Women of NSSL: Burkely T. Gallo

Burkely T. Gallo.
Burkely T. Gallo.

To celebrate Women’s History Month in March NOAA National Severe Storms Laboratory is publishing a series of stories highlighting some women working at the lab. One Q&A segment will be published each Monday in March.

Burkely T. Gallo is a Cooperative Institute for Mesoscale Meteorological Studies postdoctoral research associate working at NOAA’s National Severe Storms Laboratory. Gallo received her doctorate from the University of Oklahoma. Her work includes evaluating forecasts from convection-allowing models and using convection-allowing ensembles to create tornado forecasts. She has facilitated experiments in NOAA’s Hazardous Weather Testbed, where she tests these and other cutting-edge guidance from convection-allowing models.

Q: How did you get into your field?
A: I’ve been fascinated by the weather since I was little, particularly by thunderstorms and tornadoes. In fact, I used to be extremely scared of tornadoes and severe thunderstorms! That fear eventually turned into a desire to understand the atmosphere, which led me to research meteorology.

Q: What is it about your job that interests you?
A: In my job, I do research that is very operationally-focused, so I work closely with forecasters. By working with people who will use the guidance I develop, I know that I’m helping create better forecasts that could save lives. Plus, the weather is different every day, meaning that no two days of my job are exactly alike!

Q: Tell us about a project or accomplishment you consider to be the most significant in your career?
A: I’m still quite early in my career, but I am extremely involved in the annual Spring Forecasting Experiment in NOAA’s Hazardous Weather Testbed. The experiment brings together forecasters and researchers from around the world to test new model guidance and forecast tools in a real-time setting. This experiment is significant in that it facilitates important conversations between the research and operations communities, so that both groups can better understand each other and together produce improved severe weather forecasts.

Q: Tell us something that might surprise us about you.
A: I learned how to drive a stick shift on my parents’ farm when I was 10 years-old.

Q: What advice would you provide to up and coming meteorologists or others in your field?
A: Take advantage of even small opportunities that come your way, as you never know when they might lead to something much larger. All of my largest accomplishments seem to stem from small opportunities that I took advantage of at the time, even if they took some up-front effort beyond what I was already doing.

Q: What is the most memorable experience of your career?
A: Winning a National Science Foundation fellowship to fund my graduate education definitely sticks out in my memory. I had spent a lot of time and effort on the application, and I knew that the fellowship was very competitive and would enable me to study wherever I wanted, since it was applicable to most meteorology programs. The night that the results were announced, I woke up at around 3 am to check them and found out that I had won one.

Q: What is your personal philosophy?
A: Work hard, play hard, and always try to be empathetic and keep a positive attitude.

Q: Where is your favorite place to be?
A: Hiking, camping, or sitting around a campfire with my family and friends. If I had to pick a specific spot, I would say Cook Forest State Park in northwestern Pennsylvania.

Q: What does true leadership mean to you?
A: True leadership to me means a willingness to listen coupled with the ability to make difficult decisions and have a vision for the future that will benefit society. That way, leaders can guide people in the direction of progress while taking into account the unique circumstances affecting each individual.

Q: If you could do another job for just one day, what would it be?
A: I would probably be a Disney vacation planner. I love Disney World, organizing things, and helping people have fun, so helping people design their vacations so that they have the best experience possible sounds like a blast!

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Information analysis: social science adds needed piece to the weather puzzle

Research Scientist Jack Friedman with University of Oklahoma Center for Applied Social Research observes and works in the National Weather Forecast Office in Huntsville, Alabama. Friedman is one of the several social science researchers involved in the VORTEX-Southeast project spring 2017 experiment. (NOAA NSSL)

Increasing our knowledge of severe storms and improving the tools used to forecast them has been the singular mission of the NOAA National Severe Storms Laboratory since it was formed more than 50 years ago — until recently. Now NSSL researchers are expanding their focus to include people — how they receive, understand and interact with weather information.

