1. A Doppler Radar Emulator and its Application to the Detection of Tornadic Signatures Ryan M. May

2. Acknowledgements  Reading Committee Dr. Michael Biggerstaff Dr. Michael Biggerstaff Dr. Ming Xue Dr. Ming Xue Dr. Robert Palmer Dr. Robert Palmer  Dr. Tian-You Yu  Curtis Alexander  Gordon Carrie

3. Motivation  Create tool that generates radar moment data for a given set of radar operating parameters  Useful for: Radar system design Radar system design Scanning strategy design Scanning strategy design Algorithm development Algorithm development Retrieval technique evaluation Retrieval technique evaluation

4. Previous Work  Zrnic (1975) simulated time series radar data using an assumed Gaussian distribution of velocities within a volume  Chandrasekar and Bringi (1987) simulated reflectivity values as a function of raindrop size distribution parameters  Wood and Brown (1997) evaluated the effects of WSR-88D scanning strategies on the sampling of mesocyclones and tornadoes  Capsoni and D’Amico (1998) simulated time series radar data using returns from individual hydrometeors within a volume

5. Radar Configuration  Wavelength  Location  Transmit Power  Antenna Gain  Antenna Beamwidth  Noise Threshold  Pulse Length  PRF  Pulses per Radial  Rotation Rate  Gate Length  Scan Angles

6. Capabilities  Azimuthal Resolution  Range Resolution  Attenuation  Range Aliasing  Velocity Aliasing  Anomalous Propagation  Antenna Sidelobes

7. Scattering  Currently, the Rayleigh approximation is used for scattering:  Rain is assumed to have a Marshall-Palmer distribution  Cloud droplets are assumed to be monodisperse

8. Emulator Design  A “pulse” is propagated through the model’s numerical output grid along the current pointing angle  This pulse is subdivided into many small, individual elements  Each element is assigned values for reflectivity, radial velocity, and attenuation factor from the model grid, using nearest neighbor sampling

9. Emulator Design (cont.) Representation of segmented pulse being matched to model grid field

10. Emulator Design (cont.)  At a given instant, two pulses are being used, allowing for the simulation of 2 nd trip echoes  For every range gate along the beam, the pulses are sampled to produce a value of returned power, Doppler velocity, and velocity variance

11. Emulator Design (cont.)  Returned power is calculated as:  Doppler velocity is the power-weighted average of all velocities for all pulse elements  The velocity variance for the pulse is the power-weighted variance of velocities for all pulse elements

12. Emulator Design (cont.)  When the returns for the specified number of pulses for a radial have been calculated, a radial of data is generated  Returned power is the average returned power for all pulses  Doppler velocity is the power-weighted average velocity for all pulses  Spectrum width is the power-weighted variance for all pulses

13. Emulator Design (cont.)  At this point, the velocity is forced to a value within the Nyquist co-interval, simulating velocity aliasing  Also, equivalent radar reflectivity factor is calculated from the returned power as:

14. Simulation Characteristics  Simulation created using the Advanced Regional Prediction System (ARPS)  Horizontal grid resolution: 50m  Stretched vertical grid (~18m at surface)  Warm rain precipitation microphysics  Produces a 200m diameter tornado with a 160 m/s change in velocity across the vortex

15. ARPS Simulation Vector Velocity, Rain Water Mixing Ratio, and Total Buoyancy

16. Capabilities – Radar Characteristics Exp.λ (cm) Beamwidth (deg) PRF (Hz) Pulse Length (μs) Rot. Rate (deg s -1 ) Pulses Per Rad. Gate Length (m) control10115001.52075250 OS10115001.51550250 GS1011500.752075125 NSL10115001.52075250 BW10215001.52075250 NY10110001.52050250 X3115001.52075250 ST10115001.52075250

17. Examples – 10cm, 1 o Beamwidth Returned Power Equivalent Reflectivity Factor Doppler Velocity Spectrum Width

18. Examples – Azimuthal Oversampling CONTROL Equivalent Reflectivity Factor CONTROL Doppler Velocity OVERSAMPLED Equivalent Reflectivity Factor OVERSAMPLED Doppler Velocity

19. Examples – Azimuthal Oversampling Equivalent Reflectivity Factor Difference (Oversampled - Orginal)

20. Examples – 125m Gate Spacing CONTROL Equivalent Reflectivity Factor CONTROL Doppler Velocity 125M GATE SPACING Equivalent Reflectivity Factor 125M GATE SPACING Doppler Velocity

21. Examples – No Sidelobes NO SIDELOBES Equivalent Reflectivity Factor NO SIDELOBES Doppler Velocity CONTROL Equivalent Reflectivity Factor CONTROL Doppler Velocity

22. Examples – No Sidelobes Returned Power Difference (Original – No Sidelobes)

23. Examples – 2 o Beamwidth Equivalent Reflectivity Factor (original) Doppler Velocity (original) Equivalent Reflectivity Factor (2 o Beamwidth) Doppler Velocity (2 o Beamwidth)

