of hurricane damage is done by the big ones. Their increase is alarming even if the number of storms goes down.
Notable with this week’s forecast update is a prediction close to record territory. “We’ve never forecast up to 25 named storms” before—more than twice a season’s typical 12—noted Jerry Bell, lead seasonal hurricane forecaster at NOAA’s Climate Prediction Center. He went on to say there will be “more, stronger, and longer-lived storms than average” in the Atlantic Basin, which includes the Caribbean Sea and Gulf 0f Mexico. In an average season there are six hurricanes, and three of those grow into major hurricanes.
hurricanes
The Forecast for Huge Numbers of Hurricanes in 2020: Not a “New Normal”
Thursday NOAA updated its forecast to an “extremely active” Atlantic hurricane season. That has some news outlets linking the 19-25 predicted named storms to Earth’s future—even warmer—global climate. The future looks like it will indeed bring high levels of overall “activity” due to the intense, damaging hurricanes of a warming world (regardless of whether the frequency of storms overall changes). And, of course, settling into a new “norm” isn’t going to happen while warming is ongoing. But the huge number of storms forming? That’s a lot of what the public takes away from the forecast, and that profusion of named storms is not projected to be characteristic of seasons to come.
As we blogged here in May, recent research published in the Bulletin of the American Meteorological Society finds there’s no evidence to support an increasing trend in tropical cyclone frequency.
In that assessment of the current literature, Tom Knutson (NOAA) and other top tropical experts reviewed a number of peer-reviewed studies and determined that a majority found the numbers of named storms actually decrease in climate projections as we move deeper into this century. But there was no consensus among the authors to either support or refute those studies since their research also showed that “there is no clear observational evidence for a detectable human influence on historical global TC frequency.”
Their assessment did find that we can expect stronger and wetter hurricanes in our warming world and, notably, a possible uptick in the number of intense (Category 4 and 5) hurricanes. It’s these storms that have Knutson and his colleagues most concerned since a majority of hurricane damage is done by the big ones. Their increase is alarming even if the number of storms goes down.
Notable with this week’s forecast update is a prediction close to record territory. “We’ve never forecast up to 25 named storms” before—more than twice a season’s typical 12—noted Jerry Bell, lead seasonal hurricane forecaster at NOAA’s Climate Prediction Center. He went on to say there will be “more, stronger, and longer-lived storms than average” in the Atlantic Basin, which includes the Caribbean Sea and Gulf 0f Mexico. In an average season there are six hurricanes, and three of those grow into major hurricanes.
Isaias' Forecast Rains, Evaluated Through the New ERM Perspective
Tropical Storm Isaias is soaking the Mid-Atlantic states with what is expected to be three times as much rain as is typical for the area. Today’s heaviest tropical showers could trigger potentially deadly flash floods.
The projection is the finding of a new Intuitive Metric for Deadly Tropical Cyclone Rains, which we blogged about on The Front Page in June. The extreme rainfall multiplier (ERM) used the quantitative precipitation forecast (QPF) from the Storm Prediction Center last night to generate an ERM forecast for Isaias.
“Since Isaias is a fast-moving storm (currently moving NNE at 23 mph), the heaviest rain is forecast to fall with[in] a 24-hour period today (Aug 4)”, wrote the study’s lead author, Christopher Bosma, a Ph.D. student at the University of Wisconsin-Madison, in a-pre-dawn e-mail. “Peak rainfall totals are projected to be just over 6 inches (approx. 150 mm), mostly in a narrow region just south of the DC Metro [area].”
In contrast, the region’s heaviest single-day, 2-year rainfall event is a bit more than 50 mm. Bosma uses that comparison in generating an ERM around 2.86 (152 mm / 53 mm). Rainfall may exceed the projections, but that gives a rough idea of how the storm compares to others in residents’ recent memory.
According to the study, which was published in the Bulletin of the American Meteorological Society in May, the average value of an ERM in U.S. landfalling hurricanes and tropical storms is 2.0. ERMs can hindcast the severity of precipitation for such storms, like 2017’s Hurricane Harvey. Harvey deluged Texas with as much as 60 inches of rain and reached an ERM of 6.4—the highest calculated.