A new report released this month by the National Academies of Sciences, Engineering and Medicine concludes that realizing the greatest return on investment from significant improvements in weather information will require a better understanding of how individuals, households and communities respond to weather forecasts, watches and warnings.

NSSL is already doing many of the recommendations mentioned in the report, said Kim Klockow, a research associate working at NSSL with the University of Oklahoma Cooperative Institute for Mesoscale Meteorological Studies. Dozens of researchers are integrating disciplines such as communication, psychology and education into the traditional meteorological research at NSSL.

“Meteorologists care about saving lives and property, and ultimately those goals depend on the actions people choose to take,” Klockow said. “Information is just one piece of the puzzle. Providing the public with information about possible dangers doesn’t stop the threats from having an impact, and it alone doesn’t motivate people to take action.

“In our research at NSSL, we have to account for the ways people understand what we’re saying, the things they’re able to do, and the things that motivate them.”

Klockow leads a new societal impacts group at NSSL created to ensure new technologies are useful and usable by the public, emergency managers and public broadcasters. Several recent projects are highlighted below.

Research in the Hazardous Weather Testbed

Each year, NSSL invites broadcast meteorologists, emergency managers and National Weather Service forecasters to the NOAA Hazardous Weather Testbed in Norman, Oklahoma, to test new technology developed at NSSL and within NOAA.

“Our research needs to engage those who will be using it,” Klockow said. “We have them test what our researchers have developed to see if they can use it, or will use it.”

Next year, the researchers plan to invite larger private sector companies to participate in testbed experiments. These forecasters may provide new insights, Klockow said.

The NOAA Hazardous Weather Testbed during the Spring 2017 experiment about the Geostationary Lighting Mapper. (Photo by James Murnan/ NOAA NSSL)

People’s responses to warnings
Recently, NSSL teamed up with OU’s Center for Risk and Crisis Management to analyze how the public receives and acts on weather warnings. This project, part of the broader Probability of What project, is to study the effectiveness of the current warning infrastructure. This information will help NSSL measure the impacts new technologies might have on the public.

“We are looking at providing more information between a watch and warning to fill the information gap and provide up to an hour of advanced notice for all kinds of severe weather,” Klockow said. “We need to know if it will be beneficial to people — if they will use that information — or if giving a slew of probabilities may be more difficult to understand.”

The POW research team is conducting nationwide surveys and small experiments to measure the public’s understanding of weather information.

Social science integral part of tornado study
How emergency managers and forecasters handle information during hazardous weather events is an important part of VORTEX-Southeast, a research program studying storms and tornadoes in the southeastern United States.

“VORTEX-SE is the first time social science has been integrated into a weather field campaign,” Klockow said. “When the physical science researchers deploy to the field, so do the social science researchers.”

Klockow said social scientists have embedded with local emergency managers and National Weather Service forecasters, studying how they receive information, process that information, and relay it to the public.

“We see if there are any information gaps, points of confusion, or breaks in the communication channels and how the process may be improved,” Klockow said.

Studying the latest technology
Part of informing the public about weather affecting them includes staying apprised of the latest and greatest technology. Klockow is researching the ATSC 3.0, a new television broadcast system offering more options, including advanced emergency alerts.

“It will fundamentally change the way TV works, so someone can point to the TV with their remote and get more detailed or local information during severe weather coverage,” Klockow said. “The viewer could pull up radar, probability plumes defined by NSSL research or timelines. This offers an amazing opportunity to get more information to the user. We have to make sure we are aware of this new technology and get it in sync with our research designs.”

Whether studying the structure of a thunderstorm, developing a new radar algorithm, improving a weather forecasting model, or analyzing the ways people receive weather information — every project at NSSL has at its heart the goal of minimizing the impacts of hazardous weather on society.

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International collaboration benefits US, European forecasters

NOAA National Severe Storms Laboratory Researcher Adam Clark at the European Severe Storms Laboratory Testbed this summer.