24. Examples – Low PRF Returned Power Equivalent Reflectivity Factor Doppler Velocity Spectrum Width

25. Examples – X-band (3cm) Returned Power Equivalent Reflectivity Factor Doppler Velocity Spectrum Width

26. Examples – X-band (3cm) Returned Power Difference (Original – X-band)

27. Examples – 2 nd Trip Echoes Returned Power Equivalent Reflectivity Factor Doppler Velocity Spectrum Width

28.  We’ve now seen examples of the emulator’s capabilities  Let’s move on to material that’s more…practical: detecting tornadoes From Examples to Application

29. Example Application: Tornado Detection  Emulated data for prototype CASA radars  4 Metrics for tornado intensity: Maximum velocity Maximum velocity ΔVelocity ΔVelocity Diameter Diameter Axisymmetric vorticity: 2ΔV / D Axisymmetric vorticity: 2ΔV / D  4 Ranges : 3km, 10km, 30km, 50km  Matched Sampling / Oversampling

30. Tornado Detection – Radar Characteristics ParameterMatched SamplingOversampled λ (cm)33 Beamwidth (deg)22 PRF (Hz)2000 Rot. Rate (deg s -1 )40 Pulses Per Rad.10050 Pulse Length (μs).5 Gate Length (m)100

31. Tornado – 3km, Matched Sampling Equivalent Reflectivity Factor Spectrum Width Doppler Velocity Doppler Velocity (no aliasing)

32. Tornado – 3km, Oversampling Equivalent Reflectivity Factor Spectrum Width Doppler Velocity Doppler Velocity (no aliasing)

33. Tornado – 10km, Matched Sampling Equivalent Reflectivity Factor Spectrum Width Doppler Velocity Doppler Velocity (no aliasing)

34. Tornado – 10km, Oversampling Equivalent Reflectivity Factor Spectrum Width Doppler Velocity Doppler Velocity (no aliasing)

35. Tornado – 30km, Matched Sampling Equivalent Reflectivity Factor Spectrum Width Doppler Velocity Doppler Velocity (no aliasing)

36. Tornado – 30km, Oversampling Equivalent Reflectivity Factor Spectrum Width Doppler Velocity Doppler Velocity (no aliasing)

37. Tornado – 50km, Matched Sampling Equivalent Reflectivity Factor Spectrum Width Doppler Velocity Doppler Velocity (no aliasing)

38. Tornado – 50km, Oversampling Equivalent Reflectivity Factor Spectrum Width Doppler Velocity Doppler Velocity (no aliasing)

39. Tornado Detection Results ExperimentV max (m s -1 )ΔV (m s -1 )D (m)2 ΔV/D (s -1 ) 3km, Matched49.193.32160.864 3km, Oversampled55.7110.62161.024 10km, Matched35.257.67050.163 10km, Oversampled36.362.75290.237 30km, Matched31.833.410470.064 30km, Oversampled32.342.710470.082 50km, Matched27.529.517490.034 50km, Oversampled28.538.617490.044

40. Conclusions  The large beamwidth of the CASA radars will be significant hurdle to the detection of tornadoes Oversampling does help mitigate some of this problem Oversampling does help mitigate some of this problem  These sampling issues will compound the dealiasing problems due to the low Nyquist velocity at X-band The quality of the dealiasing procedure for the data will be extremely important The quality of the dealiasing procedure for the data will be extremely important

41. Future Studies  Continue examining the detectability of tornadoes Test detection using objective algorithms Test detection using objective algorithms Examine impacts of attenuation Examine impacts of attenuation Examine data for times when storm is not tornadic Examine data for times when storm is not tornadic Examine vertical continuity Examine vertical continuity  Evaluate scanning impacts on quality of dual Doppler analysis

42. Future Development  Mie Scattering  Phased Array Antenna  Time Evolution of Model Field  Polarimetric Variables  Ground Clutter Targets

43. Questions? Capsoni, C., and M. D'Amico, 1998: A physically based radar simulator. J. Atmos. Oceanic Technol., 15, 593-598. Chandrasekar, V., and V. N. Bringi, 1987: Simulation of radar reflectivity and surface measurements of rainfall. J. Atmos. Oceanic Technol., 4, 464-478. Wood, V. T., and R. A. Brown, 1997: Effects of radar sampling on single-Doppler velocity signatures of mesocyclones and tornadoes. Wea. Forecasting, 12, 928-938. Zrnic, D. S., 1975: Simulation of weatherlike Doppler spectra and signals. J. App. Meteor., 14, 619-620.

44. Examples – 10cm, 1 o Beamwidth Returned Power Equivalent Reflectivity Factor Doppler Velocity Spectrum Width

45. Examples – 125m Gate Spacing Returned Power (control) Equivalent Reflectivity Factor Doppler Velocity Spectrum Width

46. Examples – No Sidelobes Returned Power Equivalent Reflectivity Factor Doppler Velocity Spectrum Width

47. Examples – 2 o Beamwidth Returned Power Equivalent Reflectivity Factor Doppler Velocity Spectrum Width