Rapid Variations in Atmospheric Refractivity Revealed by an SBand Phased Array Weather Radar

1
The Atmospheric Radar Research Center (ARRC) at
the University of OklahomaAn Interdisciplinary
Approach to Weather Radar Research and
EducationDr. Bob Palmer Tommy C. Craighead
Chair and Professor, School of MeteorologyAdjunct
Professor, School of Electrical and Computer
EngineeringUniversity of Oklahoma
Operating under the auspices of the University of
Oklahomas strategic radar initiative and in
close collaboration with other Norman research
units, interested faculty members from the
Schools of Meteorology and Electrical/Computer
Engineering have united to form an
interdisciplinary team of scientists and
engineers to solve challenging radar research
problems and prepare the next generation of
students.
Penn State Visit, Nov 2007
2
ARRC Organizational Structure
National Weather Center Building
One Partners Place
3
Highlights of the ARRC

• An interdisciplinary group of ten faculty members
  from Meteorology and Electrical Engineering
• Leading effort in OUs Weather Radar Curriculum
  with enrollments of over 300 credit hours/year
  being educated in radar meteorology and
  engineering
• Leading OUs effort in radar hardware research
  through its Radar Innovations Laboratory (RIL)
• Currently developing an advanced
  Electromagnetic/Microphysics Laboratory (EML)
• Partnered with the National Severe Storms
  Laboratory on phased array radar technology for
  weather observations
• Work closely with NWS Radar Operations Center on
  several projects related to the WSR-88D
• Involved in the development of Kessler Farm Field
  Laboratory
• SMART-R program

4
Overview of ARRC Activities
5
Outline

• Inter-Disciplinary Educational Program in Weather
  Radar at the University of Oklahoma
• Overview of ARRC Research Activities
• Radar Simulator Design
• Advanced Radar Techniques and Signal Processing
• Wind Profiling Radars and Field Work
• Development of the ARRC Laboratories
• Radar Innovations Laboratory (RIL)
• Electromagnetics/Microphysics Laboratory (EML)

6
Over-Arching Educational Goals

• Provide a comprehensive interdisciplinary
  education in weather radar at both undergraduate
  and graduate levels
• Extensive hands-on experience for students
• Combine talents/interests of faculty in the
  School of Meteorology, School of Electrical and
  Computer Engineering, and Norman scientists

7
Design of Knowledge Expectations

• Started with clean slate (fall 04)
• 1 existing Radar Meteorology course (SoM)
• 1 existing Weather Radar Signal Processing course
  (ECE)
• Assessed backgrounds of prospective students
  (Meteorology and ECE)
• Mathematics same (DEQ 1)
• Physics same
• ECE students need basic physical meteorology
• Meteorology students need electromagnetics and
  signal processing
• Fundamental Question
• What should an expert in weather radar and
  instrumentation know?

8
ARRC Educational Program
During the 05-07 academic years, Alexander
Ryzhkov, Sebastian Torres, Rich Ice, Kurt Hondl,
Terry Schurr provided extensive lectures in our
radar classes.
9
Example Course

• Weather Radar Theory Practice (METR/ECE
  4673/5673)
• Motivation and Historical Perspective
• Electromagnetic Waves and Propagation -
  introduction to basic physical meteorology
• Weather Radar Design Principles
• Signal Statistics and Weather Radar Equation -
  introduction to random processes
• Doppler Spectra of Weather Signals - introduction
  of Fourier theory
• Doppler Moment Estimation - Time Frequency
  Domain
• Techniques for Improved Data Quality

