Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and...

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Transcript of Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and...

Page 1: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 1 – April 19, 2023

Radar Algorithms

MSC Radar Course

David Patrick

Hydrometeorological and Arctic Lab

Winnipeg, MB

Page 2: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 2 – April 19, 2023

Acknowledgements

• Dave Ball for inspiring this course

• Operational meteorologists across Canada for giving me ideas and input

Page 3: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Outline

• Basic algorithms– PRECIP, Doppler ClogZ Reflectivity, Radial Velocity,

Storm-relative Radial Velocity

• Grid-based severe thunderstorm algorithms– SvrWx, CAPPI 7.0, CoTPPI, VIL, WDraft, Hail, BWER,

Reflectivity Gradient, MesoCyclone, Microburst, Gust

• Cell-based severe thunderstorm algorithms– Cell Identification, Cell Properties, MultiRadarMerge,

Cell Tracking, Cell View, StormAssessmentClassification, SCIT

Page 4: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Basic Algorithms - PRECIP

• PRECIP product is combo of

– doppler reflectivity within 125 km

– conventional reflectivity beyond 125 km

doppler clutter suppression can reduce

signal and create artificial boundary at 125

interface

Page 5: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Basic Algorithms - PRECIP

• Inner doppler scan may be under-calibrated compared to outer conventional scan giving inner circle of reduced returns

7-day Rainfall Accum7-day Rainfall Accum

Page 6: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Doppler & Conventional Base Reflectivity Loop

• Doppler and conventional base level reflectivities are ~5 minutes apart in 10 minute scan cycle

• Can create a 5-minute frequency loop by alternating between the two products (not operationally available)

Page 7: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Basic Algorithms Doppler vs. Conventional Reflectivity

Doppler 0.5° “ClogZ” reflectivity Conventional 0.5° reflectivity

• Sometimes doppler reflectivity has holes in the data

Note doppler data has 4x resolution of conventional data

same cell with no holes in conventional

data

Page 8: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Basic Algorithms – Doppler Signal Processing

• At the radar site processor, a Signal Quality Index is used to determine if a radar bin’s radial velocity is good

• SQI is related to– spectrum width, the degree of spread in the radial velocity

elements for the radar bin; high spectrum width -> low SQI– signal to noise ratio; low signal -> low SQI

• If the SQI is too low, the radial velocity is trashed, along with reflectivity!

-VN 0 +VN

0

-10

-20

-30

-60

-50-40

-70-80

dBZ

ground clutterweather

Spectrum width is measure of spread of weather

Page 9: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Basic Algorithms – Doppler Signal Processing

Reflectivity

• Doppler data from 0.5° scan

• High spectrum width causes data dropout in critical area

Radial velocity Spectrum width

• 2010Z August 20, 2009; tornado on ground in missing data zone

signal trashed

Page 10: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Basic algorithms – Radial Velocity

• Canadian radars are C-band radars (except S-band McGill) that use dual pulse repetition frequencies in doppler mode

• Nyquist velocity VN is max velocity that can be unambiguously determined VN = PRF ∙ λ / 4

• All V < -VN or V > VN are “folded” into –VN to +VN range• Low PRF 892 s-1 VN = 892 ∙ 0.0534 / 4 = 11.9 m/s• High PRF 1190 s-1 VN = 1190 ∙ 0.0534 / 4 = 15.9 m/s• Low and High PRF rays are alternated around scan• Processing at radar site combines/unfolds data to give

-48 m/s <= V <= +48 m/s

Page 11: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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The ‘dual-

PRF’

unfolding technique

The ‘dual-

PRF’

unfolding technique

Basic algorithms – Radial Velocity

• Look at relative error V1200 – V900

• Pick off actual

velocity

Page 12: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Basic algorithms – Radial Velocity

• Let’s go to SErn Newfoundland

• Strong Low approaching from SW

• Original folded velocities from alternating Low/High PRF rays

• No V < -16 m/s or V > 16 m/s

Page 13: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Basic algorithms – Radial Velocity

• Unfold velocities at radar site

• Note bright green speckles (V= -36

m/s) embedded in yellow-pink area (V= +30 m/s)

