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Kyle Chudler
University of Michigan 2015
Patrick Kennedy
Colorado State University
CSU-CHILL
POLARIMETRIC RADAR DETECTION OF HAIL
USING X- AND S-BAND FREQUENCIES
8/4/2014
Summary
• Utilize CHILL Radar’s dual-frequency/dual-polarization
to detect Mie scattering
–Occurrence and size of hail
• Mie scattering occurs at lower hydrometeor diameters
at the X-Band
–Causes differences in radar moments between bands
Introduction
• Problem
– Hail is damaging and costly
– Small to moderate sized hail not as easy to detect
– Previous detection methods use DF or DP, not both
• Explore differences between DP products arising from Mie
scattering
– Mie scattering at X-band, Rayleigh at S-band
• End goal is to improve hail detection
(Skolnik 1980)
Background: Mie Backscattering
• Evidence of Mie scattering in three moments
• dBZ
– Decrease in dBZ due to initial lowering
in backscatter power in Mie regime
• ρhv
– Measure of the level of correlation
between the co-polar return signals
– Large change in backscatter with small diameter
change in Mie regime (Shoichiro and Kyosuke 2013)
Background: Mie Backscattering
• ϕdp
– Phase difference between the
co-polar signals
– Radar measures
ΨC = ϕdp (diff. prop. phase)
+ δ (diff. backscat. phase)
– Significant non-zero values of δ (> 5°) occur in Mie scattering
(Hubbert and Bringi 1995, Trömel et. al. 2013).
– Mie scattering causes “bumps” in ϕdp profile
Zrnić et. al. 1993
Methods
• Gather case studies, using VCHILL to get a first look
• Storm reports (SPC, CoCoRaHS, MPING)
• Load and manipulate radar files with MATLAB
• Look at 3 different parameters over a
time series of radar scans
– Dual frequency ratio (DFR)
– ρhv
– φdp
• Raw – Smoothed
• “5&5” test
• Use hydrometeor identification algorithm to outline areas of hail
• Compare values of parameters inside and outside hail region
Methods: DFR
• DFR: dBZSB – dBZXB
• Attenuation corrected
• Two methods
1. Calculate DFR each time step, then take temporal maximum of that
at each gate
2. Calculate temporal maximum reflectivity at each gate for each
band, then take difference between those
• Method 2 found to be less noisy
Method 1 Method 2
Methods: ρhv
• “Min-hold” technique
– Keep track of minimum ρhv that occurred over time at each gate
– Plot all of these minimum values at once
– Compare values inside and outside HID hail contour (histograms)
• X-band ρhv always lower than S-band, even without Mie
scattering
– Antenna/hardware artifact
– Correct for by looking for areas of light rain
• determine correction factor needed to match S-band in this area
UNCORRECTEDCORRECTED
Methods: φdp
• Use DROPS program to give smoothed φdp
– Also provides us with our HID
• Method 1
– Absolute difference between smoothed and raw φdp
– Max-hold
– Compare values inside and outside HID hail contour (histograms)
• Method 2
– Take difference between smoothed and raw φdp
– Look for stretches where difference remains the same sign and above a certain
magnitude for a certain number of gates
• S-band: >5 degrees for 3 gates (“5&3” test)
• X-band: >5 degrees for 5 gates (“5&5” test)
– Also includes a dBZ threshold (> 25 dBZ)
Methods: φdp
• Method 2
– S-band: >5 degrees for 3 gates (“5&3” test)
– X-band: >5 degrees for 5 gates (“5&5” test)
Range
φdp
Case Studies
• Two 0.5” – 1.5” hail storms
– Loveland, CO 06/03/2015
– Fort Collins, CO 06/04/2015
– Hail large enough to cause Mie scattering at X-band, not at S.
