Radar Detection of Shallow Weather and Orographic Phenomena Paul Joe MSC Basic Radar 2010 20100404

Radar Detection of Shallow Weather and Orographic Phenomena

Paul Joe

MSC Basic Radar 2010

20100404

1. This module briefly explores “radar meteorology” issues of low level weather detection in a generic way.

2. Radar meteorology in complex terrain

Module Objective

Outline

• Some “back of envelope calculations” of key elements– Typical reflectivities of rain, drizzle, fog, snow

(detection issue)– Beam height (detection issue)– Beam width (quantitative and detection issues)– Sensitivity (detection issue)

• Meteorology– Drizzle– Lake Effect Snow– Orographic Precipitation

Low Level Phenomena Detectable by Radar

• Meteorological Targets– Precipitation (Rain, Snow, Hail, Drizzle)– Lake Breezes, Convergence Lines, Gust

fronts, cold pools– Index of Refraction/Humidity– Turbulence (Bragg scattering)

• Ground Clutter (not discussed here)– Building, Mountains, Forests

• Hard Targets (not discussed here)– Wind turbines, Cars, ships, airplanes, space

debris• Biological Targets (not discussed here)

– Insects, birds, bats• Electro-magnetic Targets (not discussed here)

– Other radars, RLANs, Sun, second trip echoes• Other

– Forest fires– Sea Clutter

Romanian Gust Front

General Comments – Low Scanning

• Wide variety of phenomena and intensity of targets– Turbulence (too weak) to Mountains (very intense)– From very weak to very strong (-30 dBZ to 95 dBZ)

• Different Doppler signatures– Some have 0 velocity– Some have aliased velocity (> Nyquist)

• Advanced uses of weather radar– VDRAS – variational doppler radar assimilation system– Refractivity retrieval – use of ground clutter echoes

• Quantitative Precipitation Estimation– Need low level scanning– Accurate at ranges < 80-100km

• Commonality – Limited range! – Low echo strength (generally), Low height of weather, radar

sensitivity is an issue

Drizzle

Some Radar Examples

Drizzle reported in surface observations but no radar echoes.

Drizzle in surface observationsBUT NO/Little RADAR DATA

Germany Example 1

Lang, DWD

Drizzle (mm/h) and very fewechoes

Germany Example 2

Lang, DWD

Drizzle in Finland!

Saltikoff, FMI

1. Why was drizzle observed in Finland but not Germany?

2. Why is the drizzle observed only around the radar?

3. Why is the reflectivity pattern stronger near the radar and decreases away from the radar?

4. Why is there a range limit to see drizzle?

Minimum Detectable Signal

Concept

Minimum Detectable SignalThe detection threshold (as a function of range).

Range [km]

Ref

lect

ivit

y [d

BZ

]

Probability Distribution of Reflectivity with Range (not important for this discussion). Function of Wx.

Minimum Detectable Signal (constant power)

P = C Z r2

The Radar Equation

MDS can expressed as a noise temperature or a power measurement but for meteorologist it more useful to express as reflectivity at a particular range. Typically, -1 dBZ at 50 km.

Some Radar Considerations

P = C Z r2

P = power, C = radar constant, r = range

Z = N D6

[Z] = mm6/m-3

dBZ = 10 log Z

Reflectivity Factor - Linear

Radar Equation and MDS Pmin = C Zmin(r)

r2

• The Radar measures “P” – power received• The Radar Equation converts P to Z for a given

range (r)– Radar Equation accounts for expanding beam

with range (1 /r2)• Sensitivity (or MDS) is a certain power level

– Just above the noise (hsssssss) level – In terms of P (power), it is a constant – In terms of Z (reflectivity), it is a function of

range (1 /r2)• A limitation for long range detection of weak

echoes is the radar sensitivity! – If the reflectivity of the target is below MDS

then the radar does not detect it!– Beware of artificial MDSartificial MDS! The display of the

radar data may be thresholded! Some data may not be displayed!

Range

Pow

er

Range

Ref

lect

ivy

Homework QuestionEcho Power

Size [microns or mm]

Average Intensity [mm/h, cm/h]Or Liquid Water Content [g/m3]

Number of particles in a cubic meter

Calculate Z[mm6/m3]Leave this empty if you wish.

Calculate dBZLeave this empty if you wish.

Fog 0.01mm .1 g/m^3 1x10^8 0.0001 -40

Drizzle 0.1 mm .1 g/m^3 1x10^5 0.1 -10

Rain 1 mm 1 mm/h 100 100 20

A Drizzle CalculationRadius of a drizzle drop ~= 100 microns

Rainrate of drizzle ~= 1 mm/h

Fall speed ~= 1 cm/s

Therefore,

Number of drops ~= 28,000 m^-3

Reflectivity ~= -5 dBZ

Can your radar see drizzle?