Weather doesn’t stop at borders. Nowhere is this more clear than in Europe, where two researchers working at the NOAA National Severe Storms Laboratory went shoulder to shoulder with researchers in the European Severe Storms Laboratory Testbed this summer. The goal was to collaborate on forecast products and learn how NSSL technologies are used abroad.

“As scientists and meteorologists, we need to continue to talk because that’s how true knowledge transfer occurs,” said Darrel Kingfield, University of Oklahoma Cooperative Institute for Mesoscale Meteorological Studies researcher working at NSSL. “ESSL researchers came to work with us in the NOAA Hazardous Weather Testbed a couple of years ago and this year we went to them.”

Darrel Kingfield presenting at the European Severe Storms Laboratory Testbed this summer.

During its sixth year, the ESSL Testbed program evaluated forecasts for high-impact weather. Like the HWT, the ESSL testbed serves as a forum to stimulate interaction between product developers and operational forecasters from throughout Europe. Also, lectures from several local and international experts help testbed participants enhance their knowledge and skills.

Different geography, systems

Kingfield and NSSL Research Scientist Adam Clark each spent a full week at ESSL’s testbed. What struck them was the difference in geography between the United States and Europe. Clark said ingredients needed for severe weather come together much differently in Europe than the U.S.

“You have the Mediterranean Sea and the Alps and that affects much of their weather,” Clark said.

Adam Clark working in the European Severe Storms Laboratory Testbed.

Along with geographical differences, Clark and Kingfield learned about the different weather prediction and monitoring systems operated by each European country. A variety of forecasting tools and methods are used throughout Europe, from government operated to privatized systems. This results in data, forecasting and verification inconsistencies.

“For example, after a tornado occurs in the U.S., officials observe and record where it occurred and how severe it was,” Kingfield explained. “Europeans rarely go out and assess tornado damage after a storm. Those surveys are reserved for most damaging events.”

As a result, Europe’s tornado database is not nearly as complete as the United States.

Sharing tools and techniques
While in the testbed, Kingfield and Clark gazed upon a few familiar products.

“The German Weather Service is using a lot of the same techniques developed at NSSL to interpret radar data,” Kingfield said. Some European meteorologists use several products developed in the U.S. by NSSL and OU CIMMS researchers. For instance, one technique allows them to use radar data to visualize the possible track of a tornado based on the storm’s rotation.

Collaboration is an important tool for forecasters and researchers. Participation in ESSL’s testbed allows researchers like Kingfield and Clark to share new technologies, experience new techniques and learn new systems. Opportunities like this allow researchers to collaborate on new products and technology, ultimately leading to better forecasts and warnings for the American public.

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Researchers evaluating lightning data in Hazardous Weather Testbed

For the first time ever, lightning data from a weather satellite is available and being evaluated in the NOAA Hazardous Weather Testbed.

Forecasters, researchers, product developers and broadcast journalists are analyzing recently available experimental data from an instrument on GOES-16, the newly launched NOAA satellite as part of the HWT Experimental Warning Program.

GOES-16, launched by NASA last November, scans the skies five times faster than NOAA’s current geostationary weather satellites and provides images at four times greater resolution.

The higher resolution allows forecasters to see more details in storm systems, particularly during periods of rapid strengthening or weakening. GOES-16 is also the first to carry a lightning detector in geostationary orbit.

The Geostationary Lightning Mapper observes total lightning, meaning in-cloud and cloud-to-ground lightning. GLM can help increase the accuracy of forecasts and warning times when combined with other forecaster tools.

The HWT EWP GOES-16 experiment just wrapped up its second of four weeks. Kristin Calhoun, CIMMS research scientist working at NSSL, said this is the first time forecasters have seen GLM data from GOES-16.

“We are here to test it and to contribute anything from ideas for data integration to training needs,” Calhoun said. “We want people to identify as many training gaps as possible.”

