Presentation is loading. Please wait.

Presentation is loading. Please wait.

© 2000 Roger Edwards Investigating the Potential of Using Radar to Nowcast Cloud-to-Ground Lightning Initiation over Southern Ontario 18 th Annual GLOMW.

Published byHarry Norris Modified over 8 years ago

Similar presentations

Presentation on theme: "© 2000 Roger Edwards Investigating the Potential of Using Radar to Nowcast Cloud-to-Ground Lightning Initiation over Southern Ontario 18 th Annual GLOMW."— Presentation transcript:

1 © 2000 Roger Edwards Investigating the Potential of Using Radar to Nowcast Cloud-to-Ground Lightning Initiation over Southern Ontario 18 th Annual GLOMW Toronto, Ontario Y. Helen Yang / Patrick King Ontario Storm Prediction Centre Environment Canada 23.03.2010

2 page 2 – 23.03.2010 © 2000 Roger Edwards Motivation Lightning is a high-impact weather phenomenon! timely & accurately forecast lightning future lightning watch/warning products in Canada? 9-10 deaths & 92-164 injuries in Canada each year! (Mills et al. 2008)

3 page 3 – 23.03.2010 © 2000 Roger Edwards Purpose To investigate the potential use of radar echoes in nowcasting cloud-to-ground (CG) lightning initiation –To determine a reflectivity threshold value that best predicts the onset of CG lightning –To find any correlation between radar echo tops and CG lightning initiation –To study differences (if any) between negative and positive CG lightning initiation in terms of radar characteristics

4 page 4 – 23.03.2010 © 2000 Roger Edwards Data Lightning data from CLDN –Detection efficiency ≥ 90%; location accuracy within 0.5 km Radar data from URP –Horizontal resolution ~ 1 km –Temporal resolution ~ 10 min –Data from the King City Radar (WKR) only ▪Domain of study

5 page 5 – 23.03.2010 © 2000 Roger Edwards Data ‘Airmass’ thunderstorms CG lightningNo CG lightningTotal negative 1st flash positive 1st flash both 1st flash 636866143 143 cases of airmass thunderstorms from Jun- Aug 2008 A ‘case’ consists of one cell or a cluster of cells on a radar display that may or may not eventually produce lightning

6 page 6 – 23.03.2010 © 2000 Roger Edwards Methods: the premise Graupel-ice mechanism for cloud electrification –larger riming graupel and smaller ice crystals collide, and consequently electric charges are exchanged by these hydrometeors –rebounding ice crystals tend to become positively charged, while graupel particles become negatively charged –occur in the mixed-phase region in or near a storm updraft

7 page 7 – 23.03.2010 © 2000 Roger Edwards Methods: the premise cloud electrification within a storm updraft (MacGorman and Rust 1998) ice crystals graupel particles in mixed-phase layer main negative charge region constant altitudes where CG lightning is often initiated -20°C -10°C

8 page 8 – 23.03.2010 © 2000 Roger Edwards Methods What reflectivity threshold value at which temperature level can best predict the onset of CG lightning? Recall one of the objectives from earlier… Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -20XXXXXn/a -15XXXXXn/a -10n/a XXXX altitude?? temperature upper air sounding data

9 page 9 – 23.03.2010 © 2000 Roger Edwards Methods: x-section of a case Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -20n/a -15Xn/a -10n/a 2120Z 18 Aug 2008 2130Z 18 Aug 2008 2140Z 18 Aug 2008 -10°C -15°C -20°C Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -20XXn/a -15XXn/a -10n/a X Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -20XXXn/a -15XXXXn/a -10n/a XXX Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -20XXXXn/a -15XXXXn/a -10n/a XXX Hit (H) Miss (M) False (FA) Alarm Lead time [min] Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -20HHHHn/a -15HHHHn/a -10n/a HHH Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -20HHHHMn/a -15HHHHMn/a -10n/a HHHM Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -20HHHHMn/a -15HHHHMn/a -10n/a HHHM Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -2030 200Mn/a -15403020 Mn/a -10n/a 3020 M 2200Z 18 Aug 2008

