Airborne Doppler observations of tropical cyclones and convective phenomena.
Assimilation of the Doppler observations in simulations of tropical cyclones.
Methods to improve automated quality control of airborne Doppler observations, including the structure of first-guess fields used to improve real-time de-aliasing.
Observing System Simulation Experiments, particularly those designed to optimize collection of airborne data.
John Gamache, Ph.D.
Meteorologist, Hurricane Research Division
4301 Rickenbacker Causeway
Miami, Florida 33149
Dr. John Gamache was the leader of the HRD radar group, and continues to serve in the group, particularly as curator of the automated tail Doppler radar quality control and analysis software. The primary purposes of the radar group are archiving and displaying the airborne radar data collected in hurricanes, evaluating their quality, and maintaining and developing software to quality-control, analyze, display, and transmit the data. The two most significant contributions of the automated software are 1) real-time analyses for use by forecasters and quality-controlled data for assimilation in numerical models, and 2) the assistance to all who would use the data to improve basic understanding of tropical cyclones and other weather phenomena, by greatly reducing the workload to analyze the data.
1983, Ph.D., University of Washington, Seattle, WA
1976, B.S., University of Maryland, College Park, MD
- Zhang, J.A., R.F. Rogers, P.D. Reasor, and J. Gamache. The mean kinematic structure of the tropical cyclone boundary layer and its relationship to intensity change. Monthly Weather Review, 151(1):63-84, https://doi.org/10.1175/MWR-D-21-0335 2023
- Fischer, M.S., P.D. Reasor, R.F. Rogers, and J.F. Gamache. An analysis of tropical cyclone vortex and convective characteristics in relation to storm intensity using a novel airborne Doppler radar database. Monthly Weather Review, 150(9):2255-2278, https://doi.org/10.1175/MWR-D-21-0223.1 2022
- Zawislak, J., R.F. Rogers, S.D. Aberson, G.J. Alaka, G. Alvey, A. Aksoy, L. Bucci, J. Cione, N. Dorst, J. Dunion, M. Fischer, J. Gamache, S. Gopalakrishnan, A. Hazelton, H.M. Holbach, J. Kaplan, H. Leighton, F. Marks, S.T. Murillo, P. Reasor, K. Ryan, K. Sellwood, J.A. Sippel, and J.A. Zhang. Accomplishments of NOAA’S airborne hurricane field program and a broader future approach to forecast improvement. Bulletin of the American Meteorological Society, 103(2):E311-E338, https://doi.org/10.1175/BAMS-D-20-0174.1 2022
2022 U.S. Department of Commerce Bronze Medal
For the successful delivery of operational, near real-time Doppler radar data from the NOAA Hurricane Hunter aircraft to the National Hurricane Center.
2018 NOAA Administrator’s Award
For the design, fabrication, and validation of the airborne dual-Doppler weather radar system on NOAA’s P-3 aircraft.
2014 American Meteorological Society Banner I. Miller Award
For valuable insights into incorporating real-time airborne Doppler radar measurements via ensemble data assimilation, leading to improvements in forecasts of tropical cyclone track and intensity. Research described in “Performance of convection-permitting hurricane initialization and prediction during 2008-2010 with ensemble data assimilation of inner-core airborne Doppler radar observations” by Fuqing Zhang, Yonghui Weng, John Gamache, and Frank Marks, Jr.
2012 NOAA Administrator’s Award
For outstanding management of the G-IV Tail Doppler Radar project, enhancing NOAA’s weather forecasting and research capability.
2007 Army Corps of Engineers Patriotic Civilian Service Award
In recognition of participation on the Hurricane Katrina Interagency Performance Evaluation Task Force.
2007 U.S. Department of Commerce Bronze Medal
For employing a unique technology to diagnose Hurricane Katrina’s winds, a technology needed for surge, wave, intensity, and ecosystem modeling efforts.
2006 NOAA Administrator’s Award
For the development of the algorithms and related software to enable real-time analysis and transmission of wind fields and airborne Doppler radar data collected in hurricanes to improve the initialization of the new generation of hurricane forecast models.