Those having lived in the D.C. area in the early 2000s might recall a tropical storm that Bosma says is comparable to Isaias: Isabel. After landfall in eastern North Carolina as a Cat. 2 hurricane the morning of September 18, 2003, it barreled north-northwest through the Mid-Atlantic delivering flooding rains and damaging winds that night.
“Isabel was also a fast mover at landfall, and was responsible for similar one-day rain totals of just over 6 inches, based on CPC-Unified gauge-based gridded data,” Bosma wrote.” The peak ERM for Isabel was 2.8. One thing to note from Isabel is that localized rainfall totals were higher in some spots, particularly in the mountains of Virginia, highlighting the threat of localized flash flooding that might also be present today with Isaias.”
Indeed, flash flood warnings were issued all across the interior Mid-Atlantic this morning. This was despite drought conditions in parts of the area.
Bosma and colleagues Daniel Wright (UW-Madison), J. Marshall Shepherd (University of Georgia), et al., created the ERM metric to focus on the deadly hazard of extreme tropical cyclone rainfall. Getting word out about the threat using only the wind-based Saffir-Simpson Scale “was a problem brought to light with Hurricanes Harvey and Florence,” Shepherd says.
Wright also in an e-mail last night stated that for Isaias in and around Washington, D.C., it’s “a fairly large amount of rain, though certainly not unprecedented for the region.”
Isaias’ Forecast Rains, Evaluated Through the New ERM Perspective
Tropical Storm Isaias is soaking the Mid-Atlantic states with what is expected to be three times as much rain as is typical for the area. Today’s heaviest tropical showers could trigger potentially deadly flash floods.
The projection is the finding of a new Intuitive Metric for Deadly Tropical Cyclone Rains, which we blogged about on The Front Page in June. The extreme rainfall multiplier (ERM) used the quantitative precipitation forecast (QPF) from the Storm Prediction Center last night to generate an ERM forecast for Isaias.
“Since Isaias is a fast-moving storm (currently moving NNE at 23 mph), the heaviest rain is forecast to fall with[in] a 24-hour period today (Aug 4)”, wrote the study’s lead author, Christopher Bosma, a Ph.D. student at the University of Wisconsin-Madison, in a-pre-dawn e-mail. “Peak rainfall totals are projected to be just over 6 inches (approx. 150 mm), mostly in a narrow region just south of the DC Metro [area].”
In contrast, the region’s heaviest single-day, 2-year rainfall event is a bit more than 50 mm. Bosma uses that comparison in generating an ERM around 2.86 (152 mm / 53 mm). Rainfall may exceed the projections, but that gives a rough idea of how the storm compares to others in residents’ recent memory.
According to the study, which was published in the Bulletin of the American Meteorological Society in May, the average value of an ERM in U.S. landfalling hurricanes and tropical storms is 2.0. ERMs can hindcast the severity of precipitation for such storms, like 2017’s Hurricane Harvey. Harvey deluged Texas with as much as 60 inches of rain and reached an ERM of 6.4—the highest calculated.
Those having lived in the D.C. area in the early 2000s might recall a tropical storm that Bosma says is comparable to Isaias: Isabel. After landfall in eastern North Carolina as a Cat. 2 hurricane the morning of September 18, 2003, it barreled north-northwest through the Mid-Atlantic delivering flooding rains and damaging winds that night.
“Isabel was also a fast mover at landfall, and was responsible for similar one-day rain totals of just over 6 inches, based on CPC-Unified gauge-based gridded data,” Bosma wrote.” The peak ERM for Isabel was 2.8. One thing to note from Isabel is that localized rainfall totals were higher in some spots, particularly in the mountains of Virginia, highlighting the threat of localized flash flooding that might also be present today with Isaias.”
Indeed, flash flood warnings were issued all across the interior Mid-Atlantic this morning. This was despite drought conditions in parts of the area.
Bosma and colleagues Daniel Wright (UW-Madison), J. Marshall Shepherd (University of Georgia), et al., created the ERM metric to focus on the deadly hazard of extreme tropical cyclone rainfall. Getting word out about the threat using only the wind-based Saffir-Simpson Scale “was a problem brought to light with Hurricanes Harvey and Florence,” Shepherd says.