Bill Line, a meteorologist with the NOAA National Weather Service Pueblo forecast office, said if people like him learn to use GLM’s data, it will better his forecasts.

“These are new tools and we want to make sure forecasters are ready to use them,” he said. “There are many combinations of data and probabilities they haven’t looked at before.”

David Stark, a meteorologist with the NOAA National Weather Service New York forecast office, in the Hazardous Weather Testbed working with GLM data. (Photo by James Murnan/NOAA)

That is the purpose of the HWT – the facility allows end users to test new, experimental products before they are released to the NWS or other NOAA entities and partners.

“We’ve held similar experiments in the past but with proxy data,” Calhoun said. “This is the first year we are able to use real data. Ideally we will continue experiments like this, using real GOES-16 data, for years to come.”

David Stark, a meteorologist with the NWS New York forecast office, participated in the first week’s experiment. He described the experience as outstanding.

“Testing out some new products and helping fine tune them so they just aren’t thrown into the NWS is great,” he said. “To be able to see these tools and see the new research, while acting like I’m issuing warnings in an area gives me a good idea and feel of what I could be doing with this in real life and how it would enhance our current products.”

Stark said the product helps better show storm formations, providing the forecaster with a better idea of when and where a storm may form.

“This would add more confidence to my forecasts and allow me to focus more on increasing warning on possible life-threatening storms,” Stark said.

The GOES-16 experiment continues in the NOAA Hazardous Weather Testbed through July 21.

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Probabilistic Hazard Information experiment completes second week

The NOAA Hazardous Weather Testbed,  a joint project of the National Weather Service and the National Severe Storms Laboratory, is buzzing with activity again as the Experimental Warning Program focuses on its second of three years of testing probabilistic hazards with Hazard Services software. The objective is to improve severe weather warnings.

During severe storms, NOAA National Weather Service forecasters draw what is commonly referred to as a polygon around the storm to create warnings, said Gabe Garfield, National Weather Service HWT liaison and researcher with the University of Oklahoma Cooperative Institute for Mesoscale Meteorological Studies.

“When we issue warnings at the NWS it shows up as a polygon box,” Garfield said. “When a tornado passes, you’re still in the box and you may be unsure if you can leave your shelter. That’s an issue. Everywhere within the polygon has equal warning even though it’s not equally probable everyone is getting that severe weather.”

One focus of the EWP’s annual Spring Experiment is the Hazard Services – Probabilistic Hazard Information experiment, HS-PHI. The testbed allows users to test technologies and methods while providing input to see if it is ready to be implemented in forecast offices. The HS-PHI experiment is designed to test forecasters’ ability to provide probabilistic information about severe storms utilizing new software that is being designed to  be used in the future by the NWS. 

This experiment is part of the National Severe Storm Laboratory’s Forecasting a Continuum of Environmental Threats, FACETs, an initiative aimed at improving the communication of hail, wind, and tornado hazards to save lives and property.  Instead of a single polygon, in the FACETs paradigm forecasters would create probabilistic hazard information “plumes.” New types of severe weather warnings can be derived from the plumes. which new types of severe weather warnings can be derived.  These include the traditional warnings that the public receives today, to special warnings for specific users that have a lower tolerance to severe weather and require longer lead times to take action.

“Imagine you’re in a storm and the probability of severe weather at the center of the storm is 100 percent,” Garfield said. “There’s a circle around that 100 percent area but right outside there, it is 90 percent likely in the direction the storm is moving and then further out it may go down to 50 percent as it gets further away because we don’t know if it will weaken.”

As the storm moves, the circle around it moves, too. When that circle moves away from a location,  to know when the storm has passed over their location and they are able to come out of shelter.

“In the past, when the forecaster issued a polygon, the storm may change direction and the forecaster did not have any mechanism to update that without creating some confusion,” Garfield said. “But, with the probabilistic hazard information plumes, we can actually have that information and modify the plumes in real-time.”

For officials with responsibility for weather sensitive populations, such as festival organizers and hospitals, this means more lead time when severe storms threaten and better information to use in planning for severe storms.

