Flash floods — raging torrents of water caused by heavy rainfall and overtopped rivers and streams — can become deadly in a matter of minutes.
Now, a new forecasting tool is helping NOAA National Weather Service forecasters predict when and where these devastating events will occur.
Developed by researchers at NOAA’s National Severe Storms Laboratory and its partners, FLASH — short for the Flooded Locations and Simulated Hydrographs Project — combines real-time rainfall estimates with real-time surface models to supply forecasters better information and more confidence with which to issue flood warnings.
How it works FLASH gathers rainfall data from multiple radars, combines it with information about the type of surface where rain is falling and creates a highly detailed forecast for when specific rivers and streams will flood and by how much. FLASH also provides historical context, helping forecasters communicate the significance of a predicted flash flood.
FLASH was tested by researchers and NWS forecasters during the HMT-Hydro testbed experiments from 2014-2016, allowing the product to be fine-tuned.
FLASH is being reframed into a fully probabilistic framework called Pro-FLASH. This consideration of uncertainty in the modeling process accommodates forcings from ensemble precipitation forecasts.
Such can increase the lead time with the distributed hydrologic forecasts, but must consider the associated uncertainties with the forcings. We are also developing FLASH products for the outer-continental United States domains including Alaska, Hawaii, Guam, and the Caribbean.
Many members of the NWA fondly recall longtime associate Ron Przybylinski, a luminary in operationally-focused severe weather research for more than a quarter century. When Ron passed away in March 2015, a number of friends and colleagues within our association sought to honor his legacy of research-to- operations integration. The result was the first Research Operations Nexus (RON) Meetup, held at the 2015 NWA Annual Meeting in Oklahoma City in memory of Ron and his work.
The first RON meetup was a special session on Sunday night at the start of the conference, bringing together researchers and operational forecasters in a forum where they could discuss topics of mutual interest. Nearly 70 meteorologists participated in the event, breaking into groups to discuss topics like communicating uncertainty and impacts, flash flooding and heavy precipitation, use of social media in operations, and fire weather support. The sessions were structured to connect challenges being faced by operational forecasters with work being done by the research community, and to start collaborative relationships that might continue in the future.
Given the success of the RON in Oklahoma City, a second meetup has been scheduled for the upcoming 2016 NWA Annual Meeting in Norfolk. This year’s event will be held Sunday, September 11th, from 7 to 9 pm in room Marriott IV of the conference hotel. We hope you can and will make plans to attend. If you have suggestions for topics to be covered or would like more information, please contact Greg Stumpf at Greg.Stumpf@noaa.gov.
Experiments designed to improve National Weather Service severe weather forecasts will be conducted in the 2015 Spring Forecasting Experiment from May 4 through June 5, part of the NOAA Hazardous Weather Testbed (HWT) Experimental Forecast Program. The effort is a joint project between the Storm Prediction Center (SPC) and NSSL/CIMMS to support NOAA’s goal to evolve the National Weather Service and build a Weather-Ready Nation. The interactions between operational forecasters, model developers, and research scientists are critical for the effective transfer of operationally relevant guidance, tools, and techniques to operational forecasters.
Forecast teams will work with a number of sets of advanced weather computer models, called ensembles, that can depict thunderstorms (4km grid or less) to create experimental severe weather hazard outlooks valid over shorter periods (1-hr and 4-hr periods) than current SPC operational products. The outlooks will define the probability of a hazard occurring, the confidence in its path, and adjust to trends in the threat level based on new observations. These activities are foundational to the emerging FACETs vision and designed to link with initial Warn on Forecast activities conducted by the Experimental Warning Program. In addition, the predictability of severe weather hazards into Days 2 and 3 will be explored using these ultra-high-resolution forecast systems.
The HWT experiments support the NOAA mission of Science, Service, and Stewardship, in addition to providing information that will help communities be more resilient. HWT research will improve the nation’s forecasting and numerical weather prediction capabilities through collaborative efforts between the academic community and NSSL. The effort is highly relevant to NOAA’s goal to evolve the National Weather Service.
Several experiments to improve National Weather Service severe weather warnings will be conducted this spring in the NOAA Hazardous Weather Testbed (HWT) as part of the annual Experimental Warning Program, a joint project of the National Weather Service and NSSL/CIMMS to support NOAA’s goal to evolve the National Weather Service and build a Weather-Ready Nation. The EWP’s Spring Warning Project will run from May 4 through June 12, and provides a conceptual framework and a physical space to foster collaboration between research and operations to test and evaluate emerging technologies and science.
