Cooperative Institute for Research in Environmental Sciences at the University of Colorado Boulder

Darrel Kingfield

Research Interests

  • Warning/Hazard dissemination systems
  • Hazardous weather detection using Doppler radar
  • Meteorological algorithm development and evaluation
  • Damage identification using multispectral satellite imagery

Current Research

​I am a member of the Weather Information Systems Evolution (WISE) team where I serve as the Hazard Services Program Manager. Hazard Services is a next-generation hazard alert generation system that will streamline the meteorological advisory/watch/warning process for NWS offices across the country. In addition to this role, I am a scientific applications and research-to-operation transition leader tasked with researching, developing, and evaluating meteorological algorithms and forecast decision-assistance software for use by government entities like the National Weather Service (NWS), Bureau of Land Management (BLM), and the Taiwan Central Weather Bureau (CWB).

Concurrent to this, I am a PI on several grants including (1) a National Science Foundation grant examining the bulk hydrometeor characteristics of tornadic and non-tornadic supercells using Weather Service Radar-1988 Doppler (WSR-88D) data, (2) a NOAA grant incorporating the GOES-16/17 Geostationary Lightning Mapper into the Rapid Update Cycle (RAP) and High Resolution Rapid Refresh (HRRR) model assimilation frameworks, and (3) a NOAA grant examining the benefits of creating flexible county warning area boundaries for NWS severe thunderstorm and tornado warning collaboration between forecast offices.

Selected Recent Publications:

Mahalik, M. C., B. R. Smith, K. L. Elmore, D. M. Kingfield, K. L. Ortega, T. M. Smith, 2019: Estimates of Gradients in Radar Moments Using a Linear Least-Squares Derivative Technique. Wea. Forecasting, In Press. 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. Forecasting33, 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, K.M. de Beurs, 2017: Antenna structures and cloud‐to‐ground lightning location: 1995–2015. J. Geophys Res. Lett.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

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

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. Forecasting30, 1125–1139, doi: 10.1175/WAF-D-14-00096.1

Heinselman, P., D. LaDue, D.M. Kingfield, and R. Hoffman, 2015: Tornado Warning Decisions Using Phased-Array Radar Data. Wea. Forecasting30, 57–78, doi:10.1175/WAF-D-14-00042.1 


Darrel Kingfield (yellow coat) surveying damage in Moore, Oklahoma after the 20 May 2013 EF-5 tornado. These damage observations were compared to multispectral satellite retrievals and reported in:
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

Darrel Kingfield giving a seminar on polarimetric Doppler weather radar applications to participants from across the European Union at the European Severe Storms Laboratory Summer Testbed in Wiener Neustadt, Austria.

Honors and Awards

  • 2018 National Weather Association Larry R. Johnson Special Award (team award) - "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."
  • 2018 Charles Standley Memorial Award for Outstanding Publication by a Graduate Student - "For 'Effects of City Size on Thunderstorm Evolution Revealed through a Multiradar Climatology of the Central United States' published in the February 2018 issue of the Journal of Applied Meteorology and Climatology"
  • 2016 National Weather Association Larry R. Johnson Special Award (team award) - "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."
  • 2015 National Weather Association Larry R. Johnson Special Award (team award) - "For long-term and meritorious contributions to operational meteorology, and serving as a unique portal for research to operations"
  • 2015 Dept. of Commerce Silver Medal (team award) - "For successful transition of the Multi-Radar, Multi-Sensor (MR/MS) system into operations to provide critical radar-based products to forecast weather hazards."
  • 2010 Center for Spatial Analysis Environmental Systems Research Institute Outstanding Student Scholarship
  • 2009 United States Geospatial Intelligence Foundation (USGIF) Scholarship