• One giant hail case (>4”)
– Minooka, IL 06/10/2015
– NEXRAD WSR-88D data from KLOT (no X-Band)
– Hail large enough to show Mie scattering at S-band
Event 1: Loveland, CO
• Hail up to 1.5” in Loveland
• 8 radar scans ~0100 – 0118 UTC
• Warned for ping-pong ball sized
hail as it moved through Loveland
• 12 storm reports gathered
ρhv
S-Band X-Band
S-BANDX-BAND
S-BANDX-BAND
0.8423 0.9589
0.0484
0.970 0.984
0.014
φdp (Raw - Smoothed)
S-Band X-Band
S-BANDX-BAND
S-BANDX-BAND
1.39
φdp (5&3/5&5 test)
S-Band X-Band
Event 2: Fort Collins, CO
• Hail up to 1.25” in Fort Collins
• 19 radar scans ~2340 – 2355 UTC
• Warned for half-dollar sized hail
at 23:52 UTC
• 20 storm reports gathered
ρhv
S-Band X-Band
S-BANDX-BAND
S-BANDX-BAND
0.9590 0.9820
0.0230
0.9002 0.9538
0.0536
φdp (Raw - Smoothed)
S-Band X-Band
S-BANDX-BAND
S-BANDX-BAND
1.29
φdp (5&3/5&5 test)
S-Band X-Band
φdp (5&3/5&5 test)
DFR X-Band
Events 1 & 2 Summary
• All methods could detect hail/Mie scattering to some extent
• Median ρhv was reduced by ~0.05 in HID hail region in X-band
– Compared to ~0.015 in S-Band
• Absolute difference between raw and smoothed φdp increased
by ~1.35° in X-band
– Compared to no change in the S-Band
– Plot very noisy looking
• 5&5 method able to successfully hone in on HID hail region
better, got rid of noise
– Detected extended “bumps” in φdp profile
Event 3: Minooka, IL
• Hail up to 4.75” in Minnoka, IL
– Second largest ever recorded in IL
• KLOT WSR-88D data
– No X-band -> no DFR
• Looking for same Mie scattering
indications that previous cases
showed at X-band http://www.weather.gov/lot/15jun10
Photo shared to the NWS by Lauren Geiselman
dBZRaw–Smoothedφdp
ρhv5&3Test
4.75” Hail
Event 3 Summary
• Same Mie scattering effects observed as were at X-Band for
smaller hail
– Reduction in ρhv
– Increase in magnitude of difference between raw and smoothed φdp
• 5&3 method unable to localize on Mie scattering region
– Flagged gates throughout entire storm
– Very unlikely hail large enough for S-Band Mie scattering was that
prevalent
Conclusions
• Using ρhv and φdp to detect Mie scattering appears to be a
viable strategy
– Can be seen at both bands
• Mie scattering effects are observed at smaller diameter hail at
X-band
– Could lead to earlier radar detection/warnings
• “5&3” detection method needs further refinement at S-Band
Future Work
• Improve 5&3 (S-band) test
• Perform more statistical analysis
(i.e. statistical significance of ρhv reduction, etc)
• Zdr in relation to hail size
– Large hail -> negative S-band Zdr?
• Eventually a more advanced algorithm could be developed
– Like DFR (compare between two radar bands), but with polarimetric
parameters
Questions?
Loveland Storm Fort Collins Storm
S-Band X-Band S-Band X-Band
ρhv
Difference in median value
inside/outside hail region
0.014 0.0484 0.023 0.0536
Raw – Smoothed ϕdp
Difference in median value
inside/outside hail region
.09 1.39 0.10 1.29
“5&3”/ “5&5” test
Percentage of gates within
hail region that were
flagged as Mie scattering
0.6 13.4 1.8 23.6
References
A. R. Jameson and A. J. Heymsfield, 1980: Hail Growth Mechanisms in a Colorado Storm. Part I: Dual-Wavelength Radar Observations. J.
Atmos. Sci., 37, 1763–1778. doi: http://dx.doi.org/10.1175/1520-0469(1980)037<1763:HGMIAC>2.0.CO;2
Atlas, D. and Ludlam, F. H., 1961: Multi-wavelength radar reflectivity of hailstorms. Q.J.R. Meteorol. Soc., 87, 523–534.
doi: 10.1002/qj.49708737407
Battan, L. J., 1973: Radar Observation of the Atmosphere. University of Chicago Press, 324 pp.
Cavanaugh, D. E., and J. A. Schultz, 2012: WSR-88D signatures associated with one inch hail in the Southern Plains. Electronic J. Operational
Meteor., 13 (1), 114.
D. S. Zrnić, N. Balakrishnan, C. L. Ziegler, V. N. Bringi, K. Aydin, and T. Matejka, 1993: Polarimetric Signatures in the Stratiform Region of a
Mesoscale Convective System. J. Appl. Meteor., 32, 678–693.
doi: http://dx.doi.org/10.1175/1520-0450(1993)032<0678:PSITSR>2.0.CO;2
D. S. Zrnić, V. N. Bringi, N. Balakrishnan, K. Aydin, V. Chandrasekar, and J. Hubbert, 1993: Polarimetric Measurements in a Severe Hailstorm.