10 page 10 – 23.03.2010 © 2000 Roger Edwards Findings: r eflectivity threshold POD [%] Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -209996907055n/a -15100 969173n/a -10n/a 100 8864 Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -20363127107n/a -15443931235n/a -10n/a 4131168 FAR [%]

11 page 11 – 23.03.2010 © 2000 Roger Edwards Findings: reflectivity threshold CSI [%] Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -206467686552n/a -155661677170n/a -10n/a 59697660 Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -20191713106n/a -152322191410n/a -10n/a 23191713 Average lead time [min] (±5 min) Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -206467686552n/a -155661677170n/a -10n/a 59697660 Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -20191713106n/a -152322191410n/a -10n/a 23191713 FAR ave. lead time

12 page 12 – 23.03.2010 © 2000 Roger Edwards Findings: echo top threshold Things to keep in mind: –Echo tops in relation to only warm season lightning –Echo tops of convections on warmer days higher than those during cooler days –Higher echo tops stronger updrafts –Weak updrafts cannot produce intense electrification needed to generate lightning

13 page 13 – 23.03.2010 © 2000 Roger Edwards Findings: echo top threshold Maximum echo top prior to or at the start of CG lightning activity altitude of 7 km ~ -13 to -29°C levels

14 page 14 – 23.03.2010 © 2000 Roger Edwards Findings: vs Things to keep in mind: –small sample size Number of lightning-producing cases ‘-’ first lightning flash ‘+’ first lightning flash Both ‘-’ & ‘+’ total 636877 –Cases with both polarities were counted towards both ‘-’ and ‘+’ cases 77 6

15 page 15 – 23.03.2010 © 2000 Roger Edwards Findings: vs Initial lightning flash location to storm location of maximum reflectivity on MAXR [km] x

16 page 16 – 23.03.2010 © 2000 Roger Edwards Findings: vs Initial lightning flash location to storm location of maximum reflectivity on MAXR [km] mean2.23.5 median1.92.5 longest7.511.2 shortest0.0 storm location of max. reflectivity highly-reflective graupel concentrated main negative charge cloud region (± 0.5)

17 page 17 – 23.03.2010 © 2000 Roger Edwards Findings: vs Reflectivity threshold predictors Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -20 100 9397 9390 9370 7954 79n/a -15 100 97 9392 9372 93n/a -10 n/a 100 87 10068 64 Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -20 37 7633 7228 6611 357 21n/a -15 46 8141 7833 7224 626 19n/a -10 n/a 43 7933 7117 488 31 Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -20 63 2366 2767 3365 5551 65n/a -15 54 1959 2266 2771 3769 76n/a -10 n/a 57 2167 2974 5264 50 P O D F A R C S I ?

18 page 18 – 23.03.2010 © 2000 Roger Edwards Findings: vs Reflectivity threshold predictors –Average lead time [min] (±5 min) Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -2019 1518 1414 811 5 7 3n/a -1524 1523 1520 1514 1010 3n/a -10n/a 24 1620 1318 914 10 green = ‘-’ first lightning flashes red = ‘+’ first lightning flashes Temp level [ºC] Radar reflectivity threshold value [dBZ] 202530354045 -2019 1518 1414 811 5 7 3n/a -1524 1523 1520 1514 1010 3n/a -10n/a 24 1620 1318 914 10

19 page 19 – 23.03.2010 © 2000 Roger Edwards Findings: summary -10ºC / 40 dBZ could best predict the onset of CG lightning –POD=88% FAR=16% CSI=76% –Lead time ~ 17±5 minutes Trade-off between the lead time and FAR Echo tops ≥ 7 km –used in conjunction with reflectivity threshold to improve accuracy Above results are supported by other studies –e.g., Krehbiel 1986; Gremillion and Orville 1999; Vincent et al. 2004; Wolf 2007