This graduate-only course has had significant
interest from students Fall 05 (25 met, 5 ECE),
Fall 06 (11 met, 9 ECE), Fall 07 (8 met, 9 ECE)
Extensive analysis of raw time-series (I/Q) data
from KOUN, PAR, WSR-88Ds, and CASA using
student-generated Matlab code.
10
Radar Courses Offered Spring 2008 Weather Radar
and Instrumentation Program School of
Meteorology and School of Electrical Computer
Engineering The inter-disciplinary curriculum
continues in Spring 2008 providing students with
a unique and comprehensive experience in weather
radar and meteorological instrumentation.
Emphasis is placed on providing a hands-on
experience for students with data from several
radars here in the Norman community, including
the Phased Array Radar, KOUN Polarimetric Doppler
Radar operated by the National Severe Storms
Laboratory and the X-band CASA radars. New this
year is Microwave Engineering providing a
thorough background in radar hardware design.
Wx Radar Applications (METR/ECE
5683) Instructor Dr. P. Chilson
(chilson_at_ou.edu) Time MWF 300-350 pm
Radar Meteorology (METR 4624) Instructor Dr. M.
Biggerstaff (drdoppler_at_ou.edu) Time MWF
1100-1150 am F 300-600 pm
Radar Engineering (METR/ECE 4663/5663) Instructor
Dr. T. Yu (tyu_at_ou.edu) Time MW 630-745 pm
Antennas (ECE 5973 Sect 001) Focus on Phased
Arrays Instructor Dr. J. Crain (crain_at_ou.edu)
Time MW 130-245pm
RF Microwave Engineering (ECE 4973/5973 Sect
961) Instructor Dr. Y. Zhang (rockee_at_ou.edu)
Time TTh 830-945 am
Visit http//arrc.ou.edu for more details
11
Outline

• Inter-Disciplinary Educational Program in Weather
  Radar at the University of Oklahoma
• Overview of ARRC Research Activities
• Radar Simulator Design
• Advanced Radar Techniques and Signal Processing
• Wind Profiling Radars and Field Work
• Development of the ARRC Laboratories
• Radar Innovations Laboratory (RIL)
• Electromagnetics/Microphysics Laboratory (EML)

12
Weather Radar Simulator for Signal/Array
Processing Studies
Standard Beamforming

• Would like to develop/study advanced signal/array
  processing algorithms using realistic, Level-I,
  time-series radar data
• Real experimental data are not controlled or
  flexible
• Solution is an advanced radar simulator using
  high-resolution numerical weather simulation data
  as input fields

Point Target
Adaptive Beamforming
Weather
Simulated multi-function phase array antenna 155
elements 17 degree coverage 10,000 scatterers
Example simulator output with mixed weather and
point target
Possible Applications

• Multi-function (weather surveillance and target
  tracking)
• Neural network training under varying conditions
• Simulation of advanced radar designs (phased
  arrays, multi-frequency, etc.)
• Filter design for clutter mitigation
• Resolution enhancement using interferometry/deconv
  olution
• Optimization of beam scanning strategies using
  phased array radars

Conceptual diagram of model-based radar simulator
capable of simulation of realistic, complex
time-series data
OU Contact R. Palmer
13
Profiling Radar Simulator Based on LES
Time Series Spectral Examples
1210x1210x1600 m3

• LES Variables
• Mean wind components (u,v,w)
• Subgrid turbulent kinetic energy (E)
• Specific humidity (q)
• Potential Temperature (?)

OU Contacts R. Palmer, P. Chilson, E. Fedorovich
14
Turbulence Kinetic Energy
Five-Beam Doppler Beam Swinging
Spatial sampling of DBS method a major concern
15
Turbulent Momentum Fluxes

• Vertical kinematic momentum flux components
• Zonal component compares well with average LES
• Longer temporal averaging required although may
  be dependent on wind direction

16
Outline

• Inter-Disciplinary Educational Program in Weather
  Radar at the University of Oklahoma
• Overview of ARRC Research Activities
• Radar Simulator Design
• Advanced Radar Techniques and Signal Processing
• Wind Profiling Radars and Field Work
• Development of the ARRC Laboratories
• Radar Innovations Laboratory (RIL)
• Electromagnetics/Microphysics Laboratory (EML)

17
National Weather Radar Testbed NWRT

• Centerpiece of NWRT is the Phased Array Radar
  (PAR), which is an S-band, klystron-based radar
  using a SPY-1A phased array antenna
• NOAAs National Severe Storms Laboratory (NSSL)
  operates the PAR on the North Campus of the
  University of Oklahoma
• Major goal is to improve severe storm warning
  lead time using phased array radar
• Provide rapid update data for assimilation into
  numerical models
• The NWRT provides a location for
  testing/validation of advanced weather radar
  processing algorithms
• Ultimately, the goal is to perform multi-mission
  tasks including weather surveillance, aircraft
  tracking, etc.

