Darrel Kingfield, Ph.D. has been with NOAA since 2007 where he has worked at the intersection of National Weather Service (NWS) watch/warning evolution, hazardous weather research and algorithm development, and transitioning research-to-operations. At the Warning Decision Training Division from 2007-2012, he served as the project manager for the Weather Event Simulator, training forecasters to efficiently analyze meteorological data and issue accurate warnings during different weather scenarios. At the National Severe Storms Laboratory from 2012-2018, he worked in the Severe Weather Warning Applications and Technology Transfer Team focused on the development, evaluation, and transition of new technologies to NWS operations. He served as the technical lead for NOAA’s Hazardous Weather Testbed and worked on dozens of experiments evaluating new hazard detection and avoidance algorithms. He also led the delivery of the Multi-Radar/Multi-Sensor system initial operating capability products to NWS operations. At Global Systems Laboratory, he serves as the Hazard Services Program Manager with a program mission to streamline and modernize the hazardous weather watch/warning/advisory process for all hazards produced by the NWS.
Warning/Hazard dissemination systems
Hazardous weather detection using Doppler radar
Meteorological algorithm development and evaluation
Damage identification using multispectral satellite imagery
Ph.D., Geography, University of Oklahoma, May 2017
M.S., Geoinformatics, University of Oklahoma, August 2010
B.S., Synoptic Meteorology, Purdue University, May 2006
2020 - Present, Research Physical Scientist, NOAA/Global Systems Laboratory
2018 - 2020, Research Scientist II, NOAA/Global Systems Laboratory - Cooperative Institute for Research in Environmental Sciences (CIRES)
2017-2018, Research Scientist II, NOAA/National Severe Storms Laboratory (NSSL) - Cooperative Institute for Mesoscale Meteorological Studies (CIMMS)
2012-2017, Warning Research Associate, NOAA/National Severe Storms Laboratory (NSSL) - Cooperative Institute for Mesoscale Meteorological Studies (CIMMS)
2007-2012, Research Associate, NOAA/Warning Decision Training Division (WDTD) - Cooperative Institute for Mesoscale Meteorological Studies (CIMMS)
Honors and Awards
Aug. 2018 - National Weather Association Larry R. Johnson Award (Group Award)
Citation: “For creating the Meteorological Phenomena Identification Near the Ground (mPING) application which improved forecast operations by significantly increasing the number, quality, and type of ground-truth weather observations.”
Individual Role: Member of development team tasked with developing the database architecture to store the mPING reports.
Sep. 2016 - National Weather Association Larry R. Johnson Award (Group Award)
Citation: “For research, development, and delivery of severe weather applications which have been successfully transitioned into NWS operations, providing critical tools for NWS forecasts and warnings.”
Individual Role: Researcher and group developer of the Multiple-Radar/Multiple-Sensor (MRMS) severe weather suite of products and AWIPS-transition focal point for the migration of products to NWS offices and national centers.
Oct. 2015 - National Weather Association Larry R. Johnson Award (Group Award)
Citation: “For long-term and meritorious contributions to operational meteorology, and serving as a unique portal for research to operations”
Individual Role: First developer to design and implement a flexible, geopolitically agnostic, real-time or displaced real-time, Advanced Weather Interactive Processing System (AWIPS) framework capable of ingesting operational product sets alongside experiment products for side-by-side evaluations in NOAA's Hazardous Weather Testbed since 2008.
Sep. 2015 - U.S. Department of Commerce Silver Medal for Science/Engineering Achievement (Group Award)
Citation: “For successful transition of the Multi-Radar, Multi-Sensor (MR/MS) system into operations to provide critical radar-based products to forecast weather hazards.”
Individual Role: Lead Engineer in the design and implementation of the MR/MS 1 km and 500 m gridded products into the Advanced Weather Interactive Processing System (AWIPS) software environment.
Service on international research coordination organizations
2017-Present - Member, Remote Sensing Subcommittee - ASCE Standards Committee for Wind Speed Estimation in Tornadoes
How many M.S. and Ph. D. committees have you served on in the past five years?
Served as a mentor for 2 M.S. students and 1 Ph.D. student at SUNY Stony Brook.
Tuftedal, K. S., M. M. French, D. M. Kingfield, and J. C. Snyder, 2021: Observed Bulk Hook Echo Drop Size Distribution Evolution in Supercell Tornadogenesis and Tornadogenesis Failure. Mon. Wea. Rev., Accepted.
McKeown, K. E., M. M. French, K. S. Tuftedal, D. M. Kingfield, H. B. Bluestein, D. W. Reif, and Z. B. Wienhoff 2020: Rapid-Scan and Polarimetric Radar Observations of the Dissipation of a Violent Tornado on 9 May 2016 Near Sulphur, Oklahoma. Mon. Wea. Rev., 148, 3951-3971, doi: 10.1175/MWR-D-20-0033.1.
Li, J., T. Yu, I. Javed, C. Siddagunta, R. Pakpahan, M. E. Langston, L. K. Dennis, D. M. Kingfield, D. J. Moore, G. L. Andriole, H. H. Lai, G. A. Colditz, and S. Sutcliffe, 2020: Does weather trigger urologic chronic pelvic pain syndrome flares? A case‐crossover analysis in the multidisciplinary approach to the study of the chronic pelvic pain research network. Neurourology and Urodynamics. 39, 1494–1504, doi: 10.1002/nau.24381.
Mahalik, M. C., B. R. Smith, K. L. Elmore, D. M. Kingfield, K. L. Ortega, and T. M. Smith, 2019: Estimates of Gradients in Radar Moments Using a Linear Least Squares Derivative Technique. Wea. Forecasting, 34, 415–434, doi: 10.1175/WAF-D-18-0095.1.