How far can you see drizzle from the radar?

So, how far can you see drizzle (-5dBZ)?Or anything else?

P = C Z r2

Minimum Detectable Signal (power)

~ 25km

-5dBZ

Can you see drizzle – part 2?The Artificial MDS Situation

7dBZ

Data in this shaded area is thresholded (not displayed)!

~ 25km

Typical Drizzle reflectivity

Reflectivity vs Range for Constant Power (1/r2)

Where does your radar fit on this diagram?

Typical Radars

Survey Question about your Radars?How well do you know your radars? What is the minimum value that you have seen on your radar and at what range?

dBZ Rainrate 20 km 50 km 100 km 150 km

20 dBZ 0.5 mm/h

15 dBZ 0.3

10 dBZ 0.16

5 dBZ 0.08

0 dBZ 0.03

Put a check in as many boxes as you want!

Are you limited by an artificial MDS?

Beam Propagation Re-visited

Beamheight Considerations

OvershootKey Concept!

0.5oBeam totally overshoots the weather beyond this range! No detection at all!

Shallow Weather

The weather is detected but the beam is not filled beyond this range, so reflectivities are quantitatively underestimated from this range and beyond

Note: the lower the beam the longer the range for detection ability!

Non-uniform beamfilling

Drizzle

Drizzle is due to warm rain process. Slow growth which results in small drops (0.1 mm, 1 mm/h)

Note: Colour scales are different!

dBZ

dBZ

ZDR

Saltikoff, FMI

Drizzle is round!

1 km

Survey: How well do you know your radars?What is the lowest elevation angle of your radars?

Minimum Elevation Angle Please put a check mark in this column

-0.5

-0.3

0.0

0.3

0.5

Summary: Drizzle in Finland!

Saltikoff, FMI

1. Why was drizzle observed in Finland but not Germany? Thresholded!

2. Why is the drizzle observed only around the radar? Sensitivity

3. Why is the reflectivity pattern stronger near the radar and decreases away from the radar? Beamfilling

4. Why is there a range limit to see drizzle? ~80-100km, function of sensitivity, beamfilling, depth of the drizzle!

5-6°C

Drizzle ,,

Unusual widespread drizzle from cloud echoes aloft. At surface only few echoes above 1dBZ. Note: change in threshold for DWD, see more drizzle!

Hamburg

Germany Example 3

Lang, DWD

Major Factors for Detection

• Radar Sensitivity – Target Reflectivity/Radar MDS combination

• Overshoot– Lowest Angle of Radar/Height of weather / Earth

Curvature combination

• Beam filling (quantitative) – Weather is too shallow or too low– Beam is very broad

• Thresholding– Artificial MDS = Minimum Displayed Signal*

FOG

Can the radar see fog?

FogSpecial Cloud/Fog Radar (35 GHz or Ka Band)

Fog has drop sizes from 10 to 30 microns, so very low reflectivities.

An operational radar has a sensitivity as -8 dBZ at 50 km.

What is the controlling factor of detecting fog for this radar?

- Sensitivity? or elevation angle? Or Artificial MDS (color table?)

Drop Size Distributions

dBZ

10 km

Non-operational

Snow

Beamheight Again

Quantitative measurements(Advanced Material)

Partial Beam Filling

Range bins that are partially beamfilled, decreasing reflectivity with range!

0.5 degree

Question: What do you think the reflectivity will look as a function of range?

0.5o

Shallow Weather

Non-uniform beamfilling

dBZ

Range

Vertical Profile of Snow Function of Range

1. Snow originates aloft but grows as it falls.

2. The same vertical profile as observed by radar at increasing range due to beam filling, beam broadening (smoothing) and Earth curvature (can’t see lowest levels)!

Quantitative Impact of Beamfilling

Michelson, SMHI

Note the fall off of values with range.

This is NOT attenuation to which this is commonly attributed.

It is a beam filling effect!

Impact of Beamwidth / Beamfilling30 day Accumulation

Example of the impact of beamwidth or beamfilling on quantitative precipitation estimation. One radar is 0.65o and the rest are 1.1o beamwidth radars. Smaller beamwidth means less beamfilling problems with range and farther quantitative reflectivity information.