“The whole idea is to provide as much information as possible,” Garfield said. The purpose of HS-PHI is to develop and test a tool forecasters can use to convey the threat. The first version of this prototype was evaluated in the HWT in 2014.  The features of the prototype have been incorporated into the NWS version, and testing of this operational version, HS-PHI, is in its second year.

“As you might imagine, if you have one of the plumes, it would be really hard to always manually draw those probabilities in real-time, particularly if you have several severe storms going on at once,” Garfield said. “You won’t have enough time to manually resize all of these swaths. They’ve been trying to figure out the best machine automation versus human interaction. What’s the best algorithm used along with how much should humans actually tweak in the system?”

The EWP is testing experimental methods for improving the communication of severe weather threats, such as hail, wind, and tornadoes, using new software designed for the computer workstations that NWS meteorologists use today to forecast the weather.

This year, the HS-PHI Experiment is testing the probabilistic hazard information concept in a way that simulates how NWS forecasters would actually use it, within the Advanced Weather Interactive Processing System (AWIPS) software used by the NWS. NWS forecasters and human factors experts will evaluate the software design using several severe weather scenarios.

HS-PHI was developed by the National Severe Storms Laboratory with the National Weather Service and OAR’s Earth System Research Lab, and is in its second year of evaluation.

For more information, visit https://hwt.nssl.noaa.gov/ and http://www.nssl.noaa.gov/projects/facets/.

HWT EWP spring experiment HS-PHI in April 2017

 

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During busiest month for storms, researchers gather in the NOAA Hazardous Weather Testbed

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This week, during the height of severe weather season, a diverse group of scientists is coming together in Norman, Oklahoma, to improve how severe weather information is conveyed to the public. They are gathering in NOAA’s Hazardous Weather Testbed to focus on FACETs-related research and significant collaborative efforts.

The HWT is a joint effort between the National Severe Storms Laboratory, Storm Prediction Center, and the National Weather Service, along with OU’s Cooperative Institute for Mesoscale Meteorological Studies, that aims to develop, test, and evaluate forecast and warning techniques. Each year, the HWT conducts two programs during the spring to review emerging ideas and answer the question, “What do forecasters need?” The Experimental Warning Program and Experimental Forecast Program draw as many as 60 researchers and forecasters together for six to eight weeks from April to June.

While experiments formally began earlier this spring, this week is particularly noteworthy because many aspects of the future warning paradigm have been brought together for the first time. NWS forecasters, emergency managers, broadcast meteorologists, social and behavioral scientists, and research meteorologists are looking at NWS Hazard Simplification concepts, new science (e.g., Warn-on-Forecast model guidance, lightning prediction tools, storm-scale prediction, etc.), and more. With all of these groups involved in the FACETs experimental phase, researchers hope to gain insight on how they might devise a better warning system for the entire nation.

Additionally in the HWT, scientists are examining real-time forecasts with an early prototype Warn-on-Forecast system known as the NSSL Experimental WoF System for ensembles (NEWS-e). Early results appear promising, and researchers are enthusiastic about future prospects. NEWS-e’s forecasts for the severe weather events on May 8-9, 2016 were remarkably good.  On both days, the forecasts identified a number of dangerous storms with more than 20 minutes of lead time. The NEWS-e system now combines models from NOAA’s Global Systems Division and NSSL for the first time. This marks a significant milestone in the collaboration on storm-scale numerical weather prediction between the two labs.

For more information about the HWT: http://hwt.nssl.noaa.gov/.

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Technology Converging on Early Prototype Merged National HRRR Ensemble and “Warn-on-Forecast” System for High-impact Weather

750500c536EDNmainHRRRE Updraft helicityAn early prototype of a high-impact weather forecast system will get a real-time demonstration in the NOAA Hazardous Weather Testbed (HWT) this spring. This “Warn-On-Forecast” using a new HRRR-ensemble system will ultimately produce forecasts that define the probability of a weather hazard occurring, quantify the confidence in its path, and adjust to trends in the threat level based on new observations. This work combines the best technologies from NOAA’s Earth System Research Laboratory (ESRL)/Global Systems Division (GSD) and NOAA’s National Severe Storms Laboratory (NSSL).

