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