World-Wide Lightning-Location Network: WWLLN & Tropical-Cyclone Monitoring Natalia Solorzano Jeremy Thomas Robert Holzworth Reported by: Abram R. (“Abe”)

Slides:



Advertisements
Similar presentations
Structure & Structure Change IWTC VI, Topic 1 Chair: Jeff Kepert (Substituting for Hugh Willoughby) Rapporteurs Environmental Effects (E. Ritchie) Inner.
Advertisements

A Blended, Multi-Platform Tropical Cyclone Rapid Intensification Index
1 6th GOES Users' Conference, Madison, Wisconsin, Nov 3-5 WMO Activities and Plans for Geostationary and Highly Elliptical Orbit Satellites Jérôme Lafeuille.
AMS Hurricane and Tropical Meteorology Conference Tucson May 9, 2010 Vertical distribution of radar reflectivity in eyewalls observed by TRMM Deanna A.
First Flights of High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) During GRIP Lihua Li, Matt Mclinden, Martin Perrine, Lin Tian, Steve Guimond/
Hurricanes. Midlatitude Cyclones vs. Tropical Storms  Midlatitude Cyclones  Cover large area  Have cold fronts and warm fronts  Less violent (except.
Validation of the Ensemble Tropical Rainfall Potential (eTRaP) for Landfalling Tropical Cyclones Elizabeth E. Ebert Centre for Australian Weather and Climate.
Geostationary Lightning Mapper (GLM) 1 Near uniform spatial resolution of approximately 10 km. Coverage up to 52 deg latitude % flash detection day.
February 5th, TRMM Conference The 3-D Reflectivity Structure of Intense Atlantic Hurricanes as seen by the TRMM PR Deanna Hence, Robert Houze.
Impacts of Soil Moisture on Storm Initiation Christopher M. Taylor Richard Ellis.
CONVECTION IN TROPICAL CYCLONES John Molinari and David Vollaro University at Albany, SUNY Northeast Tropical Conference Rensselaerville, NY June 2009.
A Case Study of Hurricane Formation in Strong Shear: Claudette (2003) Kay Shelton University at Albany, SUNY.
August- September NSF NOAA NRL NCAR UW UM 27th Conference on Hurricanes and Tropical Meteorology, Monterey, CA, 27 April 2006.
Three-Dimensional Precipitation Structure of Tropical Cyclones AMS Hurricane and Tropical Meteorology Conference May 2nd, 2008 Deanna A. Hence and Robert.
August- September NSF NOAA NRL NCAR UW UM AGU, San Francisco, 12 December 2006.
Principal Rainband of Hurricane Katrina as observed in RAINEX Anthony C. Didlake, Jr. 28 th Conference on Hurricanes and Tropical Meteorology April 29,
Impact of the 4D-Var Assimilation of Airborne Doppler Radar Data on Numerical Simulations of the Genesis of Typhoon Nuri (2008) Zhan Li and Zhaoxia Pu.
Analysis of High Resolution Infrared Images of Hurricanes from Polar Satellites as a Proxy for GOES-R INTRODUCTION GOES-R will include the Advanced Baseline.
Vortex Rossby Waves in Hurricanes Katrina and Rita (2005) Falko Judt and Shuyi S. Chen Rosenstiel School of Marine and Atmospheric Science, University.
WWLLN (World Wide Lightning Location Network) By Prof. Robert Holzworth, Director of WWLLN, University of Washington.
The Rapid Intensification of Hurricane Karl (2010): Insights from New Remote Sensing Measurements Collaborators: Anthony Didlake (NPP/GSFC),Gerry Heymsfield.
Current status of AMSR-E data utilization in JMA/NWP Masahiro KAZUMORI Numerical Prediction Division Japan Meteorological Agency July 2008 Joint.
Jonathan Vigh NCAR Earth Systems Laboratory & Advanced Study Program Research Review 10:00 AM 27 May 2010 FL NCAR is sponsored by the National Science.
GOES-R Risk Reduction New Initiative: Storm Severity Index Wayne M. MacKenzie John R. Mecikalski John R. Walker University of Alabama in Huntsville.
© 2015 AQA. Created by Teachit for AQA What am I?
Possible impacts of improved GOES-R temporal resolution on tropical cyclone intensity estimates INTRODUCTION The Advanced Baseline imager (ABI) on GOES-R.
NASA GRIP 2010 Brief status report Ed Zipser, Univ. of Utah, Salt Lake City, UT on behalf of the GRIP Science Team.
Christopher J. Schultz 1, Walter A. Petersen 2, Lawrence D. Carey 3* 1 - Department of Atmospheric Science, UAHuntsville, Huntsville, AL 2 – NASA Marshall.
Results from Vaisala’s long range lightning detection network (LLDN) tropical cyclone studies Nicholas W. S. Demetriades Applications Manager, Meteorology.