18
Phased Array Radar (PAR)
USAs first research facility dedicated to phased
array radar meteorology
19
Measurement of Moisture Fields Using Ground
Clutter Targets

• Conventional radar processing does not allow
  measurement of moisture
• Moisture fields extremely important for
  forecasting storm initiation
• Moisture retrieval (similar to Fabry Method) has
  been implemented on several Norman radars KOUN
  (dual-pol), PAR, KCRI (ROC), KTLX (operational),
  CASA (X-band, magnetron)

OU Contact R. Palmer
20
PAR/Mesonet Comparison
5-minute temporal sampling
21
Retreating Dryline

• Dryline retreated across refractivity domain
  between 0230 and 0700 UTC (April 23, 2007)
• Refractivity field showed a strong gradient of N
  across the domain
• Refractivity change field showed increasing
  refractivity values which correspond to
  increasing dewpoint temperatures at the Mesonet
  stations

22
Outflow Boundary Case

• The outflow boundary (June 10, 2007) is evident
  in the refractivity change field by the N-S
  oriented line of positive refractivity change
  values that moves westward
• Radar refractivity and Mesonet refractivity
  increased after the boundary passed

23
Spaced Antenna Interferometry (SAI)

• Conventional Doppler radars can only measure the
  radial component of the wind field
• With the Spaced Antenna Interferometry (SAI)
  technique, it may be possible to simultaneously
  measure the complete wind field
• NSSL/LMCO has activated the azimuth difference
  channel, which is the first step in the SA
  implementation

Azimuth SA
OU Contact G. Zhang
24
Spaced Antenna Interferometry (SAI)

• SPY-1 three channels
• Sum
• Azimuth difference
• Elevation difference

Azimuth SA
Elevation SA
Dual-beams to separate shear and turbulence
Cross-correlation peak shifts due to signal
delay passing over antennas from R1 to R2
25
Weather Observations Using Monopulse Processing
on NWRT
Sum ABCD ?az (AC)-(BD) ?ze (AB)-(CD)
OU contact T. Yu
26
Beam Multiplexing (BMX)
Limitation of Scan Rate in Weather Radar
Increase rotational rate ? degrade data accuracy
Goal Increase the data update time and maintain
the data accuracy
0o
BMX is developed to exploit the idea of
collecting independent samples and maximizing the
usage of radar resources
Sample time
1o
2o
13o
OU Contact T. Yu
27
Beam Multiplexing Implementation
Applications of BMX to weather observations are
demonstrated using the PAR and the results
indicate that an average improvement factor of
two to four can be obtained for SNR higher than
10 dB.
It is evident that the gross structures of the
reflectivity and velocity from BMX and SS are
consistent.
28
Adaptive Array Processing Techniques for Clutter
Mitigation
Effects of motion of strong clutter on
reflectivity and Doppler field

• BMX causes problem for conventional temporal
  filters
• Compare different processing schemes
• Conventional Fourier beamforming
• Adaptive Capon
• Capon w/ sidelobe canceling elements
• Determine possible biases in estimated moment
  values

Model employed in advanced radar simulator
Possible Applications
Scenario for processing the time-series data

• Adaptive bias removal of intermittent clutter in
  both main and sidelobes
• Improved angular resolution of aircrafts for
  tracking

OU Contact R. Palmer
29
Demonstration of Advanced Array Processing for
Clutter Mitigation
Boundary layer echo power fields from the various
techniques. Note that the adaptive techniques
provide superior clutter suppression for both
ground and moving biological targets.
Turbulent Eddy Profiler 915 MHz Profiling Phased
Array
30
Mitigation of Non-Stationary Clutter From Wind
Turbine Farms

