Gab at the Lab: Charles Kuster

Charles Kuster, Research Scientist (OU CIMMS)


Background:M.S. Meteorology, University of Oklahoma (2014)
B.S. Meteorology, University of Oklahoma (2012)
Experience:Charles grew up in Leadville, Colorado, where, at an altitude of 10,152 feet, he might see snow any month of the year. That’s why, he says, he will never complain about a hot Oklahoma summer! After high school graduation, he briefly attended both the University of Nebraska and Colorado State University. At Colorado State, he was a physics major, but always knew he wanted to earn a degree in meteorology. This led him to the University of Oklahoma, where he completed his bachelor’s degree in 2012 and eventually his Master’s in 2014. Charles was a Graduate Research Assistant with OU CIMMS before securing a position as Research Associate in January of this year.
What He Does:Charles is part of the Radar Research and Development Division within NSSL. His work focuses on rapidly-updating radar data. He and others are examining Phased Array Radar to learn how scans of approximately one minute can provide greater insight to forecasters and emergency managers on the front lines in severe weather situations. Charles played an instrumental role in supporting the Phased Array Radar Innovative Sensing Experiment, which took place earlier this year. Along with NSSL’s Pam Heinselman and OU CIMMS’ Katie Bowden, he worked with teams of National Weather Service forecasters to study the benefits of Phase Array Radar in an operational setting.
Trivia: Charles enjoys photography, ultimate frisbee, and watching college football. He and his wife, Emma, were married in 2014.
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Eye Tracking Technology at NSSL

Have you heard about eye tracking? This burgeoning technology has become increasingly important to the work we do here at NSSL. Our researchers are leveraging opportunities to use eye tracking to analyze forecaster decision-making and improve awareness in various meteorological scenarios.

eye-tracking-1Michigan State University researcher Robert Drost applied the concept in 2013 to analyze the gestures of broadcast meteorologists and the effect on viewers’ attention. Eye tracking has since been used in several other studies.

NSSL scientists first used this technology to study how forecasters analyzed Phased Array Radar data, updating every minute. Realizing the utility of the eye tracking information, researchers were motivated to incorporate these tests into the 2015 Phased Array Radar Innovative Sensing Experiment. In this study, principal investigators Pam Heinselman (NSSL) and Katie Bowden (OU CIMMS researcher, working with NSSL) used eye tracking technology to examine the decision-making process of National Weather Service forecasters from around the country. The eye gaze data of the forecasters was collected as they studied radar data, providing insight into their thought process and focus.

CIMMS/NSSL scientist Elizabeth Argyle, in collaboration with NSSL’s JJ Gourley and CIMMS/NSSL’s Zac Flamig, uses eye tracking to study how a type of decision-making support tool for flash floods called recommenders affect a forecaster’s situational awareness of the overall meteorological situation. This type of feedback will help us develop useful tools and training for forecasters, resulting in improved warning for you when severe weather strikes!


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Gab at the Lab: Pam Heinselman

Pam HeinselmanPam Heinselman came to the NOAA National Severe Storms Laboratory in 1995 as a scientist with the University of Oklahoma’s Cooperative Institute for Mesoscale Meteorological Studies. She grew up in Westminster, Maryland, and completed her meteorological studies at the University of Saint Louis. After joining CIMMS and living in Norman for several years, she made the decision to continue her education and pursue a Ph.D. at OU. Pam was awarded her Ph.D. in May of 2004. Five years later, in 2009, she became a full-time NOAA employee, and she has continued to make important contributions to the Lab in this role.

Heinselman is the leader of the phased array radar and meteorological studies team. She coordinates the Phased Array Radar Innovative Sensing Experiment with OU PhD student Katie Bowden, who is funded through the OU Cooperative Institute for Mesoscale Meteorological Studies. PARISE is conducted through the NOAA Hazardous Weather Testbed, and investigates scientific and operational applications of rapid-scan data sampled by NSSL’s phased array radar. This research improves understanding of hazardous weather and develops methods to use rapid-scan radar data in forecasting operations

In her personal time, Pam enjoys exercising outdoors and especially looks forward to trips home to the East Coast, where she can dine on her favorite Maryland crab cakes. She also enjoys the company of her dog, Rolli.

