Post on 10-Aug-2021
Radar Basics &
Interpretation
Rita Roberts and James Wilson National Center for Atmospheric Research
Training Workshop on Nowcasting Techniques
Buenos Aires, Argentina
5 Aug 2013
Radar Principles
• Radio wave energy is transmitted ...
• ...and scattered back
Radar Principles
• Radio wave energy is transmitted ...
• ...and scattered back
Targets
insects
Ground Targets
Strong gradients in temperature/moisture
Precipitation particles
Planes
Smoke
Clouds
Radar Reflectivity Signatures
Storm Echo
Clear Air Echoes:
Convergence Boundaries
5 hour
movie loop
Radar
reflectivity
data from
one radar
Power
received
at radar
from targets Radar
Properties
Range
of
target
Radar Reflectivity
Radar Equation
Diameter
Of targets
Radar Reflectivity
Z of 729 1 mm size drops = Z of one 3 mm size drop
A single radar pulse volume A single radar pulse volume
Rainfall Estimation
Rainfall rate = (Z / a)1/b
Where
Z is reflectivity
a, b are radar coefficients
Taiwan 24 July 2013
10 min update
Monthly rainfall for February 1997
25 50 75 100 150 200 250 300 500 mm
Courtesy Clive Pierce
Rain gauges
(3494 gauges used) Radar
Radar is a quantitative tool - MUST accurately
measure the fixed and variable quantities in the
radar equation to get
Rainfall rate = (Z / a)1/b
Requires well trained and motivated engineers
Radar reflectivity
and
THE DOPPLER EFFECT
Measures the motion of the targets
away from or towards the radar (called radial velocity)
Vertical wind profile
can be diagnosed
from Doppler
velocity scan
Winds and Low Level Jets
Velocity Azimuth Display (VAD)
1 1
1,
1
1,
1
1,
2
cos(azimuth_angle) sin(azimuth_angle)
1where
2cos(azimuth_angle)
2sin(azimuth_angle)
convergence = -2 /(range cos (elevation))
rvad o
o ri
i N
ri
i N
ri
i N
o
v a a b
a vN
a vN
b vN
a
Radar
Using a Velocity Azimuth Display (VAD) Technique,
a vertical profile of the wind can be computed
Divergence Basic Single Doppler
Radar Velocity Signatures
Convergence
Rotation
Multiple Doppler Radar Wind Retrieval
Clear Air Convergence Features
• Gust fronts
• Horizontal Rolls
• Gravity waves
• Moisture boundaries
or “dry lines”
GUST FRONTS
Arc of blowing dust
Reflectivity “thin lines”
Gust Fronts
Horizontal Convective rolls
Satellite Visible
Radar Reflectivity
By concentrating low-level moisture into specific regionsd
Horizontal Convective rolls modify local stability
Weckwerth
Reflectivity at 1.1 deg elevation Radial Velocity at 1.1 deg elevation
Sea Breeze
Front
Horizontal
Convective
Rolls
Roll are
aligned with
low-level wind
Reflectivity at 2.6 deg elevation
Cumulus
clouds
(Cumulus
Clouds)
Radar “first echoes”
Non-precipitation radar features utilized in
convective storm nowcasting
Atmospheric
Bores
A wave induced into a stable
layer by a thunderstorm
outflow that can initiate other
storms
Sun and Crook
2001, Wea &
Forecasting
Wind fields retrieved from single Doppler radar
Radar reflectivity
and radial velocity
information are
assimilated into a
numerical cloud
model.
High resolution
winds help to
identify gust
fronts and other
convergence
boundaries.
4-D Variational Doppler Radar Analysis System (VDRAS)
Reflectivity Field Convergence Field
Targets
insects
Ground Targets
Strong gradients in temperature/moisture
Precipitation particles
Planes
Smoke
Clouds
RADAR REFRACTIVITY (N)
Frederic Fabry, C. Frush, I. Zawadzki and A.
Kilambi, Jtech. 1997
Near-surface index of refraction measurements can be made
using radar phase measurements from ground targets
Temperature
N = 77.6 P + 3.73 x 105 e T T2
Water vapor Refractivity Pressure
1 g/kg change in moisture ~ 4 N units
Radar Refractivity N (Water Vapor)
Increasing
Moisture
Evolution of low-level moisture
Relationship of near-surface water vapor
with the underlying terrain.
• (a) Commonly observed moisture field in early
afternoon having a broad pattern similar to the
orientation of the network of rivers (and dry
creek beds).
