April 27 Reddit AMA: Tornado! Severe Weather Research & Prediction with NOAA

Spring has arrived and with it come efforts to study and learn to better predict severe weather like tornadoes. Join NOAA for a Reddit Ask Me Anything (AMA) on severe weather research and prediction on April 27, 2017.

Patrick Marsh, Adam Clark, Kim Klockow and Harold Brooks will take your questions during Thursday’s #Reddit AMA.

Severe weather touches every state in the U.S. Tornadoes, severe thunderstorms, hail, strong winds, and floods are real threats to our property and our lives. The NOAA Hazardous Weather Testbed and VORTEX-SE (Verification of the Origins of Rotation in Tornadoes EXperiment-Southeast) are designed to learn more about storms, helping to improve our prediction abilities and bring you better forecasts.

At the National Weather Center, which houses NOAA’s National Severe Storm Laboratory (NSSL) and Storm Prediction Center, as well as the University of Oklahoma Cooperative Institute for Mesoscale Meteorological Studies (CIMMS), our scientists work to better understand and predict severe weather to help everyone be prepared.

Reddit AMA Details


     Harold Brooks, NOAA NSSL research meteorologist

     Kim Klockow, UCAR scientist at CIMMS

     Adam Clark, NOAA NSSL research meteorologist

     Patrick Marsh, NOAA SPC warning coordination meteorologist

When: Thursday, April 27, 2017, from 9:00 a.m. to 11:00 a.m. CT

Where: Reddit Science AMA series

About the Scientists

Harold Brooks, a senior scientist in the Forecast Research and Development Division of NOAA NSSL, is originally from St. Louis, Missouri. He received a Ph.D. in atmospheric science in 1990 from the University of Illinois at Urbana-Champaign. He joined NSSL in 1991 as a research meteorologist specializing in tornado climatology.

Adam Clark is a meteorologist with NOAA NSSL and a 2014 Presidential Early Career Award for Scientists and Engineers (PECASE) winner. Originally from Des Moine, Iowa, Clark received his Ph.D. in meteorology and started working at NSSL in 2009. Clark is active in the NOAA Hazardous Weather Testbed, which conducts experiments mainly late March and April.

Kim Klockow is a University Corporation for Atmospheric Research (UCAR) project scientist at NOAA’s Cooperative Institute for Mesoscale Meteorological Studies at The University of Oklahoma who earned her Ph.D. in Human Geography. Working with the NOAA National Severe Storms Laboratory, her research involves behavioral science focused on weather and climate risk, and explores the effects of risk visualization on judgment and perceptions of severe weather risk from a combination of place-based and cognitive perspectives.

Patrick Marsh is a warning coordination meteorologist at the NOAA National Weather Service’s Storm Prediction Center, which provides forecasts and watches for severe thunderstorms and tornadoes over the contiguous United States. He was born in Georgia but grew up in Arkansas and received his Ph.D. at the University of Oklahoma.


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Scientists gather to talk about using Unmanned Aerial Systems for weather research

UAS Scottsbluff, NE
University of Colorado’s Brian Argrow (with back to the camera) and graduate assistant Jason Roadman assemble the Tempest UAS prior to launch into a supercell near Scottsbluff, NE, June 2010.

Unmanned Aerial Systems (UASs) are becoming increasingly important as instrument platforms for remote and in-situ observations of the atmosphere just above the ground. Their adaptability, potential ease of deployment, and low cost make them an attractive research option. NSSL scientists will participate in the annual meeting of the International Society on Atmospheric Research using Remotely-piloted Aircraft (ISARRA) in Norman, Oklahoma, May 20 to 22 to share knowledge about using these aircraft systems to observe and monitor the atmosphere.

Topics presented by NSSL include using UASs as part of a composite observing system for predicting the formation and evolution of severe convective storms, roles for UAS in the 2016 VORTEX-Southeast project, and ground radar support of UAS operations with Multi-function Phased Array Radar (MPAR).