We’re glad to have Pam here at NSSL!

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Read more about Pam’s research here.

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2015 PARISE Experiment

This week, researchers from NOAA’s National Severe Storms Laboratory will launch the 2015 Phased Array Radar Innovative Sensing Experiment to assess the impacts of rapidly updating radar data on forecasters’ warning decision performance. The project will be carried out over the course of six weeks, and will conclude on September 25.

As in previous years, NSSL Research Scientist Dr. Pam Heinselman and CIMMS Researcher Katie Bowden will take the lead on the experiment. They will be working with NOAA National Weather Service forecasters to produce timelines of the warning decision process. Later they will analyze these timelines to determine the situational awareness attained from phased array radar data and how that information was used in warning decisions. The experiment will be conducted in three parts.

The first segment of 2015 PARISE will be conducted like a traditional experiment, according to Heinselman. Thirty National Weather Service forecasters from across the Great Plains region will be assembled to study nine archived cases. These cases will be worked in simulated real-time, using one-, two-, or five- minute phased array radar updates. The forecasters will determine whether or not to warn, based on the situational awareness gained from the radar data. Upon completion of each study, they will provide a detailed account of their warning decision process and overall workload. With more participants and additional case studies this year, the results are expected to be an improvement over previous experiments.

New this year will be the use of eye-tracking technology to better understand the decision-making processes of the forecasters. Eye-tracking technology has been successfully used for analysis in healthcare, air traffic control, and other human-computer interactions. Data pertaining to eye gaze will be gathered from each of the 30 forecasters while they are working on PAR case studies. Analysis of this data is expected to illustrate how update timelines impact forecasters’ decisions.

Eye-tracking technology used in PARISE will help NSSL researchers determine how forecasters use phased array radar data to make decisions.

On the final day of PARISE, researchers will conduct a focus group aimed at generating insightful feedback. Forecasters will have the opportunity to share new ideas that will help shape the future of the PAR network. As radar continues to develop and forecasting resources are enhanced, National Weather Service meteorologists will be better equipped to warn the public of impending severe weather. This, in turn, will support the NWS objective to protect life and property and will help to build a Weather Ready Nation.

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Impacts of Phased Array Radar Data on Forecaster Performance during Severe Hail and Wind Events

Early online release 1/13/15
Journal: Weather and Forecasting
Impacts of Phased Array Radar Data on Forecaster Performance during Severe Hail and Wind Events

Katie A. Bowden, Pamela L. Heinselman, Darrel M. Kingfield, and Rick P. Thomas

Summary:  Twelve National Weather Service (NWS) forecasters participated in the Phased Array Innovative Sensing Experiment (PARISE) 2013 and were assigned to either a control (5-min radar data updates) or experimental (1-min radar data updates) group. Each group worked a marginally severe hail event and a severe hail and wind event in simulated real time. While working each event, participants made warning decisions regarding the detection, identification, and re-indentification of severe weather, now known as “the compound warning decision process.”

Important conclusions:  The experimental group’s performance exceeded that of the control group’s, as demonstrated through their significantly longer median warning lead time, as well as superior probability of detection and false alarm ratio scores. The experimental group also had a larger proportion of mastery decisions (i.e., confident and correct) than the control group, possibly because of their enhanced ability to observe and track individual storm characteristics through the use of 1-min updates.

Significance:  This work furthers efforts that have already been made to understand the impact of higher-temporal resolution radar data, as provided by PAR, on the warning decision process of NWS forecasters. The research questions, methodology, and analysis presented in this paper build upon the findings presented from earlier PARISE work, while also sharing findings that are of a new nature.

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2013 NOAA National Weather Radar Testbed Spring Experiments

Lowering west of PAR, 2006During the 2013 central Oklahoma severe weather season, researchers will demonstrate and evaluate new capabilities developed for the NOAA National Weather Radar Testbed Phased Array Radar (NWRT/PAR). The most recent software upgrade, released in March 2013 provides new automated storm detection, tracking and scheduled scanning capabilities for NWRT/PAR.