•Increase in moisture as gust front moves into
the heart of the Platte Valley in a region of
heavily irrigated fields.
a) 20:06 UTC
b) 23:02 UTC
R.Roberts et al, BAMS
0.0 240 120
Range (km)
Feature reflectivity (dBZ) range (km)
Insects -10 to 20 50-150
Non-precipitating -10 to 5 60
cumulus
Boundaries 10 to 35 120
Radar detection of
clear-air, boundary-
layer features
Radar Detection of Severe
Weather
Microbursts
Strong, potentially damaging,
thunderstorm outflows of small
spatial and temporal scales
NIMROD Experiment
Chicago, Illinois 1978
First experiment to study wind
shear using Doppler radars
Discovered extremely high winds (35 knots) near the ground over a very small (10 km) distance
Chicago O’Hare
Airport
Approaching O’Hare
airport
A few downbursts were detected by
radar during NIMROD, but it was still
considered a very rare event…..
Fujita’s Conclusion:
Eastern Flight 66 Crash was
caused by strong wind shear.
He called this type of wind shear
a Downburst or Microburst.
On radar, microbursts have these characteristic wind signatures and time evolution:
Time = 0 Only a hint of storm
downdraft hitting the
surface Time = 2 min Downdraft and outflow
spreading along the
ground in opposite
directions
Time = 5 min Wind speed is
strengthening in both
directions
Time = 7 min Wind change associated
with spreading outflow is
greatest at this time
Time = 9 min Wind speeds are
decreasing
Evolution of a microburst on Doppler radar
Radar is located here
Microburst 17 May 2008
Radar Reflectivity Radar Radial Velocity
Hailstorms
3-Body Scattering
or
“Flare Echoes”
More commonly observed on
C-Band (5 cm wavelength )
radars
C-Band Reflectivity
C-Band Radial Velocity
Schematic of 3-body scattering
3-body scattering
Hailstorm in Brisbane, Australia
8 February 2008
Flare Echo Signatures
Hail Core
Re-circulating precipitation
caught up in updraft
Storm Updraft
Storm downdraft and
downburst
WSR-88D
Hail Algorithms
Probability of
Hail (POH)
Probability of
Severe Hail
(POSH)
Hail Size
Storm Top
Divergence
Cold Fronts
Carbone et al., JAS, 1983
Reflectivity Radial Velocity
Tornado Tornado
vortex
circulation
Interaction of cold front with horizontal rolls
Squall Lines
Reflectivity Radial Velocity
Washington D.C.
60 min
storm
extrapolatio
n
BOW ECHO
Squall line
approaches
Washington D.C. Washington D.C.
Bow echo forms
Boundary layer winds
retrieved from the
Variational Doppler Radar
Assimilation System
(VDRAS) show strong rear-
inflow intrusion, intense
leading edge winds and
book-end vortices
associated with the bow
echo.
Cyclonic book-end vortex
Anti-cyclonic book-end vortex
Radial Velocity Reflectivity
Mesocyclone Mesocyclone
Supercell
Storms
Reflectivity
Tornado
(3 May 99 - Oklahoma)
Courtesy Don Burgess
RadialVelocity
Tornado
(3 May 99 - Oklahoma)
Courtesy Don Burgess
Squall
line
Severe Weather
Tornado -
producing
storms
Asian Mei-Yu (cold front)
Mesoscale Convective
System
14 June 2008
Accurate detection,
tracking, and
monitoring of these
complex systems is
crucial for prediction of
heavy rainfall
Single polarization versus dual-
polarization radar
Single Polarimetric Radar
Dual Polarimetric Radar
• Microphysical
information on
storms
• More detail on
storm structure
• Helps discriminate
between hail,
grauple, large and
small raindrops
Advantages of dual-polarization radars
Single and Dual-polarization Fields
1. Mean Reflectivity (Zhh)
2. Mean Differential Reflectivity (Zdr)
3. Mean Specific Differential Phase (KDP)
4. Mean Copolar Correlation Coefficient (Rhohv)
5. Mean Linear Depolarization Ratio (LDR)
6. Particle ID Field (PID)
Storm intensity, severity
High correlations raindrops
Storm and precipitation structure and evolution
Types of particles
Precipitation rate, accumulation
Differentiates between hail, ice and drops
Advantages of dual-polarization radars
08:45 UTC (16:45 LT)
Reflectivity Radial
Velocity
Zdr Particle ID
Rain/hail Heavy rain
updraft
Large
drops
• KDP shows values exceeding 2o /km, indicating copious amounts of liquid water/oblate drops
• KDP-derived rain rates estimate 20 mm/hr during this time
KDP
KDP
KDP
In order automatically detect these radar features
and accurately nowcast precipation rates and
precipitation accumulations, you must address…..
• Data quality issues
• Have dedicated engineering expertise for radar maintenance
• Accurate extrapolation of radar features
• Blending of radar and other observations with Numerical
Weather Prediction (NWP) fields
These are the topics that will be covered over the next few days