Mon. Wea. Rev., 121, 2223–2238. doi: http://dx.doi.org/10.1175/1520-0493(1993)121<2223:PMIASH>2.0.CO;2
Greene, D. R., and R. A. Clark, 1972: Vertically integrated liquid water—A new analysis tool. Mon. Wea. Rev.,100, 548–552.
J. Hubbert and V. N. Bringi, 1995: An Iterative Filtering Technique for the Analysis of Copolar Differential Phase and Dual-Frequency Radar
Measurements. J. Atmos. Oceanic Technol., 12, 643–648.
doi: http://dx.doi.org/10.1175/1520-0426(1995)012<0643:AIFTFT>2.0.CO;2
References
John D. Tuttle and Ronald E. Rinehart, 1983: Attenuation Correction in Dual-Wavelength Analyses. J. Climate Appl. Meteor., 22, 1914–1921.
doi: http://dx.doi.org/10.1175/1520-0450(1983)022<1914:ACIDWA>2.0.CO;2
Junyent, F., V. Chandrasekar, V. N. Bringi, S. A. Rutledge, P. C. Kennedy, D. Brunkow, J. George, and R. Bowie, 2014: Transformation of the
CSU-CHILL radar facility to a dual-frequency, dual-polarization, Doppler system. Bull.Amer.Meteor.Soc., ,
doi:10.1175/BAMS-D-13-00150.1.
Kumjian, M., J. Picca, S. Ganson, A. Ryzhkov, and D. Zrnić, 2010: Three-body scattering signatures in polarimetric radar data. NOAA/NSSL
Rep., 12 pp. [Available online at https://www.nssl.noaa.gov/publications/wsr88d_reports/FINAL_TBSS.doc.]
Leslie R. Lemon, 1998: The Radar “Three-Body Scatter Spike”: An Operational Large-Hail Signature. Wea. Forecasting, 13, 327–340.
doi: http://dx.doi.org/10.1175/1520-0434(1998)013<0327:TRTBSS>2.0.CO;2
Matthew R. Kumjian and Alexander V. Ryzhkov, 2008: Polarimetric Signatures in Supercell Thunderstorms. J. Appl. Meteor. Climatol., 47,
1940–1961. doi: http://dx.doi.org/10.1175/2007JAMC1874.1
Paul H. Herzegh and Arthur R. Jameson, 1992: Observing Precipitation through Dual-Polarization Radar Measurements. Bull. Amer. Meteor.
Soc., 73, 1365–1374.
doi: http://dx.doi.org/10.1175/1520-0477(1992)073<1365:OPTDPR>2.0.CO
References
Rinehart, R. E., 2004: Radar for Meteorologists, Or, You Too Can Be a Radar Meteorologist, Part III. 5th ed. Rinehart Publications, 482 pp.
Rodney A. Donavon and Karl A. Jungbluth, 2007: Evaluation of a technique for radar identification of large hail across the upper midwest
and central plains of the united states. Wea. Forecasting, 22, 244–254. doi: http://dx.doi.org/10.1175/WAF1008.1
Shoichiro, F., and Kyosuke H., 2013: Radar Observations of Precipitation. Radar for Meteorological and Atmospheric Observations, D.
Richard, Ed., Springer., 198.
Silke Trömel, Alexander V. Ryzhkov, Pengfei Zhang, and Clemens Simmer, 2014: Investigations of Backscatter Differential Phase in the
Melting Layer. J. Appl. Meteor. Climatol., 53, 2344–2359. doi: http://dx.doi.org/10.1175/JAMC-D-14-0050.1
Silke Trömel, Matthew R. Kumjian, Alexander V. Ryzhkov, Clemens Simmer, and Malte Diederich, 2013: Backscatter Differential Phase—
Estimation and Variability. J. Appl. Meteor. Climatol., 52, 2529–2548. doi: http://dx.doi.org/10.1175/JAMC-D-13-0124.1
Skolnik, Merrill I, 1980: Introduction to Radar Systems, F. Cerra, Ed., McGraw-Hill Inc., 34.