Researchers will target storms within 120nm of NWRT/PAR to examine the strengths and limitations of storm cluster identification and tracking algorithms, and their usefulness for enhanced rapid sampling of severe storms. They will also use the data to understand how a thunderstorm evolves into a supercell and as it begins to produce a downburst or possible tornado. Researchers will evaluate how useful this information could be for enhanced warning lead-time during severe weather warning operations.

In addition, NSSL will work with 12 National Weather Service forecasters during six weeks in May, June, and July. They will assess how the use of rapid-scan NWRT/PAR helps with situational awareness and warning decisions during simulated severe weather events.

New this year, NSSL’s dual-pol research radar will be used as a proxy for future dual-pol Multi-function Phased Array Radar (MPAR) observations. Researchers will observe rapid changes in dual-pol signatures that occur in cyclic supercells and downbursts.

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Phased array radar Spring 2012 projects

The NOAA National Weather Radar Testbed Multi-function Phased Array Radar will support three experiments with data collection during the spring of 2012 as part of the National Severe Storms Laboratory (NSSL) Phased Array Radar Innovative Sensing Experiment (PARISE).

The Severe Weather Outbreak Study is a NOAA NSSL program to determine the importance of rapid and adaptive scanning from MPAR in the depiction and understanding of weather events with potential for significant societal impacts. The research field phase is from April 14 – June 15 2012 over the MPAR domain (defined as significant weather sampled within 120 km of MPAR).   The main focus of this study to sample rare significant events such as tornado outbreaks.

NSSL will partner with MIT/Lincoln Labs and the FAA on the Multi-function Phased Array Radar’s (MPAR) Wind-Shear Detection Capability Assessment Experiment from April 16 – June 15, 2012.  Low-altitude wind shear is a deadly threat to aircraft during landing and takeoff and its accurate and timely detection near airports is critical.  Microbursts, in particular, are fairly small and evolve rapidly.  There are 45 Terminal Doppler Weather Radars (TDWR) currently serving U.S. airports. MPAR’s have the potential to replace TDWRs at the end of their life cycle, provided they can effectively detect wind shear.  Researchers will compare radar data from the Oklahoma City TDWR with data from the NOAA MPAR.

The Deep Convective Clouds and Chemistry (DC3) experiment will explore the role of the thunderstorm updrafts in carrying electrically charged particles, water vapor and other chemicals to the upper parts of our atmosphere.  Scientists from more than two dozen organizations will use research aircraft, mobile radars, lightning mapping arrays and other tools to make measurements that will help scientists understand more about the electrical and chemical structure of thunderstorms, including the concentration of ozone.  DC3 will focus on Alabama, Colorado and Oklahoma, but when thunderstorms are within 120 km of the Multi-function Phased Array Radar in central Oklahoma, teams will coordinate data collection. The project runs from May 15 –  June 30, 2012 with funding from the National Science Foundation (NSF), National Oceanic and Atmospheric Administration (NOAA), and NASA.

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PAR Captures Long-lived Tornado in May 24, 2011 Outbreak

The tornado outbreak forecasted by the NOAA Storm Prediction Center and the National Weather Service Forecast Office in Norman, Oklahoma became a reality as five damage-producing tornadoes struck central Oklahoma between 3 pm and 7 pm CDT May 24, 2011. The longest-track tornado, rated EF3 by the Norman Forecast office, damaged homes and businesses along its 75-mile path that originated just northwest of Binger and moved through the towns of El Reno, Peidmont, and Guthrie (Fig. 1).

Tornado tracks from central Oklahoma tornado outbreak May 24, 2011
Figure 1. Preliminary tornado tracks for the May 24, 2011 tornado outbreak. (Source:

The rapid-scan, S-band phased-array radar (PAR), located within the National Weather Radar Testbed in Norman, Oklahoma, sampled this tornadic supercell every 1 minute. Based on PAR data, by 3:30 pm supercell storm formed its first well-defined hook echo and associated tornado vortex signature about 6 miles west of Binger (TVS; Fig. 2). At this time, PAR data show that the TVS had a maximum gate-to-gate velocity difference of 89 mph. A comparison of PAR velocity data with the damage path shows that the tornado formed about 12 minutes later, at 3:40 pm.