• Renewable energy production is becoming
  increasing important
• Wind farms cause non-stationary clutter signals,
  adversely affecting the operation of military,
  air traffic, and weather surveillance radars
• Conventional ground clutter filters are
  ineffective for mitigating clutter signals from
  rotating blades

Clutter Signal
WSR-88D KDDC
Wind Farm
Spectral processing with non-linear filtering may
prove important for analysis and mitigation of
wind turbine clutter
Current Study Using WSR-88D Radar
Gray County Wind Farm - 170 turbines (near Dodge
City, Kansas)
OU Contact R. Palmer
31
Interesting Scattering EffectsKTFX, Multi-Trip
and Multi-Scatter Echoes
4-Way Trip
Primary
Multi-Turbine Interaction Three-Body Scatter
Spike
Multi-Trip Echoes
32
Interpolation Method

• Global Interpolation using a Radial Basis
  Function, weights are determined by the distance
  between the points
• Use the multiquadric method Hardy, 1971

33
Pulse Compression Development forWeather Radar
Applications

• Examine pulse compression as a means of
  recovering lost range resolution caused by T/R
  module power limitations inherent to phased array
  radar systems
• Incorporate phase coding capabilities into the
  ARRC Weather Radar Simulator
• Test the performance of pulse compression under
  controlled conditions
• Test matched and mismatched filtering strategies
  for range sidelobe mitigation
• Investigate the effects of pulse compression on
  tornado detection algorithms
• Determine the impact of integrating pulse
  compression into phased array weather radar
  systems

General Pulse Compression Process
Tornado Signature
OU Contact P. Chilson
34
Advanced Algorithms for Accurate and Early
Tornado Detection
Distinct tornado spectral signatures can
facilitate the detection
OU contact T. Yu
35
Advanced Algorithms for Accurate and Early
Tornado Detection
36
Quantitative Precipitation Estimation (QPE)

• Polarimetric radar measurements lead
• accurate QPE (rainfall rate) and detailed
  information of microphysics such as
• number concentration
• median volume diameter
• shape of drop size distribution
• evaporation rate and
• accretion rate

Electromagnetic wave scattering
from non-spherical hydrometeors is different for
horizontal and vertical polarization, which can
be used to accurately characterize
cloud/precipitation microphysics
KOUN

• In addition to radar reflectivity (Z),
• polarimetric weather radars also measure
• differential reflectivity (ZDR)
• cross-correlation coefficient (?hv)
• specific differential phase (KDP)

OU Contact G. Zhang
Ultimate Goal Data Assimilation of Dual-Pol
Parameters
37
MULTI-FUNCTION RADAR FROM GROUND TO AIRBORNE
The motivations of airborne polarimetric array
Ground-based phased array is proven successful
for both meteorological study and point-target
tracking. Airborne phased array will also have
multi-function capability and shorter range
(localized and in-situ), lighter weight, higher
resolution, and faster data rate. We address
the challenge detecting and separating multiple
mixed-hazards
using a unified software/hardware
architecture
rain ice and wind hazards
Comprehensive Hazard map display Hazard
region, Hazard classification, Hazard
index, Possible air-traffics, Flight path
advisory
OU Contact R. Zhang
38
PROFESSING FLOW
39
Outline

• Inter-Disciplinary Educational Program in Weather
  Radar at the University of Oklahoma
• Overview of ARRC Research Activities
• Radar Simulator Design
• Advanced Radar Techniques and Signal Processing
• Wind Profiling Radars and Field Work
• Development of the ARRC Laboratories
• Radar Innovations Laboratory (RIL)
• Electromagnetics/Microphysics Laboratory (EML)