– Either bad unfolding or bad data leading to bad unfolded velocities

Page 14: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Basic algorithms – Radial Velocity

• Corresponding analyses

1200Z Oct 17 2009

• Surface

• 850 mb

• 700 mb

Page 15: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Basic algorithms – Radial Velocity

VAD winds at 0900Z Oct 17 2009

Winds are consistently from E to SE direction

in lower 5,000 feet

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Basic algorithms – Radial Velocity

• Apply “despike” algorithm that assumes data is accurate and tries to find best unfolded velocity compared to immediate neighbours

• This is what you see on the fcst desk

Data is smoothed but area of towards-radar velocities is increased

With despikeWithout despike

Page 17: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Basic algorithms – Radial Velocity

• Try unfolding velocities at forecast office using velocity info from a wider neighbourhood (under development)

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Basic Algorithms – Extra Info Long Range Radial Velocity

Note!• When looking at LongRange Velocity product, velocity folding occurs at just 16 m/s, not the usual 48 m/s

• Look for light blue and orange adjacent to each other

Page 19: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Basic Algorithms – Storm Relative Velocity

couplet embedded in away velocities

couplet showing away and towards motion relative to storm

• Subtract off storm motion vector from all radial velocity bins to view motion in storm-based frame of reference

Radar-based radial velocityStorm-based radial velocity

Subtract 250/40Subtract 250/40km/hkm/h from all bins from all bins

Page 20: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Grid-based Svr Wx AlgorithmsSVRWX

• Based on work done by US Air Force & NSSL in 1960s and updated in Canada in 1980s

• Height of 40 dBZ echo is correlated to severe weather occurrence (can be 45 dBZ in parts of Canada)

– Not strongly correlated to tornadoes in high shear environments

• Evidence of strong deep updraft with significant moisture/hail

Page 21: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• SvrWx values:– 40 dBZ @ 5.5 km => level 1 blue– 40 dBZ @ 8.5 km => level 2 green– 40 dBZ @ 10.5 km => level 3 yellow– 40 dBZ @ 12.0 km => level 4 red

Grid-based Svr Wx AlgorithmsSVRWX

Increasing probability of severe weather

Page 22: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Grid-based Svr Wx AlgorithmsSVRWX

• CAPPI 1.5 km shows large

swaths of strong echoes

• SvrWx highlights

sig convection

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Grid-based Svr Wx AlgorithmsCAPPI 7.0

• CAPPI 7.0 km has traditionally been used to highlight sig cvctn

• But its use depends on airmass temperature

• Poor in cool airmasses

Page 24: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Grid-based Svr Wx AlgorithmsCoTPPI -20°C

• Try using Constant Temperature PPI sfc instead of Constant Altitude PPI

• -20°C sfc slides up and down with airmass

• Use model data for temps

not operationally available

Page 25: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• Take Z for a radar bin volume, convert to liquid, and integrate thru vertical column

• Shows heavy rain potential, large hail, ~ wet microburst potential• Note: VIL Density (VIL divided by depth of echoes) will partially account for a distant cell that is substantially below the lowest scan angle

Grid-based Svr Wx AlgorithmsVIL

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• Developed by S.R. Stewart, 1991

• WDraft = 3.6 * SQRT (20.628571 x VIL - 3.125 ET**2) km/h

• Algorithm looks only at instantaneous VIL and EchoTop, not rate of change of these parameters

Grid-based Svr Wx AlgorithmsWDRAFT

Page 27: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• Big VIL packed into a relatively low echo top gives high WDraft

Grid-based Svr Wx AlgorithmsWDRAFT

Page 28: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Grid-based Svr Wx AlgorithmsHail

• Uses an algorithm developed in Southeastern Australia

• Height of 50 dBZ and freezing level are empirically correlated to hail diameter

• VIL and freezing level are also empirically correlated to hail diameter

• Given hgt 50 dBZ, VIL and freezing level, calculate hail diameter using both methods and choose the larger of the two.