Using UASs for research is a developing endeavor. A University of Colorado (CU) UAS team successfully probed the rear-flank downdraft of a tornadic supercell in northeast Colorado during the second Verification of the Origins of Rotation in Tornadoes Experiment in 2009. With NSSL support, in June 2013, a CU, University of Nebraska-Lincoln, and NSSL team flew a UAS in coordination with an NSSL mobile mesonet (vehicle with atmospheric instruments) to sample outflows from several supercells in northeast Colorado.
These interactions support the NOAA goal of investing in observational infrastructure, and NOAA’s science mission to understand and predict changes in climate, weather, oceans and coasts.

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Significant papers

Significant Papers reported to HQ for the week ending April 17. The links to each are in blue.

1. Carlin, J. 2015. Weather radar polarimetry:  Dual-pol radar promises to improve the modeling of convective storms. Physics Today. March, 2015.

Significance: This is a concise and very accurate description of the basics of weather radar polarimetry and its potential benefits for convective-storm modeling.

2. Johnson, A., Wang, X., Carley, J., Wicker, L., Karstens, C. (2015). A comparison of multi-scale GSI-based EnKF and 3DVar data assimilation using radar and conventional observations for mid-latitude convective-scale precipitation forecasts. Monthly Weather Review 2015.

Significance: Implication is that the current state of 3DVar within the GSI is not well suited for the assimilation of high-resolution meoscale and storm-scale data. The results supports NCEP developing ensemble-based data assimilation methods (potentially including hybrid methods) for meso- and storm-scale prediction.

3. Potvin, C., Flora, M. (2015). Sensitivity of idealized supercell simulations to horizontal grid spacing: Implications for Warn-on-Forecast. Monthly Weather Review 2015.

Significance: Improved understanding of grid spacing dependence of simulated convection will be needed to properly interpret and calibrate ensemble output, and to optimize tradeoffs between model resolution and other computationally constrained parameters like ensemble size and forecast lead time.

4. Yussouf, N., Dowell, D., Wicker, L., Knopfmeier, K., Wheatley, D. (2015). Storm-scale Data Assimilation and Ensemble Forecasts for the 27 April 2011 Severe Weather Outbreak in Alabama. Monthly Weather Review 2015.

Significance: The short-range ensemble probabilistic forecasts obtained from this study demonstrate the potential of a frequently-updated, high-resolution NWP systems that could be used to extend severe weather warning lead times (WoF).

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Tags: None

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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NSSL/CIMMS researchers to share cutting-edge radar research in Europe

Screen Shot 2014-09-03 at 11.40.22 AM

Researchers from NSSL/CIMMS will share the latest radar research at the 8th European Conference on Radar in Meteorology and Hydrology September 1-5 in Garmisch-Partenkirchen, Germany.

Some of the topics to be presented include:

  • New techniques and algorithms that use output from a high-resolution weather model to predict precipitation types at the ground, and to identify the layer in the atmosphere where melting occurs
  • Observations made by a dual-pol data quality team during and after the dual-pol deployment process including observations of tornado debris, the descent of the snow level in Arizona, a smoke plume, and the interface of shallow and deep water over the ocean.
  • A new technique was demonstrated for WSR-88D and weather Phased Array Radar (PAR) that transmits a few radar pulses into different directions and simultaneously receives returns to shorten update time from 1 minute to 15 seconds
  • Whether super-resolution data produced by range-oversampling techniques help or hurt NEXRAD’s ability to detect tornadoes.
  • A dual-pol product that could aid in the detection of developing and evolving deep moist convection by locating and tracking thunderstorm updrafts
  • A range-based volume coverage pattern algorithm developed to improve vertical spatial resolution without sacrificing scan update times
  • Results from a study that asked a NWS forecaster, who issued warnings for a violent tornado event in central Oklahoma using WSR-88D data, to evaluate the same event using rapid-scanning Phased Array Radar data.  The forecaster found PAR data proved most advantageous in instances of rapid storm organization, sudden mesocyclone intensification, and abrupt, short-term changes in tornado motion.
  • Overview of the NSSL Research to Operations (R2O) process, past scientific and engineering contributions, as well as current R2O activities in signal processing and polarimetric techniques.