Wright also in an e-mail last night stated that for Isaias in and around Washington, D.C., it’s “a fairly large amount of rain, though certainly not unprecedented for the region.”
Intuitive Metric for Deadly Tropical Cyclone Rains
With hurricanes moving more slowly and climate models projecting increasing rain rates, scientists have been grappling with how to effectively convey the resulting danger of extreme rains from these more intense, slow-moving storms.
Flooding rainfall already is the most deadly hazard from tropical cyclones (TCs), which include hurricanes and tropical storms. Yet the widely recognized tool for conveying potential tropical cyclone destruction is the Saffir-Simpson Scale, which is based only on peak wind impacts. It categorizes hurricanes from 1, with winds causing minimal damage, to 5 and catastrophic wind damage. But it is unreliable for rain.
Recent research by Christopher Bosma, with the University of Wisconsin in Madison, and colleagues published in the Bulletin of the American Meteorological Society introduces a new tool that focuses exclusively on the deadly hazard of extreme rainfall in tropical cyclones. “Messaging the deadly water-related threat in hurricanes was a problem brought to light with Hurricanes Harvey and Florence,” says J. Marshall Shepherd (University of Georgia), one of the coauthors. “Our paper is offering a new approach to this critical topic using sound science methods.”
“One goal of this paper,” Bosma explains, “is to give various stakeholders—from meteorologists to emergency planners to the media—an easy-to-understand, but statistically meaningful way of talking about the frequency and magnitude of extreme rainfall events.”
That way is with their extreme rainfall multiplier (ERM), which frames the magnitude of rare extreme event rainfalls as multiples of baseline “heavy” rainstorms. Scientifically, ERM is the ratio of a specific location’s storm rainfall and the maximum amount of rain that has fallen most often at the location in two consecutive-year periods from 1981 through 2010—the baseline rain events that are relatively frequent at that location. A recurring baseline heavy rain amount is defined by the median (rather than the mean) annual maximum rainfall during the 30-year period and is used to weed out outlier events.
The authors are proposing the scale to
1. Accurately characterize the TC rainfall hazard;
2. Identify “locally extreme” events because local impacts increase with positive deviations from the local rainfall climatology;
3. Succinctly describe TC rainfall hazards at a range of time scales up to the lifetime of the storm system;
4. Be easy to understand and rooted in experiential processing to effectively communicate the hazard to the public.
Experiential processing is a term meaning rooted in experience, and ERM aims to relate its values for an extreme rainfall event to someone’s direct experience, or media reports and images, of heavy rainfall at their location. Doing this has the benefit of enabling them to connect, or “anchor” in cognitive psychology terms, the sheer magnitude of an extreme rain event to the area’s typical heavy rain events, highlighting how much worse it is.
The researchers analyzed 385 hurricanes and tropical storms that either struck or passed within 500 km of land from 1948 through 2012 and, through hindcasting, determined an average ERM of 2.0. Nineteen of the storms had ERMs greater than 4.0. And disastrous rain-making hurricanes in the record had ERMs directly calculated as benchmark storms. These include the most extreme event, Hurricane Harvey with an ERM of 6.4, Hurricane Florence as well as 1999’s Hurricane Floyd, which swamped the East Coast from North Carolina to New England, (ERMs: 5.7), and Hurricane Diane (ERM: 4.9), which destroyed large swaths of the Northeast United States with widespread flooding rains in 1955, ushering “in a building boom of flood control dams throughout New England,” says, coauthor Daniel Wright, Bosma’s advisor at UW-Madison.
Wright says that a major challenge in developing ERM was maintaining scientific accuracy while widening its use to non-meteorologists.
I’ve been reading and writing research papers for more than 10 years that were written for science and engineering audiences. This work was a little different because, while we wanted the science to be airtight, we needed to aim for a broader audience and needed to “keep it simple.”
In practice, these historical values of ERM would be used to convey the severity of the rainfall hazard from a landfalling storm. For example the authors successfully hindcast ERM values in the Carolinas for Hurricane Florence, which inundated southeastern portions of North Carolina and northeastern South Carolina as it crawled ashore in 2018. With an active tropical storm or hurricane, the forecast value of ERM could be compared with historical hurricanes that have hit the expected landfall location.