Page 29: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Grid-based Svr Wx AlgorithmsHail

Observed Hail Size

vs. Height

50 dBZ & Freezing

Level

Page 30: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Grid-based Svr Wx AlgorithmsHail

Observed Hail Size

vs. VIL &

Freezing Level

Page 31: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• Tends to over-forecast hail diameter

• But in this case, 7.1 cm was good

Grid-based Svr Wx AlgorithmsHail

Page 32: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Grid-based Svr Wx AlgorithmsHail

Dauphin hailstorm Aug 9, 2007

Page 33: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• Use a reflectivity-to-hail energy relation and integrate this energy with height above the freezing level

• Using a large dataset, this integrated energy is statistically related to

– MESH (Maximum Expected Size of Hail)– POSH (Probability of Severe Hail)

Grid-based Svr Wx Algorithms U.S. NWS MESH & POSH Algorithms

Page 34: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• Hail kinetic energy E

– where W(dBZ) is a weight based on reflectivity; dBZL=40, dBZU=50

0 for dBZ <= dBZL

W(dBZ) = dBZ – dBZL for dBZL < dBZ < dBZU

dBZU – dBZL

1 for dBZ >= dBZU

)(10105 084.06 dBZWE

Grid-based Svr Wx Algorithms U.S. NWS MESH & POSH Algorithms

Page 35: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• Severe Hail Index SHI

– where H0 is height of fzlvl, HT is height of storm top, WT(H) is a weight based on temperature, and Hm20 (hgt -20C) All heights AboveRadarLevel

0 for H <= H0

WT(H) = H – H0 for H0 < H < Hm20

Hm20 – H0

1 for H >= Hm20

dHEHWSHITH

H

T 0

)(1.0

Grid-based Svr Wx Algorithms U.S. NWS MESH & POSH Algorithms

Page 36: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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– where WT is warning threshold

if WT < 20, set to 20

SHIMESH 54.2

50ln29 WT

SHIPOSH

1215.57 0 HWT

Grid-based Svr Wx Algorithms U.S. NWS MESH & POSH Algorithms

Page 37: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• URP Hail has +ve bias

Grid-based Svr Wx Algorithms U.S. NWS MESH & POSH Algorithms

• U.S. NWS MESH no bias but underfcsts large hail; overfcsts small hail

• U.S. NWS POSH if >70% svr hail likely

Page 38: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• Find upside down cup patterns in the reflectivity volume scan, as evidence of strong updraft with rotation

• Go out and up from each radar bin, looking for higher values

• URP looks out in 8 directions, but up in only 5 (let’s make it 9)

Grid-based Svr Wx AlgorithmsBWER (Bounded Weak Echo Region)

Page 39: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• Do a double pass over the data

• First pass– In these 13 (try 17) directions, go out a max of 10

radar bins (try 10 km), looking for dBZ values that are at least 8 dBZ greater than the centre radar bin, and >= 40 dBZ in value (try giving partial credit to

6+ dBZ gradients)– Count the number of “hits”– Weight all directions the same (try requiring vertical

direction hit)

Grid-based Svr Wx AlgorithmsBWER (Bounded Weak Echo Region)

Page 40: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Example:

CAPPI 1.5 km

XSM

0030Z July 30 2005

Grid-based Svr Wx AlgorithmsBWER (Bounded Weak Echo Region)

Rocky Mountains

Page 41: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 41 – April 19, 2023

Grid-based Svr Wx AlgorithmsBWER (Bounded Weak Echo Region)

BWER algorithm checks out a long way in the azimuthal direction

Page 42: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• Second pass– Go thru the first pass results, traversing the same

13 (17) directions, and subtract one “hit” every time you come across a radar bin that has a lower hit count than your centre radar bin

– This gives a measure of boundedness of the centre radar bin you’re examining

– Look thru the volume at all the radar bins with a non-zero hit count, and for each column of radar bins, save the height of the highest one (try saving

volume as well)

Grid-based Svr Wx AlgorithmsBWER (Bounded Weak Echo Region)

Page 43: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 43 – April 19, 2023

Grid-based Svr Wx AlgorithmsBWER (Bounded Weak Echo Region)