20 page 20 – 23.03.2010 © 2000 Roger Edwards Findings: summary Negative vs. positive first lightning flashes –Negative flashes were located closer to the main negative charge region in a storm cloud –No definitive difference in skills to forecast lightning of different polarities –Positive-first-lightning-producing storm clouds became strongly electrified faster than negative- lightning-producing storm clouds

21 page 21 – 23.03.2010 © 2000 Roger Edwards Conclusions Potential to use radar echo reflectivity to nowcast CG lightning initiation Much more work is needed in developing a lightning nowcast algorithm in a future nowcasting software application tool

22 page 22 – 23.03.2010 © 2000 Roger Edwards Thanks National Laboratory for Nowcasting & Remote Sensing Meteorology Ontario Storm Prediction Centre Ed Becker, Glenn Robinson, Paul Joe, Norman Donaldson, Dave Hudak, and Syd Peel

23 page 23 – 23.03.2010 © 2000 Roger Edwards Outline Why… What purpose… How… What findings… What conclusions… Thanks to…

24 page 24 – 23.03.2010 © 2000 Roger Edwards What findings… vs Magnitude of electric current [kA] mean14.121.9 median12.222.6 maximum33.130.5 minimum2.415.5

25 page 25 – 23.03.2010 © 2000 Roger Edwards Methods Average altitudes corresponding to different temperature levels for the time periods examined in the study

Download ppt "© 2000 Roger Edwards Investigating the Potential of Using Radar to Nowcast Cloud-to-Ground Lightning Initiation over Southern Ontario 18 th Annual GLOMW."

Similar presentations

EXPLORING THE USE OF A PHYSICALLY BASED LIGHTNING CESSATION NOWCASTING TOOL E. V. Schultz 1, W. A. Petersen 2, L. D. Carey 1 1 Univ. of Alabama in Huntsville.

EXPLORING THE USE OF A PHYSICALLY BASED LIGHTNING CESSATION NOWCASTING TOOL E. V. Schultz 1, W. A. Petersen 2, L. D. Carey 1 1 Univ. of Alabama in Huntsville.
WSR-88D Signatures Associated with One Inch Hail in the Southern Plains Dennis E. Cavanaugh Jessica A. Schultz National Weather Service Weather Forecast.

WSR-88D Signatures Associated with One Inch Hail in the Southern Plains Dennis E. Cavanaugh Jessica A. Schultz National Weather Service Weather Forecast.
A Microwave Retrieval Algorithm of Above-Cloud Electric Fields Michael J. Peterson The University of Utah Chuntao Liu Texas A & M University – Corpus Christi.

A Microwave Retrieval Algorithm of Above-Cloud Electric Fields Michael J. Peterson The University of Utah Chuntao Liu Texas A & M University – Corpus Christi.
Cloud Flash Evaluation Issues and Progress Report Don MacGorman, NOAA/NSSL Al Nierow, FAA Dennis Boccippio, NASA/MSFC.

Cloud Flash Evaluation Issues and Progress Report Don MacGorman, NOAA/NSSL Al Nierow, FAA Dennis Boccippio, NASA/MSFC.
Thunderstorms. What Are Thunderstorms? Thunderstorms are the most common kind of severe storm. They form in clouds called thunderheads, or cumulonimbus.

Thunderstorms. What Are Thunderstorms? Thunderstorms are the most common kind of severe storm. They form in clouds called thunderheads, or cumulonimbus.
What kind of clouds have lightning?. Observing storms from space.

What kind of clouds have lightning?. Observing storms from space.
MICHELLE WILSON LIGHTNING. BACKGROUND- LIGHTNING Separation of charges within the thunderstorm Ice particles tend to be positively charged Mix of water.

MICHELLE WILSON LIGHTNING. BACKGROUND- LIGHTNING Separation of charges within the thunderstorm Ice particles tend to be positively charged Mix of water.
Inter-comparison of Lightning Trends from Ground-based Networks during Severe Weather: Applications toward GLM Lawrence D. Carey 1*, Chris J. Schultz 1,

Inter-comparison of Lightning Trends from Ground-based Networks during Severe Weather: Applications toward GLM Lawrence D. Carey 1*, Chris J. Schultz 1,
An analysis of cloud-to-ground (CG) strokes in China during 2010-2013 and the spatial distribution of CG with severe thunderstorm wind LAC S Laboratory.