Verification of NWS forecasts for the 3-day rainfall after landfall of Hurricane Florence (and ERM forecasts derived from these QPF estimates), issued at 1200 UTC 14 Sep 2018. Actual rainfall and 3-day ERM are based on poststorm CPC-Unified data.
In theory, the sound science is such that the ERM framework could be applied to other rain-producing storms.
“We think there is potential both for characterizing the spatial properties of all kinds of extreme rainstorms…and then also for examining how these properties are changing over time,” Wright says.
The researchers caution, however, that there are things that must be resolved before ERM can be used operationally as a communication tool. For example, ERM will need to be scaled to be compatible with NWS gridded rainfall products and generalized precipitation forecasts. Forecast lead times and event durations also will need to be determined. And graphical displays and wording still need to be worked out to communicate ERM most effectively.
Nevertheless, the team argues:
…our Hurricane Florence ERM hindcast shows that the method can accurately characterize the rainfall hazard of a significant TC several days ahead in a way that can be readily communicated to, and interpreted by, the public.
Above, Daniel Wright, of the University of Wisconsin-Madison
When Hurricanes Become Machines…or Monsters
Officially, the Atlantic season is almost upon us. The season of tropical storms and hurricanes, yes, but more to the point, the season of heat-seeking machines and relentless monsters.
At least, that’s the metaphorical language of broadcast meteorologists when confronted with catastrophic threats like Hurricane Harvey in Houston in 2017. A new analysis in BAMS of the figures of speech used by KHOU-TV meteorologists to convey the dangers of this record storm shows how these risk communicators exercised great verbal skill to not only connect with viewers’ emotions, but also convey essential understanding in a time of urgent need.
For their recently released paper, Robert Prestley (Univ. of Kentucky) and co-authors selected from the CBS-affiliate’s live broadcasts during Harvey’s onslaught the more than six hours of on-air time for the station’s four meteorologists. The words the meteorologists used were coded and systematically analyzed and categorized in a partly automated, partly by-hand process. No mere “intermediaries” between weather service warnings and the public, the meteorologists—David Paul, Chita Craft, Brooks Garner, and Blake Matthews—relied on “figurative and intense language” on-air to “express their concern and disbelief” as well as explain risks.
As monster, the hurricane frequently displayed gargantuan appetite—for example, “just sitting and spinning and grabbing moisture from off the Gulf of Mexico and pulling it up,” in Paul’s words. The storm was reaching for its “food,” or moisture. The authors write, “The use of the term ‘feeder bands’…fed into this analogy.” Eventually Matthews straight out said, “We’re dealing with a monster” and Craft called the disaster a “beast.”
When the metaphor shifted to machines, Harvey was like a battery “recharging” with Gulf moisture and heat or a combustion engine tending to “blow” up or “explode.” Paul noted the lingering storm was “put in park with the engine revving.”
Other figurative language was prominent. Garner explained how atmospheric factors could “wring out that wet washcloth” and that the saturated ground was like “pudding putty, Jello.” The storm was often compared to a tall layered cake, which at one point Garner noted was tipped over like the Leaning Tower of Pisa.
In conveying impact risks, the KHOU team resorted frequently to words like “incredible” and “tremendous.” To create a frame of reference, they initially referred to local experience, like “Allison 2.0”—referring to the flood disaster caused by a “mere” tropical storm in 2001 that deluged the Houston area with three feet of rain—until Harvey was clearly beyond such a frame of reference. Then they clarified the unprecedented nature of threats, that it would be a storm “you can tell your kids about.”
The authors note, “By using figurative language to help viewers make sense of the storm, the meteorologists fulfilled the “storyteller” role that broadcast meteorologists often play during hurricanes. They were able to weave these explanations together with contextual information from their community in an unscripted, ‘off-the-cuff’ live broadcast environment.” They conclude that the KHOU team’s word choices could “be added to a lexicon of rhetorical language in broadcast meteorology” and serve as a “a toolkit of language strategies” for broadcast meteorologists to use in times of extreme weather.