A final hit count of 1 or 2 is left

oops

Page 44: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 44 – April 19, 2023

Usual way to plot BWER is in white on CELL View

Grid-based Svr Wx AlgorithmsBWER (Bounded Weak Echo Region)

Giant BWER

Page 45: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 45 – April 19, 2023

• Calculates the reflectivity gradient for any specified areal product, e.g. CAPPI 1.5 km dBZ or CAPPI 3.0 km dBZ

• Sharp mid-level gradients on upwind side of CB are correlated to rear-flank downdraft, mesocyclone development

Grid-based Svr Wx AlgorithmsReflectivity Gradient

Page 46: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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3 km CAPPI dBZ 3 km dBZ Gradient

July 24 2000

2230Z

Brunkild MB

Hook echo

Grid-based Svr Wx AlgorithmsReflectivity Gradient

Page 47: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• Doppler data is available for the 0.5, 1.5 and 3.5 degree elevation angles at every 0.5 km in range out to 112.5 km, and every 0.5 degrees azimuth around the radar; 225 x 720 bins

• Rays alternate between low PRF and high PRF• Choose only high PRF (VN=16 m/s) rays• For every range bin away from the radar out to 225

bins, go around 360 degrees, looking for aziumthal shear across every 2nd bin, i.e. every high PRF ray

• Note zones of strong connected bin-to-bin (gate-to-gate) azimuthal shear over the 3 scan angles and group them into “features”.

Grid-based Svr Wx AlgorithmsMesocyclone

Page 48: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 48 – April 19, 2023

• If feature has too little– area,– shear less than min shear threshold,– higher shear but weak momentum, or– dBZ

▪ then trash.

• These thresholds are configurable.

Grid-based Svr Wx AlgorithmsMesocyclone

Page 49: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• Assigning levels– Level 1 => 1 meso detected at 1.5 or 3.5 degrees– Level 2 => 2 mesos detected at 1.5 & 3.5 degrees– Level 3 => mesos detected at all 3 levels OR meso detected

at lowest 0.5 degree level– Level 4 => a level 3 that has sufficient momentum and max

gate-to-gate shear– Level 5 => a level 4 that is at least 5 km across in the radial

direction?

• Assigning circle diameter– Seems that the circle diameter is related to the diameter of

the circulation in the azimuthal direction … 10 times? diameter

Grid-based Svr Wx AlgorithmsMesocyclone

Page 50: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• Strong mesocyclone NW of Kitchener/ Waterloo

• Tornado on ground at time

WSO Kitchener

Hwy 401

Grid-based Svr Wx AlgorithmsMesocyclone

Page 51: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 51 – April 19, 2023

• Messy High Precipitation supercell pattern, with convective arms

WSO Kitchener

Hwy 401

Grid-based Svr Wx AlgorithmsMesocyclone

Page 52: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 52 – April 19, 2023

• Strong mesocyclone near Brunkild, SW of Winnipeg

• Wall cloud observed at time

Winnipeg

XWL

Grid-based Svr Wx AlgorithmsMesocyclone

Page 53: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 53 – April 19, 2023

• Classic supercell

Winnipeg

XWL

Grid-based Svr Wx AlgorithmsMesocyclone

Page 54: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 54 – April 19, 2023

• Remember doppler data has 225 range bins, 0.5 km resolution, and 720 azimuth bins, 0.5 degree resolution

• Rays alternate between low PRF and high PRF

• Choose only high PRF (VN=16 m/s) rays

• For the lowest scan angle, for every 2nd azimuth ray, i.e. every high PRF ray … go out along all the radial to just 113 bins, i.e. 57 km, looking for divergent radial shear.

• Note zones of radial divergent shear and group them into “features”.

Grid-based Svr Wx AlgorithmsMicroburst

Page 55: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• If feature has too little– area,– shear less than min shear threshold,– higher shear but weak momentum, or– dBZ

▪ then trash.• These thresholds are configurable.• Assign Level 1 to all features.