PAR shows strong signs of tornado development. (Image courtesy Pam Heinselman, NSSL)
Figure 2. Based on PAR data, by 3:30 pm supercell storm formed its first well-defined hook echo and associated tornado vortex signature about 6 miles west of Binger.

The 1-minute updates of the PAR exhibit many important details about the evolution of this supercell and its long-lived tornado. One example is the hard-right turn of the TVS and hook at 4:15 pm that placed El Reno in the tornado’s destructive path (Fig. 3 ~62 km northeast of PAR). About 10 min later (4:25 pm, west-side of El Reno), as cells approaching from the southeast began to merge with the hook and a new circulation developed, the hook’s motion was redirected to the northeast, toward Piedmont. Fig. 3 also shows the likely development of two “debris” signatures in the radar reflectivity, which are compact regions of high reflectivity values due to debris from the tornado.

Animated gif of PAR reflectivity and velocity displays
Figure 3. The 1-minute updates of the PAR exhibit many important details about the evolution of this supercell and its long-lived tornado.

This example shows the PAR’s capability to provide timely, detailed information about where a tornadic storm is headed, and its intensity. In the future, this PAR capability may give families the few additional minutes they may need to take cover from destructive storms.

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New enhanced radar scanning strategy to be tested

Efficient sampling of storms is a critical need for forecasters in severe weather warning situations. Phased array radar technology, with its electronically steered beam, has the potential to meet this need by giving users the ability to control how, when, and where the radar scans.  This means the radar can be directed to focus its beam only where storms are detected, without the mechanical inertia associated with rotating a parabolic antenna. Focused observations of storms lead to faster updates since the radar does not waste time scanning clear-air regions.

NSSL/CIMMS researchers developed the Adaptive Digital signal processing Algorithm for PAR Timely Scans (ADAPTS) to take advantage of this ability by “turning on” or “turning off” individual beam positions based on storm continuity, coverage and significance.  ADAPTS also includes criteria to continuously monitor low-altitude developments and follow storm movement and growth.

The original prototype was tested during the spring of 2009 and demonstrated significant performance improvement leading to reduced observation update times.

“The new ADAPTS II prototype has been enhanced to allow the user to define scanning strategies for different weather situations, rather than pre-set general scanning strategies used in the original version,” says NSSL/CIMMS researcher Sebastian Torres, leader of the National Weather Radar Testbed (NWRT) Software and Signal Processing Upgrades project.

Testing of the ADAPTS algorithm using the National Weather Radar Testbed begins on April 12. Researchers believe they will see even faster updates than before, which could help make severe weather warnings more accurate and timely.

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NSSL prepares for first study of operational impacts of faster radar data

Photo the NWRT courtesy of Mark Benner

One question driving research with the Phased Array Radar (PAR) is whether faster data updates will increase warning lead time.  To begin answering this question, NSSL will conduct the first experiment to directly compare how forecasters issue warnings based on data provided at current radar update rates, with warnings issued based on faster data updates provided by Phased Array Radar (PAR) technology.

The project is part of the 2010 Phased Array Radar Innovative Sensing Experiment (PARISE) beginning the second week in April.

Teams of forecasters will use two different PAR data sets.  One will be with the fast update time typical of the PAR, and the other will be PAR data, but updated at the WSR-88D rate.

“This gives us a basis from which we can compare warning lead times – no differences in data, just update time and the warning decision process used by each team,” says Pam Heinselman, research meteorologist at NSSL and a leader of the project.

This will be a meaningful study with the warning lead-time and warning decision process examined from a direct radar comparison.

Since 2007, NSSL has invited NWS forecasters to participate in experiments designed to demonstrate and provide user feedback on PAR weather surveillance capabilities.  The evaluations of PAR data given by previous participants have positively impacted PAR research and development.

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