Update on 2011 National Hurricane Center Proving Ground Mark DeMaria, NESDIS/STAR PG All Hands Conference Call July 22,
Tropical Cyclone Intensity Forecasting National Hurricane Center.
Lightning Outbreaks in the Eyewall MET 614 Seminar Antti Pessi.
Is Weather Becoming More Extreme? By Matt and Mazin.
Hurricane Microphysics: Ice vs Water A presenation of papers by Willoughby et al. (1984) and Heymsfield et al. (2005) Derek Ortt April 17, 2007.
3D Vortex and Warm Core Structure for Selected HS3 Cases Using NCAR- NOAA Dropsonde Data Jeffrey B. Halverson, P.I. UMBC Alex Martin, UMBC.
The Impact of Lightning Density Input on Tropical Cyclone Rapid Intensity Change Forecasts Mark DeMaria, John Knaff and Debra Molenar, NOAA/NESDIS, Fort.
TropicalCyclone Tropical Cyclone Studies by Microwave Sensors Chandra Mohan Kishtawal ASDMOG ASD/MOG Space Applications Centre ISRO/MOP/SM-2.1.
Atlantic Simplified Track Model Verification 4-year Sample ( ) OFCL shown for comparison Forecast Skill Mean Absolute Error.
The Rapid Intensification of Hurricane Karl (2010): Insights from New Remote Sensing Measurements Anthony Didlake (NPP/GSFC),Gerry Heymsfield (GSFC), Paul.
TropicalM. D. Eastin Observing the Tropics. TropicalM. D. Eastin Outline Observing the Tropics Surface Observations Atmospheric Soundings Aircraft Satellites.
Analysis of Cloud-to-Ground Lightning Within 16 Landfalling Hurricanes Danielle Nagele.
Tropical Cyclone Rapid Intensity Change Forecasting Using Lightning Data during the 2010 GOES-R Proving Ground at the National Hurricane Center Mark DeMaria.
Assimilation of Lightning Data Using a Newtonian Nudging Method Involving Low-Level Warming Max R. Marchand Henry E. Fuelberg Florida State University.
Satellites Storm “Since the early 1960s, virtually all areas of the atmospheric sciences have been revolutionized by the development and application of.
Convective Oscillations in a Strongly Sheared Tropical Storm Jaclyn Frank and John Molinari The University at Albany, SUNY.
The National Hurricane Center GOES-R Proving Ground Mark DeMaria NOAA/NESDIS, Fort Collins, CO GLM Science Meeting, Huntsville, AL September 26,
Multi-Scale Analysis of the Kinematic and Thermodynamic Structure of TS Humberto Using Dropsonde and Satellite Data Jeffrey B. Halverson, UMBC Alex Martin,
Performance of an Objective Model for Identifying Secondary Eyewall Formation in Hurricanes Matthew Sitkowski CIMSS – University of Wisconsin Jim Kossin.
New Tropical Cyclone Intensity Forecast Tools for the Western North Pacific Mark DeMaria and John Knaff NOAA/NESDIS/RAMMB Andrea Schumacher, CIRA/CSU.
1 Current and planned research with data collected during the IFEX/RAINEX missions Robert Rogers NOAA/AOML/Hurricane Research Division.
INNER CORE STRUCTURE AND INTENSITY CHANGE IN HURRICANE ISABEL (2003) Shuyi S. Chen and Peter J. Kozich RSMAS/University of Miami J. Gamache, P. Dodge,
Shuyi S. Chen, Robert A. Houze Bradley Smull, David Nolan, Wen-Chau Lee Frank Marks, and Robert Rogers Observational and Modeling Study of Hurricane Rainbands.
“CMORPH” is a method that creates spatially & temporally complete information using existing precipitation products that are derived from passive microwave.
Diagnosing the Intensity of Super Typhoon Haiyan
Andrea Schumacher1, M. DeMaria2, and R. DeMaria1
EXTREME WINDS AND PRECIPITATION FROM SPACE
Using Lightning Data to Monitor the Intensification of Tropical Cyclones in the Eastern North Pacific By: Lesley Leary1, Liz Ritchie1, Nick Demetriades2,
Rosenstial School of Marine and Atmospheric Science
Mark DeMaria and John A. Knaff - NOAA/NESDIS/RAMMB, Fort Collins, CO
Accounting for Variations in TC Size
Paper Review Jennie Bukowski ATS APR-2017
Long Range Lightning Detection Estimated Median Location Accuracy
Severe Storm in Mecca, Saudi Arabia
Hurricanes.
MJO Modulation of Lightning in Mesoscale Convective Systems
Jennifer C. DeHart, Robert A. Houze, Jr. and Deanna A. Hence
The Inner-Core Temperature Structure of Hurricane Edouard (2014): Observations and Ensemble Variability Erin B. Munsell, Fuqing Zhang, Scott A. Braun,
Hurricane Michael Landfall GOES and NEXRAD Observations 10 October 2018.
Bell, M. M. , M. T. Montgomery, and W. -C
Xu, H., and X. Li, 2017 J. Geophys. Res. Atmos., 122, 6004–6024
Presentation transcript:

World-Wide Lightning-Location Network: WWLLN & Tropical-Cyclone Monitoring Natalia Solorzano Jeremy Thomas Robert Holzworth Reported by: Abram R. (“Abe”) Jacobson, ESS/UW (Earth & Space Sciences,University of Washington)

WWLLN – CG STROKE DETECTION EFFICIENCY Variation in the WWLLN CG stroke detection efficiency with NZLDN determined return stroke peak current for the old and new algorithms (Rodger et al., 2009) Variation in the WWLLN CG stroke detection efficiency with NZLDN determined return stroke peak current for the old and new algorithms (Rodger et al., 2009)

WLLNN location accuracy for Nargis Rodger et al., 2009

HURRICANE RITA – Category 5, Sept. 21 and 22, 2005 Max. intensity increase: Sept. 21, 2005

Similar results: Squires, 2006 EYEWALL LIGHTNING

Rita: max. intensity increase Sept. 21, 2005

Rita: Sept. 21, 14:00 – 15:00 UT Shao, 2005: UTC WWLLN UTC

Hurricane Katrina – Category 5 Max. intensity increase: Aug. 28, 2005

Katrina EYEWALL LIGHTNING: Max. intensity increase: 08/28/2005

Katrina- 08/28/2005 Shao, 2005 – (1) 17:30 – 19:30 UT (2) 21:30 – 23:30 UT WWLLN:

Hurricane Wilma – Category 5 Max. intensity increase: 10/19/2005

Wilma – Eyewall lightning

Durian - Supertyphoon EYEWALL LIGHTNING

Typhoon – Supertyphoon Chanchu EYEWALL LIGHTNING Max. intensity increase: May 14, 2006

Similar results: Squires and Businger, 2008 using LR-NLDN WWLLN EYEWALL LIGHTNING (< 100 km from storm center)

Rita: max. intensity increase Sept. 21, 2005

NARGIS - APRIL 30, 2008

Nargis eyewall lightning (<100 km from storm center) and max. sustained winds

Apr 27, 21 Z Apr 28, 12 Z Apr 28, 18 Z Apr 29, 00 Z

Nargis eyewall lightning (<100 km from storm center) and max. sustained winds

Apr 29, 18 Z April 30, 17:30 Z May 01, 09:00 Z May 01, 23:00 Z Prior to intensifi cation Intens ification Weakening

NARGIS APRIL 30, 17:00 UT These lightning are pinpointing the region of active convection in the eyewall. This active convection area is not evident by examining only the infrared data, which show a large area of cold cloud-tops in the inner core. The subsequent rapid strengthening of Nargis was underestimated by forecasters who relied mostly on infrared satellite images and did not use lightning data.

TRMM IMAGES TRMM 85 GHz 18:31 Z METEOSAT IR 18 Z WWLLN 17:30-18:30 Z TRMM APR 30, 03 Z – Prior to MAIN INTENSIFICATION