Grid-based Svr Wx AlgorithmsMicroburst

Page 56: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 56 – April 19, 2023

• Microburst algorithm seems to be too “sensitive”, especially near radar

• Maybe we can “fine-tune” it

WSO Kitchener

Hwy 401

WSO

Grid-based Svr Wx AlgorithmsMicroburst

Page 57: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 57 – April 19, 2023

• Microbursts, maybe yes, maybe no

Winnipeg

XWL

Grid-based Svr Wx AlgorithmsMicroburst

Page 58: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 58 – April 19, 2023

• Yes, doppler data has 225 range bins, 0.5 km resolution, and 720 azimuth bins, 0.5 degree resolution

• For the lowest scan angle, for every 2nd azimuth ray, i.e. every high PRF ray … go out along all the radial to 226 bins, i.e. 113 km, looking for convergent radial shear.

• Note zones of radial convergent shear and group them into “features”, i.e. shear lines.

Grid-based Svr Wx AlgorithmsGust (shear line)

Page 59: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 59 – April 19, 2023

• If feature has too little– area,– shear less than min convergent shear threshold,– higher shear but weak momentum, or– dBZ

▪ then trash.• These thresholds are configurable.• Assign Level 1 to all features.

Grid-based Svr Wx AlgorithmsGust (shear line)

Page 60: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 60 – April 19, 2023

• Lines of strong convergent shear detected approaching radar

WHK

multiple gust fronts painted dark yellow

Grid-based Svr Wx AlgorithmsGust (shear line)

Page 61: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 61 – April 19, 2023

• Definition of cell is very simple – Area of echoes is called a cell if the 45 dBZ MaxR

above 2 km covers at least 2 radar bins in radial direction and 2 radar bins in the azimuthal direction, i.e. >= 4 bins

– Ground clutter MaxR returns can’t be allowed to contaminate cell identification

– Mask them out by making a blue sky MaxR image and then blacking out all future MaxR values from these areas

– 45 dBZ level and number of contiguous azimuthal radar bins is configurable, but not number of radial bins

Cell-based Svr Wx AlgorithmsCell ID

Page 62: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 62 – April 19, 2023

A plot of URP cells on the 7 km CAPPI product

URP Cell ID tends to get overly excited close in to the radar

Cell-based Svr Wx AlgorithmsCell ID

WSO radar

Page 63: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• Instead of keying on MaxR, try using volume of strong echoes and measures of AP likelihood to limit “fake” echoes

• Identify thunderstorm cells by adjusting the following thresholds

– Core dBZ threshold, eg. 45– Minimum core volume, eg. 50 km**3– Temperature threshold, eg. -20C– Outer dBZ threshold, eg. 30– Minimum outer volume of outer dBZ colder than

Temperature threshold, 5 km**3

• Also assess likelihood that “cell” is AP by looking at– Texture, spin, model MUCAPE, model AP risk

Cell-based Svr Wx AlgorithmsCell ID possible improvements

Page 64: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 64 – April 19, 2023

Current Cell ID

37 cells

Many insignificant cells near radar

Cell-based Svr Wx AlgorithmsCell ID possible improvements

Page 65: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 65 – April 19, 2023

Proposed New Cell

ID

14 cells

Cell-based Svr Wx AlgorithmsCell ID possible improvements

Page 66: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• Calculates and stores a number of properties for the cell which are available to any program for use

• Construct best-fit ellipse for MaxR footprint of the cell• Within and in immediate vicinity of the ellipse,

calculate …– Average & max values and location of CAPPI 1.5,

EchoTop, MaxZ, 45dBZEchoTop, Hail, VIL, VILD, WDraft, LoLvlZGrad, MidLvlZGrad, BWER, Meso, Micro, (try Lightning)

– Cell location, velocity – (try storing other properties: attenuation, AP likelihood,

model FZLVL, model mean wind velocity)

Cell-based Svr Wx AlgorithmsCell Properties

Page 67: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 67 – April 19, 2023

Cell-based Svr Wx AlgorithmsMultiRadarMerge

• Decide which radar will track and assess a given thunderstorm cell

• With URP, the radar that sees the greatest MaxR for the cell is the winner

– Poor choice if winner radar is a “hot” radar that only sees the top of the cell

• Try instead, go with the radar that sees the greatest depth of the cell, i.e. the one that sees the lowest down in the cell

Page 68: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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• Uses ThunderstormIdentificationTrackingAnalysisNowcasting method by Dixon,Wiener 1993

• From current cell velocity, generate a forecast of cell position at T+10 minutes

• Use “Hungarian” algorithm to pair up observed cells with forecast cells.