Forecasters will evaluate an updated Lightning Jump Algorithm (LJA), based on the GOES-R Geostationary Lightning Mapper, that was enhanced based on feedback from forecasters participating in the 2014 program. In severe storms, rapid increases in lightning flash rate, or “lightning jumps,” typically precede severe weather such as tornadoes, hail, and straight line winds at the surface by tens of minutes. These evaluations will help prepare for possible operational implementation in 2016 following the launch of GOES-R.
Earth Networks’ total lightning and total lightning derived products, including storm-based flash rates tracks, time-series, and three levels of thunderstorm alerts will be evaluated in real time, building upon the initial evaluation in 2014. The 2015 evaluation will test the feasibility of use and performance under the stress of real-time warning operations.
A new set of high-resolution Weather Research and Forecasting (WRF) models will serve as a prototype for developing the “Warn-on-Forecast” warning paradigm. Feedback from this project will go into developing new model tools capable of managing the large amounts of model information associated with future forecast systems.
During three weeks of the experiment, forecasters will assess a new tool using rapidly-updating high-resolution gridded Probabilistic Hazard Information (PHI) as the basis for next-generation severe weather warnings. This experiment is part of a broad effort to revitalize the NWS watch/warning paradigm known as Forecasting a Continuum of Environmental Threats (FACETs). The major emphasis of the HWT PHI experiment will be on initial testing of concepts related to human-computer interaction while generating short-fused high-impact Probabilistic Hazard Information for severe weather. The long-term goal of this effort is to migrate the refined concepts and methodologies that result from this experiment into Hazard Services, the next generation warning tool for the NWS, for further testing and evaluation in the HWT prior to operational deployment.
This year will mark the inaugural HWT Experiment with Emergency Managers. The EMs will be provide feedback on their interpretation of experimental probabilistic forecasts generated in the HWT from the PHI experiment and the Experimental Forecast Program (EFP). This feedback will be used in conjunction with feedback from forecasters to refine how the uncertainty information is generated and disseminated.
For the past few weeks, Darrel Kingfield and Dr. Kristin Calhoun from CIMMS/NSSL and Dr. Eric Bruning from Texas Tech University have been working alongside forecasters from the National Weather Service (NWS) Forecast Office in Lubbock, Texas, to generate and integrate real-time 1km lightning products into the Advanced Weather Interactive Processing System-2 (AWIPS-2). AWIPS-2 is the weather forecasting, display and analysis package currently being used by the NWS. The team pushed hard to get these products functional for potential severe weather on April 16 and were successful.
Two products — Flash Extent Density and Flash Initiation Density — are gridded visualizations of total lightning data from Lightning Mapping Arrays (LMA). There are several arrays across the U.S. that are able to map the three-dimensional shape, extent and development of branched lightning channels. These data are an essential component of modern lightning detection and physics studies, because they reliably map the extent of the in-cloud charge reservoirs tapped by each lightning flash. Both of these products have been successfully evaluated in the Hazardous Weather Testbed.
A third product, the experimental Flash Area product from Texas Tech University, was also integrated into AWIPS-2. Forecasters have seen in the LMA data that small, compact flashes are mostly associated with robust or developing convection. As thunderstorms mature and reach the subsequent dissipation stage, the flash area starts to increase. The transfer of these products to operations will provide the developers, researchers and forecasters with the opportunity to learn more about how total lightning products can be utilized in the forecast and warning decision process.
This work benefits operational forecasters, highlights research to operations transitions, and supports NOAA’s work to evolve the National Weather Service. It also supports NSSL’s Grand Scientific Challenge to predict useful warnings of lightning activity one hour in advance.
Kristin Calhoun (NSSL/CIMMS) will give an invited webinar to National Weather Service meteorologists and hydrologists on April 1, 2015, about current lightning prediction products in research and development at NSSL. Calhoun will also discuss the NOAA Hazardous Weather Testbed (HWT) and how forecaster feedback is used to evaluate and refine the products.The webinar is part of a monthly series for NWS Science Operations Officers and Development and Operations Hydrologists that benefits operational forecasters, highlights research to operations transitions, and supports NOAA’s work to evolve the National Weather Service.