Stanley A. Changnon and Jonathan Burroughs, 2003: The tristate hailstorm: the most costly on record. Mon. Wea. Rev., 131, 1734–1739.
doi: http://dx.doi.org/10.1175//2549.1
References
Steven A. Amburn and Peter L. Wolf, 1997: VIL Density as a Hail Indicator. Wea. Forecasting, 12, 473–478.
doi:http://dx.doi.org/10.1175/1520-0434(1997)012<0473:VDAAHI>2.0.CO;2
Warning Decision Training Branch and Radar Operations Center, cited 2010: References.
[Available online at http://www.erh.noaa.gov/rah/downloads/Dual_Pol/CC_v1.pdf]

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presentation

  • 1. Kyle Chudler University of Michigan 2015 Patrick Kennedy Colorado State University CSU-CHILL POLARIMETRIC RADAR DETECTION OF HAIL USING X- AND S-BAND FREQUENCIES 8/4/2014
  • 2. Summary • Utilize CHILL Radar’s dual-frequency/dual-polarization to detect Mie scattering –Occurrence and size of hail • Mie scattering occurs at lower hydrometeor diameters at the X-Band –Causes differences in radar moments between bands
  • 3. Introduction • Problem – Hail is damaging and costly – Small to moderate sized hail not as easy to detect – Previous detection methods use DF or DP, not both • Explore differences between DP products arising from Mie scattering – Mie scattering at X-band, Rayleigh at S-band • End goal is to improve hail detection
  • 5. Background: Mie Backscattering • Evidence of Mie scattering in three moments • dBZ – Decrease in dBZ due to initial lowering in backscatter power in Mie regime • ρhv – Measure of the level of correlation between the co-polar return signals – Large change in backscatter with small diameter change in Mie regime (Shoichiro and Kyosuke 2013)
  • 6. Background: Mie Backscattering • ϕdp – Phase difference between the co-polar signals – Radar measures ΨC = ϕdp (diff. prop. phase) + δ (diff. backscat. phase) – Significant non-zero values of δ (> 5°) occur in Mie scattering (Hubbert and Bringi 1995, Trömel et. al. 2013). – Mie scattering causes “bumps” in ϕdp profile Zrnić et. al. 1993
  • 7. Methods • Gather case studies, using VCHILL to get a first look • Storm reports (SPC, CoCoRaHS, MPING) • Load and manipulate radar files with MATLAB • Look at 3 different parameters over a time series of radar scans – Dual frequency ratio (DFR) – ρhv – φdp • Raw – Smoothed • “5&5” test • Use hydrometeor identification algorithm to outline areas of hail • Compare values of parameters inside and outside hail region
  • 8. Methods: DFR • DFR: dBZSB – dBZXB • Attenuation corrected • Two methods 1. Calculate DFR each time step, then take temporal maximum of that at each gate 2. Calculate temporal maximum reflectivity at each gate for each band, then take difference between those • Method 2 found to be less noisy
  • 10. Methods: ρhv • “Min-hold” technique – Keep track of minimum ρhv that occurred over time at each gate – Plot all of these minimum values at once – Compare values inside and outside HID hail contour (histograms) • X-band ρhv always lower than S-band, even without Mie scattering – Antenna/hardware artifact – Correct for by looking for areas of light rain • determine correction factor needed to match S-band in this area
  • 12. Methods: φdp • Use DROPS program to give smoothed φdp – Also provides us with our HID • Method 1 – Absolute difference between smoothed and raw φdp – Max-hold – Compare values inside and outside HID hail contour (histograms) • Method 2 – Take difference between smoothed and raw φdp – Look for stretches where difference remains the same sign and above a certain magnitude for a certain number of gates • S-band: >5 degrees for 3 gates (“5&3” test) • X-band: >5 degrees for 5 gates (“5&5” test) – Also includes a dBZ threshold (> 25 dBZ)
  • 13. Methods: φdp • Method 2 – S-band: >5 degrees for 3 gates (“5&3” test) – X-band: >5 degrees for 5 gates (“5&5” test) Range φdp
  • 14. Case Studies • Two 0.5” – 1.5” hail storms – Loveland, CO 06/03/2015 – Fort Collins, CO 06/04/2015 – Hail large enough to cause Mie scattering at X-band, not at S. • One giant hail case (>4”) – Minooka, IL 06/10/2015 – NEXRAD WSR-88D data from KLOT (no X-Band) – Hail large enough to show Mie scattering at S-band
  • 15. Event 1: Loveland, CO • Hail up to 1.5” in Loveland • 8 radar scans ~0100 – 0118 UTC • Warned for ping-pong ball sized hail as it moved through Loveland • 12 storm reports gathered
  • 16.