From May 2 to June 3 in the NOAA Hazardous Weather Testbed in Norman, Oklahoma, more than 80 forecasters, researchers, and model developers will use this “state of the art” system, gain experience with software and workflows, and help developers identify its strengths and weaknesses. This is a significant step towards the National Weather Service (NWS) strategy of Forecasting a Continuum of Environmental Threats (FACETs) at ultra-high resolutions. Scientists hope to have a national HRRR ensemble system in operations later this decade and a WoF system in operations by 2023.

The foundation of the WoF prototype is ESRL/GSD’s experimental hourly-updating High-Resolution Rapid Refresh–Ensemble (HRRRE) regional analysis and prediction system. To start HRRRE with the current weather, the system uses special techniques to bring surface, aircraft, and other observations into the early stages of the model run. HRRRE then produces multiple forecast scenarios out to 15 hours, all starting with slightly different initial conditions, to produce hourly snapshots of possible weather conditions. HRRRE cycles every hour to merge the forecast models with real-time data and bring small-scale storm structure into focus.

HRRRE predictions will then be the starting point for the prototype sub-3km 0-1 hour NSSL Warn on Forecast System for Ensembles (NEWS-e). NEWS-e will ingest radar and cloud data at 15-minute intervals to produce frequent 90-minute forecasts of thunderstorms. Researchers are working to make these very short-range probabilistic forecasts accurately predict storm-scale hazards such as low-level rotation in supercell thunderstorms, thunderstorm winds, damaging large hail, and flash flooding.

The NOAA HWT Spring Forecasting Experiment is organized every year by NSSL and the NOAA Storm Prediction Center to test emerging concepts and technologies to improve predictions of hazardous convective weather. This year’s participants include the NOAA NWS, the NWS Weather Prediction Center, ESRL/GSD, the NOAA Environmental Modeling Center, the Aviation Weather Center, the National Center for Atmospheric Research, the Cooperative Institute for Research in Environmental Sciences at the University of Colorado Boulder, the Center for the Analysis and Prediction of Storms, the University of Oklahoma School of Meteorology, the Cooperative Institute for Mesoscale Meteorological Studies, and other university and international partners.

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NOAA Hazardous Weather Testbed Spring Activities Kick Off April 18

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The 2016 NOAA Hazardous Weather Testbed Spring Experiment will kick off on Monday, April 18. During the course of the experiment, meteorologists from across the United States will come to Norman, Oklahoma, to develop, test, and evaluate severe weather forecast and warning techniques with researchers at NOAA’s National Severe Storms Laboratory and the NOAA National Weather Service Storm Prediction Center.

Each year, the HWT conducts two programs during the spring to review emerging ideas and answer the question, “What do forecasters need?” The Experimental Warning Program and Experimental Forecast Program draw as many as 60 researchers and forecasters together for six to eight weeks from April to June. Emergency managers and broadcasters are also involved in the research.

The 2016 Spring Experiment will include four major projects, co-organized by NSSL and SPC. First, the GOES-R experiment will prepare forecasters to use data from NOAA’s next generation of geostationary weather satellites. Three NWS forecasters and one broadcaster will participate each week. Next, two different experiments will test the early concepts of FACETs with the newly designed Probabilistic Hazards Information tool. The Hazards Services-PHI experiment will include two NWS forecasters each week, evaluating software design using archive and real-time data. In the PHI-Prototype Experiment, three NWS forecasters per week will create probabilistic forecasts for severe convective hazards using the PHI tool. Finally, in late June, the Hydro experiment, part of the Hydrometeorological Testbed, will continue its focus on flash flood watches and warnings, with five forecasters participating during each segment of its three-week run.

