Radio Meteorology and Precipitation Physics
Office: Burnside Hall 810
Tel.: (514) 398-3652
Fax.: (514) 398-6115
frederic.fabry [at] mcgill.ca (Email)
McGill operates several remote sensing instruments on a continuous basis for research and monitoring purposes. These systems observe the shape, intensity, and movement of radar targets, allowing us to get a 4-D view of the state of the atmosphere and in particular of precipitation. We use these tools both to improve our understanding of precipitation microphysics and dynamics as well as to develop new methods and algorithms for short-term forecasting, or nowcasting, of severe weather.
My work spans from trying to enhance our understanding of the precipitation process to developing new instruments and techniques to make better meteorological measurements. At this time, I am focusing on the following topics:
Nowcasting of precipitation
Precipitation is one of the most difficult parameter to predict accurately, yet it is probably the one with the greatest impact on human activities. For very short term forecasts, nothing performs better than using radar data and extrapolating them in time. Short term forecasts, or nowcasts, are used for a variety of applications such as aviation weather and flood forecasting. We are interested in improving the accuracy of nowcasting as well as quantifying the quality and predicting the uncertainty of the forecasts. While improving nowcasts has obvious benefits, quantifying the uncertainty in these nowcasts is also particularly important for decision makers such as hydrologists managing dams and other flood control systems.
Remote sensing of humidity and applications
Water vapour is the fuel of storms and minute changes in the distribution of moisture can completely alter storm development. Yet water vapour distribution is a poorly measured quantity, especially at the mesoscale. We developed a radar-based technique that can provide near-surface moisture information whereby we use the change in the travel time of radar waves between fixed points (such as the ground targets observed by a radar) to infer changes in the refractive index of air caused by changes in near-surface humidity. While on one end, we are working on fine-tuning that technique and making measurements in a variety of field experiments, one the other end we are analyzing the data to see to what extent its information can be used for improving storm initiation prediction.
Mesoscale measurements by microwave radiometry
All objects emit heat, and also emit tiny but detectable amounts of microwaves. Microwave radiometry is a specialization of remote sensing that deals with the study and the use of the emissions of microwaves from the atmosphere. Microwave radiometers, the instruments that measure these emissions, are used to obtain information on temperature, humidity, and cloud amounts, fields that we have great difficulties to characterize otherwise. Until now, microwave radiometers were designed to only measure the vertical profiles of atmospheric parameters. We are currently designing and testing an instrument that scans the atmosphere much like a radar does, in an attempt to get 2-D or 3-D information on temperature, and humidity. Here too, the instrument will be used to evaluate its ability to improve severe storm forecasting, especially at the early stages of storm development.
Consult our group’s web site for more details on our activities: www.radar.mcgill.ca.
Some recent publications
Besson, L., O. Caumont, L. Goulet, S. Bastin, L. Menut, F. Fabry, and J. Parent du Châtelet, 2016. Comparison of real-time refractivity measurement by radar with automatic weather stations, AROME-WMED and WRF forecasts simulations during the SOP1 of HyMeX campaign. Quarterly Journal of the Royal Meteorological Society, 142, 138–152, doi: 10.1002/qj.2799.
Feng, Y.-C., and F. Fabry, 2016: The imperfect phase pattern of real parabolic radar antenna and data quality. Journal of Atmospheric and Oceanic Technology, 33, 2655–2661.
Feng, Y.-C., F. Fabry, and T. M. Weckwerth, 2016: Improving radar refractivity retrieval by considering the change in the refractivity profile and the varying altitudes of ground targets. Journal of Atmospheric and Oceanic Technology, 33, 989–1004, doi: 10.1175/JTECH-D-15-0224.1.
Kirshbaum, D., F. Fabry, and *Q. Cazenave, 2016. The Mississippi Valley convection minimum on summer afternoons: Observations and simulations. Monthly Weather Review, 144, 263–272.