  • 17.
  • 20. φdp (Raw - Smoothed) S-Band X-Band
  • 23. Event 2: Fort Collins, CO • Hail up to 1.25” in Fort Collins • 19 radar scans ~2340 – 2355 UTC • Warned for half-dollar sized hail at 23:52 UTC • 20 storm reports gathered
  • 24.
  • 27. φdp (Raw - Smoothed) S-Band X-Band
  • 31. Events 1 & 2 Summary • All methods could detect hail/Mie scattering to some extent • Median ρhv was reduced by ~0.05 in HID hail region in X-band – Compared to ~0.015 in S-Band • Absolute difference between raw and smoothed φdp increased by ~1.35° in X-band – Compared to no change in the S-Band – Plot very noisy looking • 5&5 method able to successfully hone in on HID hail region better, got rid of noise – Detected extended “bumps” in φdp profile
  • 32. Event 3: Minooka, IL • Hail up to 4.75” in Minnoka, IL – Second largest ever recorded in IL • KLOT WSR-88D data – No X-band -> no DFR • Looking for same Mie scattering indications that previous cases showed at X-band http://www.weather.gov/lot/15jun10 Photo shared to the NWS by Lauren Geiselman
  • 34. Event 3 Summary • Same Mie scattering effects observed as were at X-Band for smaller hail – Reduction in ρhv – Increase in magnitude of difference between raw and smoothed φdp • 5&3 method unable to localize on Mie scattering region – Flagged gates throughout entire storm – Very unlikely hail large enough for S-Band Mie scattering was that prevalent
  • 35. Conclusions • Using ρhv and φdp to detect Mie scattering appears to be a viable strategy – Can be seen at both bands • Mie scattering effects are observed at smaller diameter hail at X-band – Could lead to earlier radar detection/warnings • “5&3” detection method needs further refinement at S-Band
  • 36. Future Work • Improve 5&3 (S-band) test • Perform more statistical analysis (i.e. statistical significance of ρhv reduction, etc) • Zdr in relation to hail size – Large hail -> negative S-band Zdr? • Eventually a more advanced algorithm could be developed – Like DFR (compare between two radar bands), but with polarimetric parameters
  • 37. Questions? Loveland Storm Fort Collins Storm S-Band X-Band S-Band X-Band ρhv Difference in median value inside/outside hail region 0.014 0.0484 0.023 0.0536 Raw – Smoothed ϕdp Difference in median value inside/outside hail region .09 1.39 0.10 1.29 “5&3”/ “5&5” test Percentage of gates within hail region that were flagged as Mie scattering 0.6 13.4 1.8 23.6
  • 38. References A. R. Jameson and A. J. Heymsfield, 1980: Hail Growth Mechanisms in a Colorado Storm. Part I: Dual-Wavelength Radar Observations. J. Atmos. Sci., 37, 1763–1778. doi: http://dx.doi.org/10.1175/1520-0469(1980)037<1763:HGMIAC>2.0.CO;2 Atlas, D. and Ludlam, F. H., 1961: Multi-wavelength radar reflectivity of hailstorms. Q.J.R. Meteorol. Soc., 87, 523–534. doi: 10.1002/qj.49708737407 Battan, L. J., 1973: Radar Observation of the Atmosphere. University of Chicago Press, 324 pp. Cavanaugh, D. E., and J. A. Schultz, 2012: WSR-88D signatures associated with one inch hail in the Southern Plains. Electronic J. Operational Meteor., 13 (1), 114. D. S. Zrnić, N. Balakrishnan, C. L. Ziegler, V. N. Bringi, K. Aydin, and T. Matejka, 1993: Polarimetric Signatures in the Stratiform Region of a Mesoscale Convective System. J. Appl. Meteor., 32, 678–693. doi: http://dx.doi.org/10.1175/1520-0450(1993)032<0678:PSITSR>2.0.CO;2 D. S. Zrnić, V. N. Bringi, N. Balakrishnan, K. Aydin, V. Chandrasekar, and J. Hubbert, 1993: Polarimetric Measurements in a Severe Hailstorm. Mon. Wea. Rev., 121, 2223–2238. doi: http://dx.doi.org/10.1175/1520-0493(1993)121<2223:PMIASH>2.0.CO;2 Greene, D. R., and R. A. Clark, 1972: Vertically integrated liquid water—A new analysis tool. Mon. Wea. Rev.,100, 548–552. J. Hubbert and V. N. Bringi, 1995: An Iterative Filtering Technique for the Analysis of Copolar Differential Phase and Dual-Frequency Radar Measurements. J. Atmos. Oceanic Technol., 12, 643–648. doi: http://dx.doi.org/10.1175/1520-0426(1995)012<0643:AIFTFT>2.0.CO;2