French, M.M. and D.M. Kingfield, 2019: Dissipation Characteristics of Tornadic Vortex Signatures Associated with Long-Duration Tornadoes. J. Appl. Meteor. Climatol., 58, 317–339. doi: 10.1175/JAMC-D-18-0187.1.
Kingfield, D.M. and J.C. Picca, 2018: Development of an Operational Convective Nowcasting Algorithm Using Raindrop Size Sorting Information from Polarimetric Radar Data. Wea. Forecasting, 33, 1477–1495. doi: 10.1175/WAF-D-18-0025.1.
Kingfield, D.M., K.M. Calhoun, K.M. de Beurs, and G.M. Henebry, 2018: Effects of City Size on Thunderstorm Evolution Revealed through a Multiradar Climatology of the Central United States. J. Appl. Meteor. Climatol., 57, 295–317. doi: 10.1175/JAMC-D-16-0341.1.
Kingfield, D. M., K. M. Calhoun, and K. M. de Beurs, 2018: Antenna structures and cloud‐to‐ground lightning location: 1995–2015. Geophys. Res. Let., 44, 5203-5212. doi: 10.1002/2017GL073449.
Kingfield, D. M. and K. M. de Beurs, 2017: Landsat Identification of Tornado Damage by Land Cover and an Evaluation of Damage Recovery in Forests. J. Appl. Meteor. Climatol., 56, 965-987. doi: 10.1175/JAMC-D-16-0228.1.
Wilson, K.A., P.L. Heinselman, C.M. Kuster, D.M. Kingfield, and Z. Kang, 2017: Forecaster Performance and Workload: Does Radar Update Time Matter?. Wea. Forecasting, 32, 253–274. doi: 10.1175/WAF-D-16-0157.1.
Hwang, Y., T-Y Yu, V. Lakshmanan, D. M. Kingfield, D-I Lee, and C-H. You, 2017: Neuro-Fuzzy Gust Front Detection Algorithm with S-Band Polarimetric Radar. IEEE Trans. Geoscience and Remote Sensing, 55, 1618-1628. doi: 10.1109/TGRS.2016.2628520.
Smith, T. M., V. Lakshmanan, G. J. Stumpf, K. L. Ortega, K. Hondl, K. Cooper, K. M. Calhoun, D. M. Kingfield, K. L. Manross, R. Toomey, and J. Brogden, 2016: Multi-Radar Multi-Sensor (MRMS) Severe Weather and Aviation Products: Initial Operating Capabilities. Bull. Amer. Meteor. Soc., 97, 1617-1630. doi: 10.1175/BAMS-D-14-00173.1.
Karstens, C.D., G. Stumpf, C. Ling, L. Hua, D. Kingfield, T.M. Smith, J. Correia, K. Calhoun, K. Ortega, C. Melick, and L.P. Rothfusz, 2015: Evaluation of a Probabilistic Forecasting Methodology for Severe Convective Weather in the 2014 Hazardous Weather Testbed. Wea. Forecasting, 30, 1551–1570. doi: 10.1175/WAF-D-14-00163.1.
Jiang, H., S. Albers, Y. Xie, Z. Toth, I. Jankov, M. Scotten, J. Picca, G. Stumpf, D. Kingfield, D. Birkenheuer, and B. Motta, 2015: Real-Time Applications of the Variational Version of the Local Analysis and Prediction System (vLAPS). Bull. Amer. Meteor. Soc., 96, 2045–2057. doi: 10.1175/BAMS-D-13-00185.1.
Lakshmanan, V., B. Herzog, and D. Kingfield, 2015: A Method for Extracting Postevent Storm Tracks. J. Appl. Meteor. Climatol., 54, 451-462. doi: 10.1175/JAMC-D-14-0132.1
Kingfield, D. M., and J. G. LaDue, 2015: The Relationship between Automated Low-Level Velocity Calculations from the WSR-88D and Maximum Tornado Intensity Determined from Damage Surveys. Wea. Forecasting, 30, 1125-1139. doi: 10.1175/WAF-D-14-00096.1.
Bowden, K.A., P.L. Heinselman, D.M. Kingfield, and R.P. Thomas, 2015: Impacts of Phased-Array Radar Data on Forecaster Performance during Severe Hail and Wind Events. Wea. Forecasting, 30, 389–404. doi: 10.1175/WAF-D-14-00101.1.
Heinselman, P., D. LaDue, D. M. Kingfield, and R. Hoffman, 2015: Tornado Warning Decisions Using Phased-Array Radar Data. Wea. Forecasting, 30, 57–78. doi: 10.1175/WAF-D-14-00042.1.
Calhoun, K.M., T.M. Smith, D.M. Kingfield, J. Gao, and D.J. Stensrud, 2014: Forecaster Use and Evaluation of Real-Time 3DVAR Analyses during Severe Thunderstorm and Tornado Warning Operations in the Hazardous Weather Testbed. Wea. Forecasting, 29, 601–613. doi: 10.1175/WAF-D-13-00107.1.
Smith, T.M., J. Gao, K.M. Calhoun, D.J. Stensrud, K.L. Manross, K.L. Ortega, C. Fu, D.M. Kingfield, K.L. Elmore, V. Lakshmanan, and C. Riedel, 2014: Examination of a Real-Time 3DVAR Analysis System in the Hazardous Weather Testbed. Wea. Forecasting, 29, 63–77. doi: 10.1175/WAF-D-13-00044.1.