The mission of ERAD2014 is to provide a platform for exchange between students, research scientists, radar operators, and end users of weather radar. It also provides an opportunity to transfer knowledge from research into operational use (and vice versa) of weather radar. The first ERAD conference was in Bologna, Italy in 2000.

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Significant papers sent to HQ

Journal: Weather and Forecasting

Early online release: March 27

Title: Forecaster Use and Evaluation of Real-Time 3DVAR Analyses during Severe Thunderstorm and Tornado Warning Operations in the Hazardous Weather Testbed

Authors: Kristin M. Calhoun,* Travis M. Smith, and Darrel M. Kingfield, Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma, NOAA/OAR National Severe Storms Laboratory, Norman, Oklahoma, Jidong Gao and David J. Stensrud NOAA/OAR National Severe Storms Laboratory, Norman, Oklahoma

Summary: A weather-adaptive three-dimensional data assimilation (3DVAR) system was included in the NOAA Hazardous Weather Testbed as a first step towards introducing Warn-on-Forecast initiatives into operations. NWS forecasters were asked to incorporate the data in conjunction with single-radar and multi-sensor products in the Advanced Weather Interactive Processing System (AWIPS) as part of their warning-decision process for real-time events across the United States.

Important Conclusions: Forecasters found the updraft, vertical vorticity, and storm-top divergence products the most useful for storm interrogation and quickly visualizing storm trends, often using these tools to increase the confidence in a warning decision and/or issue the warning slightly earlier. Blending data from multiple radars was extremely useful to forecasters rather than having to analyze multiple radars separately. The largest hurdle for realtime use of 3DVAR or similar data assimilation products by forecasters is the data latency, as even 4-6 minutes reduces the utility of the products when new radar scans are available.

Significance: The eventual goal of this real-time 3DVAR system is to help meteorologists better track severe weather events and eventually provide better warning information to the public, ultimately saving lives and reducing property damage.


Journal: Bulletin of the AMS

Online release: April 2, 2014

Title: ATMOSPHERIC SCIENCES AND RELATED RESEARCH: Current Systems, Emerging Technology, and Future Needs


Summary: To assist the National Science Foundation in meeting the needs of the community of scientists by providing them with the instrumentation and platforms necessary to conduct their research successfully, a meeting was held in late Nov. 2012 with the purpose of defining the problems of the next generation that will require radar technologies and determining the suite of radars best suited to help solve these problems.

Important Conclusions: The research community recommended polarimetric radars, S-band radars with Bragg-scattering radars, airborne radars, diverse radar platforms at several wavelengths, VHF profiling systems, radars in data sparse areas, deployable networks of radars, phased-array radar technology, better software tools for radar display and analysis, availability of radar instrumentation for the research community, educational support, and an increase computer resources. Radar developers need to think far ahead (~50 years). What is useful now might quickly become old technology.

Significance: The emerging radar technologies that will be most helpful in answering the key scientific questions are identified.

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NSSL scientists invited editors for special journal issue

Advances In Meteorology-Feb2014NSSL scientists Jidong Gao, David Stensrud, and Louis Wicker were among five invited guest editors for a special issue of Advances in Meteorology, an open access international journal. This special issue focuses on high-resolution storm-scale computer models that ingest or assimilate radar data.

With the steady increase in computing power, operational centers throughout the world are preparing to run their weather computer models at resolutions high enough to predict individual thunderstorms. To do this, the models will be required to ingest observations.

This opportunity increases the demand for using radar data in storm-scale data assimilation in order to insert storm structures into model initial conditions.

The potential for successfully assimilating radar data into storm-scale numerical weather prediction (NWP) models is challenged by data quality control, proper estimation of the background error statistics, and the estimation of atmospheric state variables that are not directly observed by radar.