0.65o

(no blue)

Patrick, EC

1.0o

(blue)

Applying the Correctionaka Vertical Profile Correction

aka Range Correction

Koistinen, FMI

Orographic

Mountain Top Radars

Germann, MCH

Freezing Level and Mountain Sited Radars

Time-Height TemperatureFreezing Level from Radiosondes

March 2008 Payerne

July 2008 Payerne

Most of the time, the radar sees snow!

Valley Radar

Whistler Mtn

Squamish

Pemberton

Winter Olympic Park

Blackcomb

H99

Distance Range to Terrain VVO

Azimuth

North East South West North

Whistler Squamish Callaghan

Ele

vati

on

An

gle

Snow

Callaghan Whistler Squamish

Whistler Doppler Weather Radar

Another View

VVO

Dave MurrayDownhill Start

What is this?

Would you see it on a mountain top radar?

Blocked flow (downslope winds)means Intenseprecipitation is on the slope and not on mountain peak

Doppler velocity: Blue means air is moving to the left or downslope

Precipitation: the intense precipitation is on the slope.

How many low level jets do you see? Do you see convergence?

Remember RABT = Red Away Blue Toward (except in Switzerland)

Why is there a hole in the data?

Would you see this on a mountain top radar?

Summary

• Shallow Weather– Focus on drizzle as an example to explain

detectability and measurability– Observability is a function of the radar too (MDS,

beamheight, beamwidth)– A few simple but key calculations to explain (not

calibration, not attenuation) – A little insight into “radar meteorology”

• A few case examples– Drizzle, snow, lake effect snow, orographic

Examples of Shallow Weather

Lake Effect Snow

shallow but lots of weather

1/8SM +SN +BLSNPatrick, EC

Morphology of Snowbands Thermal Convergence - Single Band

Development

Morphology of Snowbands Thermal Convergence - Single Band

Development

Morphology of SnowbandsFrictional Convergence - Single Band

Development

Ocean/Lake Effect SnowConceptual Model

Niziol, NWS/COMET

FetchLength of time cold air is over warm water.

Note that small variations in wind direction can result in significant changes in fetch. On Lake Erie for instance, a 230 degree wind has a 130-km fetch, while a 250 degreewind results in a 360-km fetch!

Morphology of Snow Bands

Horizontal Roll Multiple Banding

Single Band

Land Breeze Banding

MesoLow Multi-Lake Banding

The direction of the wind will produce significantly different results from lake to lake depending on the shape and orientation of a

body of water.

Ocean/Lake Effect Snow

Multiple Bands

Multiple Bands

Single Band

Frictional ConvergenceFrictional Convergence

Lake Ontario

Lake Erie

Lake Huron

Georgian Bay

Lake Michigan

Lake Superior

Morphology of Snow Bands Multiple Band - Horizontal Roll Convection

• Counter-rotating vortices in the boundary layer.

• Major axes aligned with the mean boundary layer wind shear vector.

• Wavelength (updraft to updraft) is about three times the height of the Boundary Layer.

Lake effect snowwind from northwest

Velocity Structure

dBZ Vr

Low speeds in the middle of the band indicating low horizontal speeds or convergence

Separated Bands

dBZ Vr

Thermal Convergence

The MesoLowLight Winds

Lake Breeze and Convective Weather

Morning

Mid Afternoon“Pure” LB exampleEnhance convergence

Lake Breeze BoundariesLakeHuron Lake Ontario

LakeSt Clair

Lake Erie

+

+

=

Pure lake breeze

Moderate SW Flow

Lake Breezes

Spring (15 Mar - 15 Jun) Tornado Touchdown Points

… overlaid with boundaries from 31 July 1994 ...

… tornadoes are suppressed in regions where Southwest winds are onshore ...

… and enhanced in regions where lake breeze boundaries often form.

Forecasters use knowledge of lake breeze positions in their severe weather forecast for weak tornadoes

Extremely Shallow Case

3.5

1.5

-0.1

Orographic Precipitation

Rain shadow

Two Conceptual Models of Orographic Precipitation

Medina and Houze, 2003

Stable Case: Blocked Flow from South

North South

ALPS

Precipitation on plains, Italy

Flow is blocked, flow is towards the south

MAP IOP-8 Medina and Houze, 2003

Radial Velocity - Blocked Flow

Medina and Houze, 2003

Unstable Case: Up and Over

Precipitation is on the first range

No blocked flow. Flow is from the south

Medina and Houze, 2003

Radial Velocity – Up and Over

Medina and Houze, 2003

FOEHN, no rain

H3km

The Alps

Lee Side Suppression

Erzgebirge

Ore m

ountains, grey

Doppler

No rain

No rain

1h accumulation

No rain

Accumulations

Wind Drives Precipitation

Germann, MCH