40
Combined Profiler and Polarimetric Weather Radar
Studies of Precipitation
Range Time Intensity Plots
SNR
Rad Vel
Spec Width
Z
ZDR
Corr
Doppler Spectra of Raindrop Terminal Velocities
Retrieved Vert Velocity
DSDs
OU Contact P. Chilson
41
Digital Beamforming Studies of Precipitation
Time history of echo power showing mixture of
precipitation and clear-air turbulence
Radar developed by the Univ of Massachusetts.
Univ of Massachusetts
Array configuration designed to maximize angular
resolution using a sparse array
A 2.5-min sequence of three-dimensional conical
images of isolated precipitation (blue) and
clear-air turbulent (yellow) echoes. The
isosurfaces where obtained at power levels of
52.5 dB (precipitation) and 45.8 dB (clear-air).
OU Contact R. Palmer
42
Interaction of Precipitation and Wind
Field/Turbulence

• Precipitation descends into turbulent layer at
  1.2 km
• Dissipation occurs below 1 km possibly caused by
  turbulent breakup?
• Significant updraft below 1 km (0.5 ms-1)
• Other possibilities include evaporation, Doppler
  sorting, or advection

43
Atmospheric Research at theOU Kessler Farm Field
Laboratory
Mesonet Tower
PicoNet Site
OU Contact P. Chilson G. Zhang
44
Hurricane Dynamics Using Mobile Radar

• Flooding from heavy rain is leading cause of loss
  of life from land-falling hurricanes
• Population along threatened coastal region
  exceeds infrastructure needed for timely
  evacuation
• Precipitation forecasting during landfall a
  complex interaction between hurricane dynamics,
  boundary layer changes, and environmental
  characteristics

OU Contact M. Biggerstaff
45
Outline

• Inter-Disciplinary Educational Program in Weather
  Radar at the University of Oklahoma
• Overview of ARRC Research Activities
• Radar Simulator Design
• Advanced Radar Techniques and Signal Processing
• Wind Profiling Radars and Field Work
• Development of the ARRC Laboratories
• Radar Innovations Laboratory (RIL)
• Electromagnetics/Microphysics Laboratory (EML)

46
ARRC Laboratory Facilities
Vision A premier facility for designing,
fabricating, and testing prototype radars, and
conducting radar-related research and education,
in support of the Radar Strategic Initiative and
related programs
47
Layout of Laboratories
RIL
EML

• Approximately 4000 sq ft in 1PP
• Office space for Technical Manager, Faculty,
• and several students
• 1100 sq ft Radar Innovations Lab
• Small RF Shielded Screen Room
• 900 sq ft Electromagnetics/Microphysics Lab

48
Radar Innovations Laboratory

• Opened March 2007
• 4000 sq ft lab space
• 1.3M value of test equipments and software
• Up to 50 GHz test and fabrication capability
• Shielded screen room and EM chamber
• Dedicated to radar technology RD

• Current Projects
• High-speed digital receivers (NASA)
• X-band airborne weather radar (AF/NASA)
• 8-channel receiver for PAR (NSF-MRI)
• Profiling radar sidelobe cancellation
• X-band mobile radar (dual-pol, imaging radar)
• Controlled in-door dual-pol phased array
  experiments (NOAA, LMCO)
• X-band, dual-pol CASA radar (NSF ERC)

49
Electromagnetic Microphysics Laboratory
Absorbing materials
Control computer
Rotary stage
Tx horn Low-sidelobe
Network analyzer
External hardware
Rx horn Dual-polarized
hydrometeors
HP system cabinet
Simple, Fast multi-channel measurement with
E8464B network analyzer
50
Summary

• With significant support from the OU
  administration, a group of interested faculty
  members has organized into the Atmospheric Radar
  Research Center (ARRC)
• A diverse portfolio of research and educational
  interests are represented by the ARRC membership
• The Radar Innovations Laboratory (RIL) and the
  Electromagnetics/Microphysics Laboratory (EML)
  have recently been established under the ARRC
  umbrella to support enterprise-wide research and
  educational activities
• It is our intention that the ARRC can open a
  new era of collaboration within the Norman radar
  community and with partners from other
  universities and the private sector