Formal publications

Formal publications go through a strict review process known as scholarly peer review, or simply peer review. Peer review helps maintain scientific standards, improves the quality of published works, and provides credibility to scientists and engineers.

Getting a paper published in a reputable journal is a lengthy and sometimes frustrating process, but a significant accomplishment in a scientist's life, which carries a lot of weight at the time of being evaluated.

Below is a list of my formal publications. You can click on the icon to get a PDF copy of each published paper (only published or in-print papers are available). If you have trouble getting any of the papers already published, please let me know.

• Nai, F., J. Boettcher, C. Curtis, D. Schvartzman, and S. Torres, 2020: The Impact of Elevation Sidelobe Contamination on Radar Data Quality for Operational Interpretation. J. Appl. Meteor. Climatol., 59, 707–724.
• Torres, S., and C. Curtis, 2020: Revisiting the optimum receiver filter bandwidth for range-oversampling processing. J. Atmos. Oceanic Technol., 37, 507-515.
• Schvartzman, D., S. Torres, and D. Warde, 2020: The Hybrid-Scan Estimators: Exploiting WSR-88D Split Cuts to Improve the Quality of Polarimetric-Variable Estimates. J. Atmos. Oceanic Technol., 37, 299–315.
• Umeyama, A., B. Cheong, S. Torres, and D. Bodine, 2018: Orientation analysis of simulated tornadic debris. J. Atmos. Oceanic Technol., 35, 993-1010.
• Curtis, C. and S. Torres, 2017: Adaptive range oversampling processing for nontraditional radar-variable estimators. J. Atmos. Oceanic Technol., 34, 1607-1623.
• Warde, D. and S. Torres, 2017: Spectrum width estimation using matched autocorrelations. IEEE Geosci. and Remote Sensing Letters, 14, 1661-1664.
• Torres, S., C. Curtis, and D. Schvartzman, 2017: Requirement-driven design of pulse compression waveforms for weather radars. J. Atmos. Oceanic Technol., 34, 1351-1369.
• Cheong, B., D. Bodine, C. Fulton, S. Torres, T. Maruyama, and R. Palmer, 2017: SimRadar: A Polarimetric Radar Time-Series Simulator for Tornadic Debris Studies. IEEE Trans. Geosci. Remote Sensing, 55, 2858-2870.
• Umeyama, A., S. Torres, and B. Cheong, 2017: The bootstrap dual-polarimetric spectral density estimator. IEEE Trans. Geosci. Remote Sensing, 55, 2299-2312.
• Warde, D. and S. Torres, 2017: Staggered PRT Sequences for Doppler Weather Radars. Part II: The CLEAN-AP Filter. J. Atmos. Oceanic Technol., 34, 703-716.

• Schvartzman, D., S. Torres, and T. Yu, 2017: Weather Radar-Spatio Temporal Saliency: A first look at an information-theory-based human attention model adapted to reflectivity images. J. Atmos. Oceanic Technol., 34, 137-152.

• Torres, S. and D. Warde, 2017: Staggered PRT Sequences for Doppler Weather Radars. Part I: Spectral Analysis using the Autocorrelation Spectral Density. J. Atmos. Oceanic Technol., 34, 51-63.
• Nai, F., S. Torres, and R. Palmer, 2016: Adaptive beamspace processing for phased-array weather radars. IEEE Trans. Geosci. Remote Sensing, 54, 5688-5698.

• Torres, S., R. Adams, C. Curtis, E. Forren, D. Forsyth, I. Ivić, D. Priegnitz, J. Thompson, and D. Warde, 2016: Adaptive-Weather-Surveillance and Multifunction Capabilities of the National Weather Radar Testbed Phased-Array Radar. IEEE Proc., 104, 660-672.
• Torres, S. and C. Curtis, 2015: The impact of range-oversampling processing on tornado velocity signatures obtained from WSR-88D superresolution data. J. Atmos. Oceanic Technol., 32, 1581-1592.
• Torres, S. and D. Warde, 2014: Ground clutter mitigation for weather radars using the autocorrelation spectral density. J. Atmos. Oceanic Technol., 31, 2049-2066.
• Curtis, C. and S. Torres, 2014: Adaptive range oversampling to improve estimates of polarimetric variables on weather radars. J. Atmos. Oceanic Technol., 31, 1853-1866.
• Warde, D. and S. Torres, 2014: The autocorrelation spectral density for Doppler-weather-radar signal analysis. IEEE Trans. Geosci. Remote Sensing, 52, 508-518.
• Curtis, C. and S. Torres, 2013: Real-time measurement of the range correlation for range oversampling processing. J. Atmos. Oceanic Technol., 30, 2885-2895.