Of course all of this colorful language was, perhaps, not just good science communication but also personal reality. Prestley et al. note: “The KHOU meteorologists also faced personal challenges, such as sleep deprivation, anxiety about the safety of their families, and the flooding of their studio. The flood eventually forced the meteorologists to broadcast out of a makeshift studio in a second-floor conference room before evacuating their building and going off air.”
As water entered the building, Matthews told viewers, “There are certain things in life you think you’ll never see. And then here it is. It’s happening right now.”
The new BAMS article is open access, now in early online release.
Active Hurricane Seasons: Maybe For 2020, But Not Necessarily in a Warmer Future
For a fifth consecutive year, NOAA is forecasting an above-average number of tropical cyclones (TCs) in the Atlantic, with 13-19 named storms expected in 2020. The number of TCs includes both tropical storms and hurricanes. This is in line with recent hurricane season forecasts by The Weather Channel, Penn State, Tropical Storm Risk, and others.
The recent spate of highly-active TC seasons, however, contrasts sharply with future trends in a majority of climate models, which simulate decreasing annual numbers of TCs as Earth’s climate continues to warm. That’s one of a number of findings in a recent paper by Tom Knutson (NOAA) and colleagues in the Bulletin of the American Meteorological Society.
In the paper, a team of tropical meteorology and hurricane experts led by Knutson assessed model projections of TCs in a world 2°C warmer than pre-industrial levels. The authors indicated mixed confidence in a downward TC frequency trend, even though 22 of 27 climate models the authors reviewed indicating the decrease. Some reputable models, though a minority, showed the frequency in named storms will instead increase in a warmer world, which lowered confidence in this particular finding.
As noted in Knutson et al. (2019, Part I of their two-part study: “Tropical Cyclones and Climate Change Assessment”), there is no clear observational evidence for a detectable human influence on historical global TC frequency. Therefore, there is no clear observational evidence to either support or refute the notion of decreased global TC frequency with climate warming. This apparent discrepancy between model projections and historical observations could be due to a number of factors. Among these are the relatively short available global TC records, the relatively modest expected sensitivity of global TC frequency to global warming since the 1970s, errors arising from limitations of model projections, differences between historical climate forcings and those used for twenty-first-century projections, or even observational limitations. However, the growing TC observational databases may soon provide a means of distinguishing between some highly divergent modeled scenarios of global TC frequency.
An average hurricane season in the Atlantic, which includes storms forming in the Caribbean Sea and Gulf of Mexico, sees 12 named storms with 6 becoming hurricanes. Of those hurricanes, typically three strengthen their sustained winds above 110 mph, becoming major hurricanes.
NOAA’s forecast cited warmer-than-usual sea surface temperatures, light winds aloft, and the lack of an El Niño, which tends to shear apart hurricanes, as factors for this year’s potentially active season. “Similar conditions have been producing more active seasons since the current high-activity era began in 1995,” NOAA stated in a release Thursday.
Knutson and his colleagues explain that the reason or reasons for a future decrease in TC frequency is uncertain, even as a warmer world would mean a continuation of warming seas. One possibility, the team entertains, is a decrease in large-scale rising air, termed “upward mass flux,” in the future. Its mechanism, however, is unclear, they find. Another is a reduction in saturation of the middle atmosphere in the models. Both are unfavorable for TC genesis.
The authors state that projections of TC frequency in different TC basins are “less robust” than the global signal. Comparing basins, they did find that the southwest Pacific and southern Indian oceans had greater TC decreases than the Atlantic and the Eastern and Western Pacific oceans.
They conclude this portion of the study stating that “reconciling projection results with theories or mechanistic understanding of TC genesis may eventually lead to improved confidence in projections of TC frequency.”
Knutson’s team found greater certainty in other facets of future TCs in the same study. For example, they expressed medium-to-high confidence that hurricanes will become stronger and wetter by the end of the twenty-first century.
New Assessment Is Confident Global Warming Brings Stronger, Wetter Tropical Cyclones
Even with a modest amount of global warming, future hurricanes will become nastier. They’ll push ashore higher storm surges, grow into superstorms like Hurricanes Dorian and Irma more often, and unleash inundating rains similar to Hurricanes Harvey and Florence more frequently.
