A Doppler Radar Emulator and its Application to

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

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

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

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

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

Capabilities Ø Azimuthal Resolution Ø Range Resolution Ø Attenuation Ø Range Aliasing Ø Velocity Aliasing Ø Anomalous Propagation Ø Antenna Sidelobes

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

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

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

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

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

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

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

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

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

Capabilities – Radar Characteristics Exp. λ (cm) Beamwidth (deg) PRF (Hz) control 10 1 1500 OS 10 1 GS 10 NSL Pulse Length (μs) Rot. Rate (deg s-1) Pulses Per Rad. Gate Length (m) 1. 5 20 75 250 1500 1. 5 15 50 250 1 1500 . 75 20 75 125 10 1 1500 1. 5 20 75 250 BW 10 2 1500 1. 5 20 75 250 NY 10 1 1000 1. 5 20 50 250 X 3 1 1500 1. 5 20 75 250 ST 10 1 1500 1. 5 20 75 250

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

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

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

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

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

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

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

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

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

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

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

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

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

Tornado Detection – Radar Characteristics Paramete r Matched Sampli ng Oversa mpl ed λ (cm) 3 3 Beamwidt h (deg) 2 2 PRF (Hz) 2000 Rot. Rate (deg s 1) 40 40 Pulses Per Rad. 100 50 Pulse Length . 5

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

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

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

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

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

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

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

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

Tornado Detection Results Experimen t Vmax (m s-1) ΔV (m s-1) D 2 ΔV/D ( (s-1) m ) 3 km, Matched 49. 1 93. 3 216 0. 864 3 km, Oversa mpled 55. 7 110. 6 216 1. 024 10 km, Matched 35. 2 57. 6 705 0. 163 10 km, Oversa mpled 36. 3 62. 7 529 0. 237 30 km, 31. 8 33. 4 104 0. 064

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

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

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

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. Questions?

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

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

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

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