• Ivić, I, C. Curtis, and S. Torres, 2013: Radial-based noise power estimation for weather radars. J. Atmos. Oceanic Technol., 30, 2737-2753.
• Nai, F., S. Torres, and R. Palmer, 2013: On the mitigation of wind-turbine clutter for weather radars using range-Doppler spectral processing. IET Radar, Sonar & Navigation, 7, 178-190.
• Torres, S. and C. Curtis, 2013: The importance of accurately measuring the range correlation for range oversampling processing. J. Atmos. Oceanic Technol., 30, 261-273.
• Torres, S. and C. Curtis, 2012: The impact of signal processing on the range weighting function for weather radars. J. Atmos. Oceanic Technol., 29, 796-806.
• Curtis, C. and S. Torres, 2011: Adaptive range oversampling to achieve faster scanning on the National Weather Radar Testbed Phased Array Radar. J. Atmos. Oceanic Technol., 28, 1581-1597.
• Heinselman, P. and S. Torres, 2011: High-temporal resolution capabilities of the National Weather Radar Testbed phased-array radar. J. Appl. Meteor., 50, 579-593.
• Reinoso-Rondinel, R., T.-Y. Yu, and S. Torres, 2010: Multifunction phased-array radar: time balance scheduler for adaptive weather sensing. J. Atmos. Oceanic Technol., 27, 1854-1867.
• Hood, K., S. Torres, and R. Palmer, 2010: Automatic detection of wind turbine clutter for weather radars. J. Atmos. Oceanic Technol., 27, 1868-1880.
• Torres, S., R. Passarelli, A. Siggia, and P. Karhunen, 2010: Alternating dual-pulse, dual-frequency techniques for range and velocity ambiguity mitigation on weather radars. J. Atmos. Oceanic Technol., 27, 1461–1475.
• Le, K., R. Palmer, B. Cheong, T. Yu, G. Zhang, and S. Torres, 2010: Reducing the effects of noise on atmospheric imaging radars using multilag correlation, Radio Sci., 45, RS1008.
• Palmer, R., M. Yeary, M. Biggerstaff, P. Chilson, J. Crain, K. Droegemeier, Y. Hong, A. Ryzhkov, T. Schuur, S. Torres, T.Y. Yu, G. Zhang, and Y. Zhang, 2009: Weather Radar Education at the University of Oklahoma - An Integrated Interdisciplinary Approach. Bull. Amer. Meteor. Soc., 90, 1277–1282.
• Torres, S., 2009: Processing of oversampled signals in range on polarimetric weather radars with mismatched channels . J. Atmos. Oceanic Technol., 26, 1289-1301.
• Le, K. D. , R. D. Palmer, B. L. Cheong, T. Y. Yu, G. Zhang, and S. Torres, 2009: On the use of auxiliary receive channels for clutter mitigation with phased array weather radars. IEEE Trans. Geosci. Remote Sensing , 47, 272-284.
• Torres, S., W. González-Espada, 2006: Calculating 'g' from acoustic Doppler data. Phys. Teach., 44, 536-539.
• Torres, S., Y. Dubel, and D. S. Zrnić , 2004: Design, implementation, and demonstration of a staggered PRT algorithm for the WSR-88D . J. Atmos. Oceanic Technol., 21, 1389-1399.
• Torres, S., C. D. Curtis, and J. R. Cruz, 2004: Pseudowhitening of weather radar signals to improve spectral moment and polarimetric variable estimates at low signal-to-noise ratios. IEEE Trans. Geosci. Remote Sensing, 42, 941-949.
• Torres, S., and D. Zrnić , 2003: Whitening of signals in range to improve estimates of polarimetric variables. J. Atmos. Oceanic Technol., 20, 1776-1789.
• Ivić, I. R., S. Torres, and D. Zrnić, 2003: Whitening in range to improve weather radar spectral moment estimates. Part II: Experimental evaluation. J. Atmos. Oceanic Technol., 20, 1449-1459.
• Torres, S., and D. S. Zrnić, 2003: Whitening in range to improve weather radar spectral moment estimates. Part I: Formulation and simulation. J. Atmos. Oceanic Technol., 20, 1433-1448.
• DeBrunner, V., and S. Torres, 2000: Multiple fully adaptive notch filter design based on allpass sections. IEEE Trans. Signal Processing, 48, 550-552.
• Torres, S., and D. S. Zrnić, 1999: Ground Clutter Filtering with a Regression Filter. Journal of Atmospheric and Oceanic Technology, 16, 1364-1372.

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