Dates for the 2016 Hazardous Weather Testbed experiments are as follows:
April 18-22 GOES-R
April 25-29 GOES-R
May 2-6 GOES-R, Hazard Services-PHI
May 9-13 GOES-R, PHI – Prototype
May 16-20 Hazard Services-PHI
May 23-27 PHI- Prototype
May 31-June 4 Hazard Services-PHI
June 6-10 PHI – Prototype
June 20-24 Hydro
June 27-July 1 Hydro
July 11-15 Hydro

Members of the press are invited to attend a media day at 10 a.m. April 14 to learn more about these projects. More information about the HWT is available on our newly redesigned web page: http://hwt.nssl.noaa.gov/.

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Significant Paper: Evaluation of a Probabilistic Forecasting Methodology for Severe Convective Weather in the 2014 Hazardous Weather Testbed

PHI Evaluation of a Probabilistic Forecasting Methodology for Severe Convective Weather in the 2014 Hazardous Weather Testbed
Authors: Chris Karstens, Greg Stumpf, Chen Ling, Lesheng Hua, Darrel Kingfield, Travis Smith, James Correia Jr., Kristin Calhoun, Kiel Ortega, Chris Melick, Lans Rothfusz

Journal: Weather and Forecasting
Publication Date: Online 12/2015

Important Conclusions:
This paper establishes a methodology for creating Probabilistic Hazard Information and describes an evaluation of this methodology conducted with researchers and forecasters in the NOAA Hazardous Weather Testbed. Forecasters were able to quickly adapt to the new tools and concepts and ultimately produced probabilistic hazard information in a timely manner. The probabilistic forecasts from two severe hail events tested in a control–test experiment were more skillful than storm-based warnings and were found to have reliability in the low-probability spectrum. False alarm area decreased while the traditional verification metrics degraded with increasing probability thresholds. The latter finding is attributable to a limitation in applying the current verification methodology to probabilistic forecasts. Relaxation of on-the-fence decisions exposed a need to provide information for hazard areas below the decision-point thresholds of current warnings. Automated guidance information was helpful in combating potential workload issues, and forecasters raised a need for improved guidance and training to inform consistent and reliable forecasts.

The methodology by which the findings were derived in this study was of equal importance to the findings themselves. NOAA’s National Severe Storms Laboratory is demonstrating to the NWS that NSSL is cautious, thorough, and scientific in development of the FACETs tools.

Significance:
This paper describes a proposed methodology for issuing Probabilistic Hazard Information for severe convective weather, as opposed to the warnings issued by the National Weather Service today. Additionally, the findings from the Hazardous Weather Testbed experiments are summarized, along with descriptions of how this process has informed ongoing and future development.

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Hydrometeorological Testbed 2015

During the week of July 20-24, six forecasters from NWS offices nationwide joined NSSL and CIMMS researchers for the final week of the Hydrometeorological Testbed. This project was supported by JJ Gourley, Steve Martinaitis, Race Clark and Zac Flamig.

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During the week, the forecasters issued experimental watches and warnings for hydrologic extremes in real-time, with the objective of improving flash flood guidance. This project leveraged opportunities for collaboration with two other NSSL research programs, the Severe Hazards Analysis and Verification Experiment (SHAVE) and the Meteorological Phenomenon Identification Near the Ground (mPING).

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The purpose of the HMT was to evaluate the skills of the NSSL-designed FLASH suite of products in flash flood forecasting and, ultimately, to enhance understanding of short-term flash flood forecasting challenges. The meteorologists shared their findings in a “Tales from the Testbed” teleconference held at the end of the week, highlighting the difficulties and successes they encountered when applying FLASH products in various weather scenarios. Notably, they found that it is beneficial to have soil moisture products available when considering flash flood watch and warning issuance. Overall, they determined the new FLASH products to be an improvement in operational capabilities that will lead to more accurate and timely decision-making.

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