An analysis of cloud-to-ground (CG) strokes in China during and the spatial distribution of CG with severe thunderstorm wind LAC S Laboratory.
Thunderstorms One of Natures Most Exotic Events Unlike ordinary rain storms, thunderstorms have a delicate balance of airborne water vapor that is whipped.

Thunderstorms One of Natures Most Exotic Events Unlike ordinary rain storms, thunderstorms have a delicate balance of airborne water vapor that is whipped.
Predicting lightning density in Mediterranean storms based on the WRF model dynamic and microphysical fields Yoav Yair 1, Barry Lynn 1, Colin Price 2,

Predicting lightning density in Mediterranean storms based on the WRF model dynamic and microphysical fields Yoav Yair 1, Barry Lynn 1, Colin Price 2,
Opportunities for Atmospheric Electricity and Lightning studies at DUSEL Richard Sonnenfeld Physics Department New Mexico Tech Kenneth Eack Los Alamos.

Opportunities for Atmospheric Electricity and Lightning studies at DUSEL Richard Sonnenfeld Physics Department New Mexico Tech Kenneth Eack Los Alamos.
Using WSR-88D Reflectivity for the Prediction of Cloud-to- Ground Lightning Nowcasting a storm’s first strike Brandon Vincent NWS-Newport Larry Carey Texas.

Using WSR-88D Reflectivity for the Prediction of Cloud-to- Ground Lightning Nowcasting a storm’s first strike Brandon Vincent NWS-Newport Larry Carey Texas.
Lightning and Storm Electricity Research Don MacGorman February 25–27, 2015 National Weather Center Norman, Oklahoma.

Lightning and Storm Electricity Research Don MacGorman February 25–27, 2015 National Weather Center Norman, Oklahoma.
TRMM Observations of Convection over the Himalayan Region R. A. Houze and D. C. Wilton University of Washington Presented 1 February 2005 at the International.

TRMM Observations of Convection over the Himalayan Region R. A. Houze and D. C. Wilton University of Washington Presented 1 February 2005 at the International.
Severe Squall Line over Quebec August 18th 2008 Robert Michaud QSPC – Montreal October 29th 2008.

Severe Squall Line over Quebec August 18th 2008 Robert Michaud QSPC – Montreal October 29th 2008.
Aerosol effects on rain and hail formation and their representation using polarimetric radar signatures Eyal Ilotovich, Nir Benmoshe and Alexander Khain.

Aerosol effects on rain and hail formation and their representation using polarimetric radar signatures Eyal Ilotovich, Nir Benmoshe and Alexander Khain.
On the relationship of in-cloud convective turbulence and total lightning Wiebke Deierling, John Williams, Sarah Al-Momar, Bob Sharman, Matthias Steiner.

On the relationship of in-cloud convective turbulence and total lightning Wiebke Deierling, John Williams, Sarah Al-Momar, Bob Sharman, Matthias Steiner.
Anticipating Cloud-to-Ground (CG) Lightning Utilizing Reflectivity Data from the WSR-88D. Pete Wolf, SOO National Weather Service Jacksonville, Florida.

Anticipating Cloud-to-Ground (CG) Lightning Utilizing Reflectivity Data from the WSR-88D. Pete Wolf, SOO National Weather Service Jacksonville, Florida.
The Lightning Warning Product Fifth Meeting of the Science Advisory Committee 18-20 November, 2009 Dennis Buechler Geoffrey Stano Richard Blakeslee transitioning.

The Lightning Warning Product Fifth Meeting of the Science Advisory Committee November, 2009 Dennis Buechler Geoffrey Stano Richard Blakeslee transitioning.

Similar presentations

Ads by Google