That’s the assessment of published, peer-reviewed research in the past decade, according to an assessment by Thomas Knutson (NOAA) and colleagues, recently published in the Bulletin of the American Meteorological Society. It’s the second in a two part study conducted by the author team, 11 experts in climate and tropical cyclones (TCs). Part 1 found there are indeed already detectable changes in tropical cyclone activity attributable to human-caused climate change. Part 2, in the March 2020 BAMS online, project changes in the climatology of these storms worldwide due to human-induced global warming of just 2°C.
Highest confidence among the experts was in storm surge flooding. Rising sea levels due to warming and expanding oceans, responding to atmospheric warming and glacial ice melt, are already making it easier for hurricanes and even tropical storms to drive greater amounts of seawater ashore at landfall. And this will only worsen.
With CO2 levels climbing to about 414 ppm in March, as measured atop Mauna Loa in Hawaii, Earth is on track to reach a 2°C average global temperature increase by mid century. Already global average surface temperature has risen 1.2°C since the Industrial Revolution began.
In the assessment the authors have medium-to-high-confidence that rainfall rates in tropical cyclones will increase globally by 14% due to the increasing amount of water vapor available in a warmer atmosphere. They project a 5% global increase in tropical cyclone intensity along with an increase in the number of Category 4 and 5s ̶ although the range of opinions among the experts involved is 1-10%. In the Atlantic Basin, which includes the Caribbean Sea and Gulf of Mexico, the number of storms is projected to decrease while intensity as well as the number of intense hurricanes increases.
Other studies found that hurricanes will slow down, making them even more prolific rainmakers, among other changes. Authors of the new assessment discussed these additional changes, but cited less confidence in general and that different tropical basins around the world had different projections:
Author opinion was more mixed and confidence levels generally lower for some other TC projections, including a further poleward expansion of the latitude of maximum intensity of TCs in the western North Pacific basin, a decrease of global TC frequency, and an increase in the global frequency (as opposed to proportion) of very intense (category 4–5) TCs. The vast majority of modeling studies project decreasing global TC frequency (median of about −13% for 2°C of global warming), while a few studies project an increase. It is difficult to identify/quantify a robust consensus in projected changes in TC tracks across studies, although several project either poleward or eastward expansion of TC occurrence over the North Pacific. Projected TC size metric changes are on the order of 10% or less, and highly variable between basins and studies. Confidence in projections of TC translation speed is low due to the potential for data artifacts in the observed slowdown and a lack of model consensus. Confidence in various TC projections in general was lower at the individual basin scale than for the global average.
Observations without Fear: NOAA's Drones for Hurricane Hunting
Nowhere is it more dangerous to fly in a hurricane than right near the roiling surface of the ocean. These days, hurricane hunting aircraft wisely steer clear of this boundary layer, but as a result observations at the bottom of the atmosphere where we experience storms are scarce. Enter the one kind of plane that’s fearless about filling this observation gap: the drone.
NOAA’s hurricane hunter aircraft in recent storms has been experimenting with launching small unmanned aircraft systems (sUAS) into raging storms–and these devices show promise for informing advisories as well as improving numerical modeling.
The observations were made by a new type of sUAS, described in a recently published paper in BAMS, called the Coyote that flew below 1 km in hurricanes. Sampling winds, temperature, and humidity in this so-called planetary boundary layer (PBL), the expendable Coyotes flew as low as 136 m in wind speeds as high as 87 m s-1 (196 mph) and for as long as 40 minutes before crashing (as intended) into the ocean.
In the BAMS article, Joe Cione at al. describe the value of and uses for the low-level hurricane observations:
Such high-resolution measurements of winds and thermodynamic properties in strong hurricanes are rare below 2-km altitude and can provide insight into processes that influence hurricane intensity and intensity change. For example, these observations—collected in real time—can be used to quantify air-sea fluxes of latent and sensible heat, and momentum, which have uncertain values but are a key to hurricane maximum intensity and intensification rate.