• Assign a weight to the strength of each potential match of forecast cell to observed cell.

– The greater the weight, the better the match

• Then the Hungarian algorithm will decide which combination of pairs will give highest total weight

• Hungarian algorithm will always pair up the max possible matches– Given 10 fcst and 12 obs, there will be 10 pairs and 2 new obs cells

• Current URP only breaks a match if cell speed would be > 35 m/s

Cell-based Svr Wx AlgorithmsCell Tracker

Page 69: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 69 – April 19, 2023

• Calculate and use 30 minute (configurable) mean cell velocity when tracking, instead of latest 10 minute motion

– If cell < 30 min. old, use timespan of cell

• Knowledge of mean velocity provides– more consistent tracking– input into Warnings

• Generate a forecast of cell position, volume, area & other cell attributes at T+10 minutes

– For a new cell, instead of giving it no velocity, push it along with 0-8 km mean wind vector

• Assign weights for possible matches using distance, volume & area• Need rules to disallow unreasonable matches

– Cell track “matches” that result in motions that deviate “too much” from their neighbours or from the mean flow are disallowed

• Rules need fine-tuning in squall line situations where “cell” centroid moves erratically with addition and shedding of individual cells

Cell-based Svr Wx AlgorithmsCell Tracker possible improvements

Page 70: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Current URP found & tracked 253 cells

between Jun 23 2200Z – Jun 24 0400Z 2007

Page 71: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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New prototype URP found & tracked 90 cells

between Jun 23 2200Z – Jun 24 0400Z 2007

Page 72: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

Page 72 – April 19, 2023

Cell-based Svr Wx AlgorithmsCell View (conventional scan panel)Assemble various cell-centred products in a panel

ZZ

Time series

1.5

3.0

7.0

9.0MaxRMaxR

ETET

3.0 3.0 GradGrad

1.5 1.5 GradGrad

SvrSvrWxWx

VILVIL

BWERBWER

HailHail

Page 73: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Cell-based Svr Wx AlgorithmsCell View (doppler scan panel)

Assemble various cell-centred products in a panel

Time series

VV ZZ WW

0.3°

0.5°

1.5°

3.5°

Page 74: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Cell-based Svr Wx AlgorithmsStorm Assessment/Classification &

SCIT

• The Storm Assessment & Classification algorithm produces

– Storm rank– Storm class, SC, SST, MST, WST

• The Storm Cell Identification Table contains a list of cell properties for each identified cell

• Any properties calculated by the Cell Properties algorithm can be displayed

• Here is the SCIT for the operational URP

Page 75: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Rank weight is an even weighting of the following 7 attributes:

• BWER, Meso, Hail, WDraft, VILDensity, MaxZ, ETop45dBZ

• generally maxes out around 10

Green, yellow, red thresholds are all configurable.

Cell-based Svr Wx AlgorithmsSCIT

Page 76: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Location VIL Density

WDraft (km/h)

EchoTop45 (km)

Total Ltg FlashesMax Z

Pct of CG Flashes that are +ve

Core Volume < 0C (km^3)

Core Volume (km^3)

BWER Volume (km^3)

Hail (cm)

Ave Meso Shear

Rank Weight

Primary Radar

BWER Height (km)

Max Amp (Kamp)

Flash Density (km^-2)

Flash Tendency (min^-1)

Mean Velocity (dir’n / km/h)

Cell-based Svr Wx AlgorithmsSCIT possible improvements

We could potentially add more attributes …

Page 77: Page 1 – September 4, 2015 Radar Algorithms MSC Radar Course David Patrick Hydrometeorological and Arctic Lab Winnipeg, MB.

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Radar Algorithms

And finally we’re at

The End

Thank you

Any questions?