Christopher Curtis

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Christopher Curtis

Research
Scientist III

chdcurtis@ou.edu
chris.curtis@noaa.gov
National Weather Center 4417

Education

PhD, Engineering, University of Oklahoma
MS, Applied Mathematics, University of Illinois
BS, Mathematics with CS, University of Oklahoma

Affiliated CIWRO Team

Advanced Radar Techniques (ART)

About

From 1995 to 1999, Dr. Curtis was with the Radar Signal Processing Group at Texas Instruments and later Raytheon in Plano, TX. He is currently a research scientist with the Cooperative Institute for Severe and High-Impact Weather Research and Operations (CIWRO), University of Oklahoma, which is affiliated with the National Severe Storms Laboratory (NSSL). He is a member of the Advanced Radar Techniques team in NSSL’s Radar Research and Development Division. His research interests are in the area of signal processing with applications to phased array and Doppler weather radars, including range oversampling processing, adaptive beamforming, radar variable estimation, and radar interference.

Research Focus

Digital Signal Processing
Phased Array Radar
Doppler Weather Radar
Adaptive Beamforming
Radar Variable Estimation
Electromagnetic Interference

CIWRO Research Themes

Weather Radar and Observations

Publications

Warde, D., D. Schvartzman, C. D. Curtis, 2023: Generalized Multi-Lag Estimators (GMLE) for Polarimetric Weather Radar Observations. IEEE Transactions on Geoscience and Remote Sensing, 61, 1–12, doi:10.1109/TGRS.2023.3278489.
Boettcher, J., S. Torres, F. Nai, C. Curtis, D. Schvartzman, 2022: A Multidisciplinary Method to Support the Evolution of NWS Weather Radar Technology. Weather and Forecasting, 37, 429–444, doi:10.1175/WAF-D-21-0159.1.
Curtis, C. D., S. M. Torres, 2021: The Impact of Reflectivity Gradients on the Performance of Range-Oversampling Processing. J. Atmos. Oceanic Technol., 38, 1343–1352, doi:10.1175/JTECH-D-20-0201.1.
Nai, F., J. Boettcher, C. Curtis, D. Schvartzman, S. Torres, 2020: The Impact of Elevation Sidelobe Contamination on Radar Data Quality for Operational Interpretation. Journal of Applied Meteorology and Climatology, 59, 707–724, doi:10.1175/JAMC-D-19-0092.1.
Nai, F., S. Torres, C. Curtis, 2020: Mitigating the Impact of Azimuthal Sampling on the Strength of Radar-Observed Circulations. J. Atmos. Oceanic Technol., 37, 1103–1116, doi:10.1175/JTECH-D-19-0152.1.
Torres, S. M., C. D. Curtis, 2020: Revisiting the Optimum Receiver Filter Bandwidth for Range-Oversampling Processing. J. Atmos. Oceanic Technol., 37, 507–515, doi:10.1175/JTECH-D-19-0057.1.
Schvartzman, D., C. D. Curtis, 2019: Signal Processing and Radar Characteristics (SPARC) Simulator: A Flexible Dual-Polarization Weather-Radar Signal Simulation Framework Based on Preexisting Radar-Variable Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12, 135-150, doi:10.1109/JSTARS.2018.2885614.

Conference presentations

Curtis, C., 2023: Speeding Up Time Series Simulations: Looping Through Signal Parameters. 40th Conference on Radar Meteorology, Minneapolis, MN, Amer. Meteor. Soc., August 29, 2023, 8B.4.
C. Curtis, 2022: A New Approach for Addressing Correlation Coefficient Estimator Bias at Low Signal-to-Noise Ratios. ERAD 2022, Locarno, Switzerland, RSP.P1.
Curtis, C. D., J. B. Boettcher, F. Nai, D. Schvartzman, and S. M. Torres, 2019: Using the SPARC Simulator to Study Data Quality and Adaptive Scanning for SENSR. Phased Array Symposium at the 99th AMS Annual Meeting, Phoenix AZ, USA, Amer. Meteor. Soc., January, 8, 2019.
Curtis, C., and S. Torres, 2019: How Do Reflectivity Gradients Affect the Performance of Range Oversampling Processing? 39th International Conference on Radar Meteorology, Nara, Japan, Amer. Meteor. Soc., September 16, 2019.

Christopher Curtis

Christopher Curtis

Research Scientist III

Research
Scientist III