Title: Lightning Studies at Florida State University
1Lightning Studies at Florida State University
- Scott D. Rudlosky
- Ph.D. Candidate, Florida State University
- Henry E. Fuelberg
- Professor of Meteorology, Florida State University
2Prof. Fuelbergs Lightning Team
- Alumni
- Dr. Phillip Shafer
- NWS/MDL - Silver Springs, MD
- Dr. Geoffrey Stano
- ENSCO/SPoRT - Huntsville, AL
- Geoffrey Wagner
- RS Information/NWS-MDL - Silver Springs, MD
- Jessica Stroupe
- NWS WFO - Slidell, LA
- Current Students
- Amanda Hansen Ph.D. Candidate
- Scott Rudlosky Ph.D. Candidate
- Holly Anderson Masters Candidate
- Pete Saunders Masters Candidate
-
3Outline
- Background
- Past Research
- NWS WFO Tallahassee
- Florida Power and Light Corp.
- Geographic Information System Applications (CSTAR
and FPL) - Total Lightning Studies (NASA - Kennedy Space
Center) - Current and Future Research
- NASA KSC
- NOAA - COMET
- NOAA/NESDIS
4NWS WFO Tallahassee
- CG climatologies by flow regime
- Jessica Stroupe (M.S.)
- Vector mean wind between 1000 -700 hPa
- For warm season months of May through September.
- First guess for daily convective activity
associated with the sea breeze. - Used as input for probability of precipitation
(PoP) grids.
5FPL Lightning Guidance
- Forecasts for the occurrence of CG Lightning
- Dr. Philip Shafer
- Originally for 13 individual FPL service areas
(roughly half the size of a county). - Earliest equations utilized morning rawindsonde
data - Focused on populated regions
- FPL shifted focus
- Developed spatial forecast guidance product for
CG across the entire state of Florida.
6Objectives
FPL Lightning Guidance
- Type A composite sea-level pressure
Type A frequency 1800-2059 Z
Type B composite sea-level pressure
Type B frequency 1800-2059 Z
7FPL Lightning Guidance
June 4, 2004 1800-2059 Z period
- Utilized perfect prognosis (PP) technique
-
- Create a high-resolution, gridded forecast
guidance product for warm season CG - Used data from the Rapid Update Cycle (RUC) model
and CG data from the National Lightning Detection
Network (NLDN). - Most important derived parameters create 3-hourly
spatial probability forecasts for - The occurrence of one or more CG flashes.
- Chance of exceeding flash count percentile
thresholds. - Binary logistic regression for one or more
flashes - Negative binomial (NB) model the amount of
lightning.
8Positive CG Lightning Study
- Characteristics of positive CG (CG) lighting in
Florida - Masters thesis for Scott Rudlosky
- Phase 5 of FPL research
- Climatologies of total CG and CG lightning
prepared - Equations to predict percentage of CG created
- Valid within 100 km radius of sounding locations
- Equations for CG had two steps
- Sounding parameters correlated with percentage of
positive strikes for overall relationship - Stepwise linear regression then utilized
9Positive CG Lightning Study
- Several conclusions possible
- Percentage Positive increases as...
- Freezing level height increases
- 1000 700 hPa wind speed increases
- Showalter Stability Index increases
- Theta E at 850 hPa increases
- Percentage Positive decreases as
- Mean mixing ratio in lowest 100 hPa increases
- Surface to 1 km shear increases
- Total Totals increases
- Pressure at -10 C increases
- Results agree with the literature in that
low-level moisture decreases the relative amount
of CG.
- Low level mean wind speed seems more influential
than shear magnitude.
10Misclassification of Cloud Pulses
- Prior to the 2002-2003 upgrade, a threshold of
10 kA was recommended. Afterwards, the
threshold was changed to 15 kA (Biagi et al
2007). - The (small) population of positive discharges
between 10-20 kA are a mix of CG and cloud
discharges (Cummins et al. 2006). - This population is far from small during the warm
season in Florida.
11Geographic Information System
- Geographic Information System (GIS) software
provides new approaches to analyze CG lightning
data. - GIS has many applications for lightning research
- Visualization of data
- Computation of cell statistics
- Locating/Analyzing strikes of interest
- Incorporation of elevation data sets
- Interrogation of multiple data sets within a
common framework - GIS Advantages
- Avoid complex Fortran gridding programs.
- Data analysis and visualization are in same
software.