  • 39. References John D. Tuttle and Ronald E. Rinehart, 1983: Attenuation Correction in Dual-Wavelength Analyses. J. Climate Appl. Meteor., 22, 1914–1921. doi: http://dx.doi.org/10.1175/1520-0450(1983)022<1914:ACIDWA>2.0.CO;2 Junyent, F., V. Chandrasekar, V. N. Bringi, S. A. Rutledge, P. C. Kennedy, D. Brunkow, J. George, and R. Bowie, 2014: Transformation of the CSU-CHILL radar facility to a dual-frequency, dual-polarization, Doppler system. Bull.Amer.Meteor.Soc., , doi:10.1175/BAMS-D-13-00150.1. Kumjian, M., J. Picca, S. Ganson, A. Ryzhkov, and D. Zrnić, 2010: Three-body scattering signatures in polarimetric radar data. NOAA/NSSL Rep., 12 pp. [Available online at https://www.nssl.noaa.gov/publications/wsr88d_reports/FINAL_TBSS.doc.] Leslie R. Lemon, 1998: The Radar “Three-Body Scatter Spike”: An Operational Large-Hail Signature. Wea. Forecasting, 13, 327–340. doi: http://dx.doi.org/10.1175/1520-0434(1998)013<0327:TRTBSS>2.0.CO;2 Matthew R. Kumjian and Alexander V. Ryzhkov, 2008: Polarimetric Signatures in Supercell Thunderstorms. J. Appl. Meteor. Climatol., 47, 1940–1961. doi: http://dx.doi.org/10.1175/2007JAMC1874.1 Paul H. Herzegh and Arthur R. Jameson, 1992: Observing Precipitation through Dual-Polarization Radar Measurements. Bull. Amer. Meteor. Soc., 73, 1365–1374. doi: http://dx.doi.org/10.1175/1520-0477(1992)073<1365:OPTDPR>2.0.CO
  • 40. References Rinehart, R. E., 2004: Radar for Meteorologists, Or, You Too Can Be a Radar Meteorologist, Part III. 5th ed. Rinehart Publications, 482 pp. Rodney A. Donavon and Karl A. Jungbluth, 2007: Evaluation of a technique for radar identification of large hail across the upper midwest and central plains of the united states. Wea. Forecasting, 22, 244–254. doi: http://dx.doi.org/10.1175/WAF1008.1 Shoichiro, F., and Kyosuke H., 2013: Radar Observations of Precipitation. Radar for Meteorological and Atmospheric Observations, D. Richard, Ed., Springer., 198. Silke Trömel, Alexander V. Ryzhkov, Pengfei Zhang, and Clemens Simmer, 2014: Investigations of Backscatter Differential Phase in the Melting Layer. J. Appl. Meteor. Climatol., 53, 2344–2359. doi: http://dx.doi.org/10.1175/JAMC-D-14-0050.1 Silke Trömel, Matthew R. Kumjian, Alexander V. Ryzhkov, Clemens Simmer, and Malte Diederich, 2013: Backscatter Differential Phase— Estimation and Variability. J. Appl. Meteor. Climatol., 52, 2529–2548. doi: http://dx.doi.org/10.1175/JAMC-D-13-0124.1 Skolnik, Merrill I, 1980: Introduction to Radar Systems, F. Cerra, Ed., McGraw-Hill Inc., 34. Stanley A. Changnon and Jonathan Burroughs, 2003: The tristate hailstorm: the most costly on record. Mon. Wea. Rev., 131, 1734–1739. doi: http://dx.doi.org/10.1175//2549.1
  • 41. References Steven A. Amburn and Peter L. Wolf, 1997: VIL Density as a Hail Indicator. Wea. Forecasting, 12, 473–478. doi:http://dx.doi.org/10.1175/1520-0434(1997)012<0473:VDAAHI>2.0.CO;2 Warning Decision Training Branch and Radar Operations Center, cited 2010: References. [Available online at http://www.erh.noaa.gov/rah/downloads/Dual_Pol/CC_v1.pdf]