Coyote was first deployed successfully in Hurricane Edouard (2014) from NOAA’s WP-3 Orion hurricane hunter aircraft. Recent Coyote sUAS deployments in Hurricanes Maria (2017) and Michael (2018) include the first direct measurements of turbulence properties at low levels (below 150 m) in a hurricane eyewall. In some instances the data, relayed in near real-time, were noted in National Hurricane Center advisories.
Turbulence processes in the PBL are also important for hurricane structure and intensification. Data collected by the Coyote can be used to evaluate hurricane forecasting tools, such as NOAA’s Hurricane Weather Research and Forecasting (HWRF) system. sUAS platforms offer a unique opportunity to collect additional measurements within hurricanes that are needed to improve physical PBL parameterization.
Images were captured from a video courtesy of Raytheon Corporation.
The authors write that during some flights instrument challenges occurred. For example:
thermodynamic data were unusable for roughly half of the missions. Because the aircraft are not recovered following each flight, the causes of these issues are unknown. New, improved instrument packages will include a multi-hole turbulence probe, improved thermodynamic and infrared sensors, and a laser or radar altimeter system to provide information on ocean waves and to more accurately measure the aircraft altitude.
Future uses of the sUAS could include targeting hurricane regions for observations where direct measurements are rare and models produce large uncertainty. Meanwhile, the article concludes, efforts are underway to increase sUAS payload capacity, battery life, and transmission range so that the NOAA P-3 need not loiter nearby.
Observations without Fear: NOAA’s Drones for Hurricane Hunting
Nowhere is it more dangerous to fly in a hurricane than right near the roiling surface of the ocean. These days, hurricane hunting aircraft wisely steer clear of this boundary layer, but as a result observations at the bottom of the atmosphere where we experience storms are scarce. Enter the one kind of plane that’s fearless about filling this observation gap: the drone.
NOAA’s hurricane hunter aircraft in recent storms has been experimenting with launching small unmanned aircraft systems (sUAS) into raging storms–and these devices show promise for informing advisories as well as improving numerical modeling.
The observations were made by a new type of sUAS, described in a recently published paper in BAMS, called the Coyote that flew below 1 km in hurricanes. Sampling winds, temperature, and humidity in this so-called planetary boundary layer (PBL), the expendable Coyotes flew as low as 136 m in wind speeds as high as 87 m s-1 (196 mph) and for as long as 40 minutes before crashing (as intended) into the ocean.
In the BAMS article, Joe Cione at al. describe the value of and uses for the low-level hurricane observations:
Such high-resolution measurements of winds and thermodynamic properties in strong hurricanes are rare below 2-km altitude and can provide insight into processes that influence hurricane intensity and intensity change. For example, these observations—collected in real time—can be used to quantify air-sea fluxes of latent and sensible heat, and momentum, which have uncertain values but are a key to hurricane maximum intensity and intensification rate.
Coyote was first deployed successfully in Hurricane Edouard (2014) from NOAA’s WP-3 Orion hurricane hunter aircraft. Recent Coyote sUAS deployments in Hurricanes Maria (2017) and Michael (2018) include the first direct measurements of turbulence properties at low levels (below 150 m) in a hurricane eyewall. In some instances the data, relayed in near real-time, were noted in National Hurricane Center advisories.
Turbulence processes in the PBL are also important for hurricane structure and intensification. Data collected by the Coyote can be used to evaluate hurricane forecasting tools, such as NOAA’s Hurricane Weather Research and Forecasting (HWRF) system. sUAS platforms offer a unique opportunity to collect additional measurements within hurricanes that are needed to improve physical PBL parameterization.
Images were captured from a video courtesy of Raytheon Corporation.
The authors write that during some flights instrument challenges occurred. For example:
thermodynamic data were unusable for roughly half of the missions. Because the aircraft are not recovered following each flight, the causes of these issues are unknown. New, improved instrument packages will include a multi-hole turbulence probe, improved thermodynamic and infrared sensors, and a laser or radar altimeter system to provide information on ocean waves and to more accurately measure the aircraft altitude.
Future uses of the sUAS could include targeting hurricane regions for observations where direct measurements are rare and models produce large uncertainty. Meanwhile, the article concludes, efforts are underway to increase sUAS payload capacity, battery life, and transmission range so that the NOAA P-3 need not loiter nearby.