It has long been theorized, and in limited studies demonstrated, that the use of total lightning detections and associated derivative products could have positive impacts on the warning process for thunderstorm events. Two total lightning algorithms to potentially improve short-term prediction and warnings of severe storms have been evaluated in the Hazardous Weather Testbed (HWT) in Norman, Oklahoma.
In severe storms, rapid increases in lightning flash rate, or “lightning jumps,” typically precede severe weather, such as tornadoes, hail and straight line winds, at the surface by tens of minutes. The GOES-R Geostationary Lightning Mapper (GLM) will allow the use of continuous total lightning observations and the lightning jump concept operationally throughout the United States. A total lightning jump algorithm (LJA) that can be used by NWS forecasters to enhance situational awareness and diagnose convective trends was evaluated in the HWT as part of the experimental warning program in 2014 and will be evaluated again in 2015.
Earth Networks (ENI), a private company that provides lightning data and products, has indicated the potential for their total lightning data and “Dangerous Thunderstorm Alerts” to increase lead-time over current National Weather Service (NWS) severe weather and tornado warnings, while maintaining a similar probability of detection and false alarm ratio. This project integrates the ENI total lightning data and products into the NWS operational software and tests the feasibility of use and performance under the stress of real time warning operations.
In 2014, 18 NWS forecasters visited the HWT during a period of six weeks, 21 July-29 August, for a full product evaluation. The forecasters completed a series of six two hour weather-warning simulations of marginally severe storms to high-impact tornadic events throughout the United States. The 2015 HWT experiment will build upon the initial evaluation in 2014, including enhancements based on forecaster feedback.
Weather forecasters rely on an incredibly large amount of information when they make forecasts and issue warnings. A new system, activated by NOAA’s National Weather Service last week, quickly harnesses the tremendous amount of weather data from multiple sources, intelligently integrates the information, and provides a detailed picture of the current weather.
The Multiple Radar Multiple Sensor (MRMS) system combines data streams from multiple radars, satellites, surface observations, upper air observations, lightning reports, rain gauges and numerical weather prediction models to produce a suite of decision-support products every two minutes. Because it provides better depictions of high-impact weather events such as heavy rain, snow, hail, tornadoes, and other threats, forecasters can quickly diagnose severe weather and issue more accurate and earlier forecasts and warnings.
“MRMS uses a holistic approach to merging multiple data sources, allowing forecasters to better analyze data and potentially make better predictions,” said Ken Howard, a research meteorologist at NOAA’s National Severe Storms Laboratory who helped design MRMS. “It was developed in collaboration with NOAA’s National Weather Service hydrologists and forecasters who tested experimental versions and provided valuable input and feedback.”
Researchers at NOAA’s National Severe Storms Laboratory designed the MRMS system to improve decision making within NOAA and other agencies – marking another NOAA research to operations success. Implementation of the system into NWS operations was funded in part by the Disaster Relief Appropriations Act of 2013.
MRMS will improve the ability of forecasters to issue public warnings and advisories for severe weather such as tornadoes, hail and flash floods, and will help improve forecasts for safety of air traffic.
NSSL’s experimental version of the MRMS system has been available at various National Weather Service offices, but now that it is becoming operational, NOAA researchers plan to continue their collaboration with NOAA partners such as developers, trainers and forecasters to collect best practices and case studies. The system is designed so that new techniques and products can be added, increasing its capabilities.
“The nationally consistent products available from the MRMS are another important step toward NOAA’s goal of building a Weather Ready Nation by providing better analyses and forecasts to a wide range of decision makers,” said Louis Uccellini, Ph.D., director of NOAA’s National Weather Service. “This is another tool to help ensure communities are better prepared and more resilient in the face of high-impact weather events.”
MRMS data are also an input into the newly operational High-Resolution Rapid Refresh weather model, which will improve the quality of forecasts and warnings for severe weather events.
NOAA researchers developed the MRMS system in cooperation with The University of Oklahoma’s Cooperative Institute for Mesoscale Meteorological Studies.
In this record-breaking spring tornado season, emergency responders are saving precious hours when they count the most – in the immediate aftermath of a devastating storm. A tool developed by the NOAA National Severe Stor m Lab (NSSL) has cut disaster assessment time dramatically for the organizations, state, and federal agencies that have adopted it.
The American Red Cross of Central Oklahoma, for example, is using the NSSL Warning Decision Support System—Integrated Information (WDSS-II) to shorten the time it takes to deliver assistance to the neighborhoods ripped apart by tornadoes. Real-time information from the system can be plotted on maps, for example, speeding up the response process.
