Weather radar research is a key part of NSSL’s mission in support of the NOAA National Weather Service (NWS). This week, NSSL/CIMMS scientists will share the latest in weather radar research at the American Meteorological Society’s 2013 Conference on Radar Meteorology in Breckenridge, Colo.
Phased array radar research presentations include:
An overview of the latest improvements to the National Weather Radar Testbed
Phased Array Radar (NWRT PAR) capabilities to demonstrate Multi-function
Phased Array Radar (MPAR) program weather and aviation requirements
How NWS forecasters’ responded to rapid, adaptive phased array radar sampling and if it increased their ability to effectively cope with tough tornado
New techniques to increase the NWRT PAR scan rate and reduce observation
NWRT PAR observations of microburst events
A method to detect and characterize storm merges and splits using rapidly updating NWRT PAR observations in thunderstorm models
NSSL/CIMMS researchers also work with current weather radars in operation and will present:
A new algorithm that combines output from a forecast model with dual-polarized radar data to more accurately estimate what winter weather is occurring between the lowest scan of the radar and the ground.
A study of how NSSL’s products that estimate precipitation amounts improved using dual-polarized radar data
Evaluation of existing hail size estimation algorithms
Crowdsourced reports precipitation types at the ground using the “meteorological Phenomena Identification Near the Ground” (mPING) smart phone app
Development of a database of U.S. flash flood events using NSSL’s Severe Hazards Analysis and Verification Experiment, and mPING reports
Improvements in radar wind data quality control
Other presentations include mobile radar observations of a tornadic supercell and rainfall in the Mediterranean region and airborne radar observations of precipitation in the Indian Ocean.
NSSL and collaborators will leverage new technology including dual-polarized radar observations and a precipitation reporting mobile device app to improve forecasts of winter weather during February and March.
The experiment will evaluate the performance of new algorithms that use dual-polarized radar data and determine what new tools could be developed to improve detection of precipitation type and amount in winter storms.
The group will assess a new technique that is a “first-guess” of precipitation type using dual-pol data and compare it to observations collected from the Precipitation Identification Near the Ground mobile app and the Severe Hazards Analysis and Verification Experiment phone calls. They plan to identify potential biases and regions of poor performance.
They will also look at quantitative precipitation estimation products that include dual-polarized information and compare them to current products to see if dual-polarized data improves the result.
The experiment is a collaboration between NSSL, the Storm Prediction Center, the Norman Weather Forecast Office, the National Weather Service Warning Decision Training Branch and the Radar Operations Center.
The NSSL/CIMMS Severe Hazards Analysis and Verification Experiment (SHAVE) are collecting hail, wind damage and flash flooding reports through phone surveys from now through mid-August. This is the sixth year of the project, logging more than 29,000 hail reports, 5500 wind reports and 9300 flash flood reports since the project began.
SHAVE reports, when combined with the voluntary reports collected by the NWS, creates a unique and comprehensive database of severe and non-severe weather events and enhances climatological information about severe storm threats in the U.S. Some NWS forecast offices use SHAVE data to assist in verifying their warnings.
Largely student led and run, the SHAVE team makes phone calls along the path of a target storm. People who answer the calls are questioned about hail size, wind damage and flash flooding that occurred over the past 60 minutes. The phone data is blended with radar information on Google Maps to create a database on the storm for research.
NSSL/CIMMS researchers are using the SHAVE datasets as verification for multi-radar, multi-sensor detection algorithms and techniques, dual polarized radar, and a system that automatically detects supercell thunderstorms.
Because SHAVE leans heavily on students, it gives them rich opportunities for professional development and leadership. It has also led to year-round undergraduate research assistantships and research projects for over half of the participants. Between 2006-2011, 26 students have worked for SHAVE.
Flash floods are the number one hazardous weather-related killer in the US, yet they remain poorly observed. An NSSL project now collects data from the public on flash flooding, in addition to hail and win
d reports. This effort is creating a comprehensive database that will lead to the development of better tools to identify regions being impacted or about to be impacted by hazardous weather.
An article on the flash flood data collection success is currently in press in the Journal of Hydrology.
Since 2006, NSSL’s Severe Hazards Analysis and Verification Experiment (SHAVE) has conducted phone surveys of residents along the path of a target storm. People who answer the calls are asked about hail size and wind damage that occurred during the past 60 minutes. The addition of the collection of witness reports on flash floods was added in 2008. Data from the survey responses are used to evaluate flash flood forecasts from radar information and hydrologic model outputs.
The SHAVE flash flood reports supplement the operational NWS database because they are higher in density and contain additional information such as “no flooding” reports, “minor” impacts from flash flooding, floodwater depths, lateral extents of flooded streams, road closures, respondent estimated flood frequencies, evacuations, and rescues.
The combined datasets will lead to flash flood climatology maps, improved understanding of rainfall-runoff processes that cause flash floods, and the ability to evaluate and improve tools used to detect and predict flash floods.
Over the past five summers, students have been making thousands of phone calls to collect reports of severe weather from the public as part of the Severe Hazards Analysis and Verification Experiment (SHAVE). SHAVE reports, when combined with the voluntary reports collected by the National Weather Service, create a comprehensive database of severe and non-severe weather events.
From May through August each year, SHAVE students conduct phone surveys of residents along the path of a target storm. People who answer the calls are asked about hail size, wind damage and flash flooding that occurred during the past 60 minutes. The phone data is blended with radar information on Google Maps to create a database on the storm for research.
“The process of verification through SHAVE’s calls is much more comprehensive and the potential applications of the high-resolution datasets are nearly endless, “ said Keith Sherburn, a student working with SHAVE as part of a NOAA Hollings undergraduate internship.
SHAVE data collected during the past several years is being used by a number of NSSL researchers to evaluate severe weather detection algorithms and techniques. Several students are evaluating how well specific signals in the radar data indicate hail at the ground. Other students are using SHAVE hail reports to test the reliability of different warning decision support products. SHAVE wind reports are being studied to determine what radar signatures are most and least efficient for identifying areas of severe wind in thunderstorms. SHAVE flood reports are being used to evaluate the skill of legacy flash flood guidance and new gridded flash flood guidance being developed at River Forecast Centers.
SHAVE students also collected hail data on any storm that VORTEX2, the Verification of the Origins of Rotation in Tornadoes Experiment targeted during its field campaigns. The data will be combined with data collected by mobile radars and probes on the same storm to increase our knowledge and understanding of severe weather.
Between 2006 and 2010, 24 students have worked for SHAVE. Largely student lead and run, SHAVE provides rich opportunities for professional development and leadership and has opened doors leading to year-round undergraduate research assistantships and research projects for more than half of the participants.