Fabry, F., and J. Sun, 2010. For how long should what data be assimilated for the mesoscale forecasting of convection and why? Part I: On the propagation of initial condition errors and its implications for data assimilation. Monthly Weather Review, 138, 242-255.
Fabry, F., 2010. For how long should what data be assimilated for the mesoscale forecasting of convection and why? Part II: On the observation signal from different sensors. Monthly Weather Review, 138, 256-264.
Fabry, F., and A. Seed, 2009. Quantifying and predicting the accuracy of radar-based quantitative precipitation forecasts. Advances in Water Resources, 32, 1043-1049.
Roberts, R.D., F. Fabry, P.C. Kennedy, E. Nelson, J. Wilson, N. Rehak, J. Fritz, V. Chandrasekar, J. Braun, J. Sun, S. Ellis, S. Reising, T. Crum, L. Mooney, and B. Palmer, 2008. REFRACTT-2006: Real-time retrieval of high-resolution, low-level moisture fields from operational NEXRAD and research radars. Bulletin of the American Meteorological Society, 89, 1535-1548.
Campos, E.F., W. Hocking, and F. Fabry, 2008. Evaluating the effects of a space-variable reflectivity and antenna sidelobes into the radar equation. Journal of Atmospheric and Oceanic Technology, 25, 1469-1476.
Koch, S.E., W. Feltz, F. Fabry, M. Pagowski, B. Geerts, K.M. Bedka, D.O. Miller, and J.W. Wilson, 2008. Turbulent mixing processes in atmospheric bores and solitary waves deduced from profiling systems and numerical simulation. Monthly Weather Review, 136, 1373-1400.
Campos, E. F., W. Hocking, and F. Fabry, 2007: Precipitation measurement using VHF, wind-profiler radars: A multi-faceted approach to calibrate VHF radar antenna and receiver. Radio Science, 42, RS4008, doi:10.1029/2006RS003508.
Campos, E. F., F. Fabry, and W. Hocking. 2007: Precipitation measurements using VHF wind profiler radars: Measuring rainfall and vertical air velocities using only observations with a VHF radar. Radio Science, 42, RS3003, doi:10.1029/2006RS003540.
Heymsfield, A. J., G.-J. van Zadelhoff, D. Donovan, F. Fabry, R. Hogan, and A. Illingworth, 2007: Refinements to ice particle mass dimensional and terminal velocity relationships for ice clouds: part II: evaluation and parameterizations of ensemble ice particle sedimentation velocities. Journal of Atmospheric Sciences, 64, 1068-1088.
Fabry, F., 2006: The spatial structure of moisture near the surface: Project-long characterization. Monthly Weather Review, 134, 79-91.
Demoz, B., C. Flamant, T. Weckwerth, D. Whiteman, K. Evans, F. Fabry, P. DiGirolamo, D. Miller, B. Geerts, W. Brown, G. Schwemmer, B. Gentry, W. Feltz, and Z. Wang, 2006: The dryline on 22 May 2002 during IHOP_2002: convective scale measurements at the profiling site. Monthly Weather Review, 134, 294-310.
Weckwerth, T. M., C. R. Pettet, F. Fabry, S. Park, J. W. Wilson, and M. A. LeMone, 2005: Radar refractivity retrieval: Validation and application to short-term forecasting. Journal of Applied Meteorology, 44, 285-300.
Zawadzki, I., W. Szyrmer, C. Bell, and F. Fabry, 2005: Modeling of the melting layer, Part III: the density effect. Journal of the Atmospheric Sciences, 62, 3705-3723. Fabry, F., 2004: Meteorological value of ground target measurements by radar. Journal of Atmospheric and Oceanic Technology, 21, 560 573.
Fabry, F., and Keeler, R. J., 2003: Innovative signal utilization and processing. In Radar and Atmospheric Science: A Collection of Essays in Honor of David Atlas (R.M. Wakimoto and R.C. Srivastava, eds.), American Meteorological Society monograph, Chap. 8.