This special issue focuses on progress in some of these important areas. There are 12 papers published in this special issue, including seven papers from NSSL and five papers from other institutions. This special issue can be found at:  http://www.hindawi.com/journals/amete/si/567170/

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NSSL/CIMMS researchers to present at AMS annual meeting

AMSlogo-compact-final.ashxNSSL and CIMMS staff are preparing to receive honors and present recent research at the 2014 American Meteorological Society Annual Meeting in Atlanta, Ga., February 1-6.

NSSL’s Doug Forsyth, retired Chief of the Radar Research and Development Division, has been elected an AMS Fellow and will be honored at the meeting.

Presentations and poster topics include the first real-data demonstration of the potential impact from an MPAR observing capability for storm-scale numerical weather prediction, using cloud top temperatures in numerical weather prediction models to forecast when thunderstorms will form, and crowdsourcing public observations of weather.  Real-time flash flood modeling, understanding forecasters’ needs to improve radar observations using adaptive scanning, and aircraft detection and tracking on the National Weather Radar Testbed Phased Array Radar will also be presented.

Preliminary analyses of research data collected during the 2013 May tornado outbreaks in Oklahoma will be a special focus at the meeting.

NSSL staff will also serve as session chairs.

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2011 OAR Outstanding Scientific Paper

2011 Outstanding Scientific Paper 

Mr. M.R. Kumjian and Dr. A. V. Ryzhkov

Storm-Relative Helicity Revealed from Polarimetric Radar Measurements. Journal of the Atmospheric Sciences, 66, 667-685

The dual-polarization radar variables are especially sensitive to the microphysical processes of melting and size sorting of precipitation particles. In deep convective storms, polarimetric measurements of such processes can provide information about the airflow in and around the storm that may be used to elucidate storm behavior and evolution. Size sorting mechanisms include differential sedimentation, vertical transport, strong rotation, and wind shear. In particular, winds that veer with increasing height typical of supercell environments cause size sorting that is manifested as an enhancement of differential reflectivity (ZDR) along the right or inflow edge of the forward-flank downdraft precipitation echo, which has been called the ZDR arc signature. In some cases, this shear profile can be augmented by the storm inflow. It is argued that the magnitude of this enhancement is related to the low-level storm-relative environmental helicity (SRH) in the storm inflow.

To test this hypothesis, a simple numerical model is constructed that calculates trajectories for raindrops based on their individual sizes, which allows size sorting to occur. The modeling results indicate a strong positive correlation between the maximum ZDR in the arc signature and the low-level SRH, regardless of the initial drop size distribution aloft. Additional observational evidence in support of the conceptual model is presented. Potential changes in the ZDR arc signature as the supercell evolves and the low-level mesocyclone occludes are described.

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NSSL and NSSL/CIMMS scientists will be presenting their work at the 46th annual Fall Meeting of the American Geophysical Union next week in San Francisco, Calif. They will also be available in the NOAA booth to answer questions and display their research data.

Topics include:

  • Simulating storm electrification with bin and bulk microphysics
  • Electrical Discharges in the Overshooting Tops of Five Storms
  • Balloon-borne electric field and microphysics measurements in the 29-30 May 2012 supercell storm in Oklahoma during DC3
  • Evaluating Snowfall Detectability of NASA CloudSat with NOAA/NSSL Ground Radar-Based National Multi-sensor Mosaic QPE (NMQ)
  •  Raman Lidar Observations from the ARM Site in Darwin, Australia: A Water Vapor and Aerosol Climatology
  • Retrospective Analysis of High-Resolution Multi-Radar Multi-Sensor QPEs for the Unites States
  • A real-time automated quality control of rain gauge data based on multiple sensors
  • Evaluating Global Precipitation Measurement (GPM) Precipitation Products in Real-Time
  • Uncertainty in Quantitative Precipitation Estimates and Forecasts in a Hydrologic Modeling Context


More than 22,000 Earth and space scientists, educators, students, and other leaders gather for the meeting each year to present groundbreaking research and connect with colleagues.

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