“This technology cut our disaster assessment time down from 72 to 24 hours,” said Steven Klapp, a volunteer and disaster assessment team leader for the American Red Cross of Central Oklahoma. Klapp has trained more than 250 people in Oklahoma and Texas to use the technology to support disaster recovery operations.
American Red Cross Disaster Assessment teams were out in full-force the morning following the Tuesday, May 24, tornado outbreak in central Oklahoma. Their responders used the NSSL software tool to direct them where to go.
The tool helps the Red Cross to pinpoint when and where damage caused by severe weather most likely occurred. The system uses the Internet to draw data from a nationwide network of weather radars, satellites, surface observations, and lightning detectors.
The system receives data in real-time, then processes, analyzes, and displays the data in a way that is useful to people who need to diagnose severe weather quickly. The American Red Cross of Central Oklahoma uses the On Demand feature of this NSSL system to display storm information on a Web page.
The NSSL tool records the tracks of rotation in a storm and marks where hail fell using the storm data it gathers from radars, satellites, and other observation systems. The rotation track or hail swath image is produced in a format that can be opened in Google Earth. The image is automatically overlaid on Google Earth maps that can be viewed at any scale down to high-resolution street maps.
Disaster teams zoom in on the areas most likely damaged during a storm to assess which neighborhoods need assistance first and what roads they should take to get there.
“They no longer have to put boots on the ground to visually assess the situation before planning how they will deploy response teams,” said Kurt Hondl, NSSL research meteorologist. “It makes the coordination and planning of the American Red Cross’s response so much more efficient.”
“This kind of technology has been nothing short of a blessing for the American Red Cross and those we serve,” said Rusty Surette, director of communications for the American Red Cross of Central Oklahoma. “Our organization embraces anything that helps speed up our emergency services and deliveries to those who’ve been impacted by a disaster, and the WDSS-II has proven to be an effective tool in doing just that.”
“This is just another example of how NOAA’s emerging science and technology is being used to improve emergency services to our communities,” said Doug Forsyth, chief of NSSL’s Radar Research and Development Division.
Among other users of the NSSL On Demand software tool are the Virginia Department of Emergency Management, the Federal Emergency Management Agency, and the Department of Homeland Security. FEMA used it to plan aerial damage survey flyovers of the Arkansas storms in February 2008.
FEMA also used the rotation tracks to determine where FEMA-funded safe rooms might have been damaged by storms. FEMA responders can cross-reference the track and safe room locations easily, instead of manually sifting and sorting the information. This information lets them plan trips to storm-damage areas much faster than the old way, which was to wait for the release of official storm track data.
In addition, many National Weather Service Forecast Offices use the NSSL system for warning verification or damage surveys.
The WDSS-II On Demand software is available to all American Red Cross offices and other disaster assessment organizations. Go to http://ondemand.nssl.noaa.gov to learn more.
A team from NSSL completed the installation of NSSL’s real-time Multiple-Radar/Multiple-Sensor (MRMS) system at the FAA William J Hughes Technical Center in Atlantic City, N.J. last week.
The automated algorithms in MRMS quickly and intelligently integrate data streams from multiple radars, surface and upper air observations, lightning detection systems, satellite and forecast models. The MRMS system was developed to produce severe weather and precipitation products for improved decision-making capability within NOAA.
This system will be used to develop and test new aviation NextGen products in addition to advancing techniques in quality control, icing detection, and turbulence in collaboration with the National Center for Atmospheric Research, the University Corporation for Atmospheric Research, and Lincoln Laboratories.
The FAA Right Sizing project provided the hardware and funding resources to establish a MRMS system a William J Hughes Technical Center in Atlantic City. The RightSizing Project is a collaborative effort between the FAA, research laboratories and other government agencies to optimize the performance of the NextGen sensor systems and sensor networks and to understand, document and report on the complete range of current and alternative sensor technologies which may be fielded to support the NextGen National Airspace system.
The FAA is looking forward to the added capabilities the system brings to NSSL and FAA MOU objectives.
The MRMS system was jointly developed in cooperation with the Cooperative Institute for Mesoscale Meteorological Studies (CIMMS), and the University of Oklahoma retains the right to commercially license the software. Several leading weather information companies have previously licensed the MRMS system from the University of Oklahoma for commercial use, although the software is available for government at no cost.