12GIS Applications
- U.S. Park Service gridding tool is used to
produce a grid with the desired cell size and
spacing. - Individual strikes are joined to the grid (i.e.,
each flash is assigned a grid cell), and are then
summed and combined to produce flash densities.
22 km Grid
Individual CG Flashes
Sum of CG Flashes
13GIS Applications
- GIS files are easily manipulated for flash
densities and cell statistics. - GIS allows comparisons with other data sets
(i.e., precipitation, elevation, wildfires,
etc.). - Extremely fine grid spacing allows identification
of several grid cells with greater than 25
flashes km-2 year-1.
14GIS Applications
- Forecast equations for thunderstorm development
- By Masters Student Geoffrey Wagner
- For West Texas and New Mexico regions
- Utilize sounding, reanalysis, elevation and NLDN
data - This research differs from our previous studies
in that
- Topography is the dominant forcing mechanism.
- GIS computes the aspect ratio and slope for each
grid cell. - Study attempts to predict the initiation of
thunderstorms (i.e., the first CG flash) during a
specified time period.
Data from the United States Geological Survey
(USGS) National Elevation Dataset (NED)
15GIS Applications
- Binary Logistic Regression (BLR) techniques
developed statistical relations between lightning
initiation and candidate predictors. - Equations developed and employed to produce
deterministic and probabilistic forecasts for
thunderstorm initiation.
16GIS Applications
- Scott Rudlosky (Ph.D. Candidate) related
wildfires with CG flashes and precipitation
estimates. - Database contains the location of each wildfire,
statistics on CG within 2 km, and a 24 h
precipitation estimate. - Over 70 of all reported lightning initiated
wildfires during May, June, and July 2007 were
physically linked to CG lightning. - Positive lightning was associated with less than
7 of all lightning induced wildfires.
17Total Lightning Studies
- Our total lightning studies utilized the
Lightning Detection and Ranging (LDAR) network at
Kennedy Space Center (KSC).
- Dr. Geoffrey Stano employed a flash consolidation
algorithm to combine individual sparks into
flashes. (Murphy et al. 2000 McNamara 2002
Nelson 2002)
18Total Lightning Studies
- KSC is one of the few regions in the U.S. that
issues lightning advisories. - The U.S. Air Forces 45th Weather Squadron (45WS)
has a good record of forecasting the initiation
of lightning. - When should an advisory be canceled?
- Dr. Geoffrey Stano examined LDAR, CG, sounding,
and WSR-88D data to produce lightning cessation
guidelines.
19Current Research
2052 UTC 6 June 2007
- Continuing cessation studies
- Masters student Holly Anderson
- New techniques utilizing WDSS-II
Reflectivity at 0 C
30 dBZ Cluster
Reflectivity at -20 C
Reflectivity at -10 C
20Current Research
- Expanding CG forecast techniques to new locations
- Pete Saunders (Masters Student)
- Through COMET
- NWS WFO Pueblo, CO
- NWS WFO Pendleton, OR
- NWS WFO Sterling, VA
- Combining and applying earlier techniques
- Dr. Phil Shafer for Florida
- Geoffrey Wagner for West Texas New Mexico
Images courtesy of Steven Hodanish
21Current Research
- Ph.D. Candidate Scott Rudlosky is working on
Optimizing the Use of Lightning Data in Severe
Storm Warning Assessment. - Project relies heavily on newly developed WDSS
techniques and algorithms which have yet to be
created. - Data will include LMA/LDAR total lightning data,
NLDN CG lightning data, RUC-derived model data,
WSR-88D data, and new data sets as they become
available. - Our goal is procedures and/or guidelines to
optimally utilize total lightning data from the
GOES-R Global Lightning Mapper (GLM), thereby
leading to more accurate severe storm warnings.
22Conclusions
- The Fuelberg Lightning Group at Florida State
University continues to focus on operational
lightning research. - This approach has benefited both the public (NWS,
NASA, KSC, FDOF) and private (FPL) sectors. - Our research fits into four general categories
- Forecasting CG lightning in the 0-24 h time range
- Forecasting lightning cessation
- Analyzing the relationship between environmental
conditions and lightning patterns within severe
and non-severe storms - Relating lightning and precipitation to the
initiation of wildfires
23Conclusions
- Several key aspects include
- Newly developed GIS techniques
- Algorithm creation within the WDSS-II software
- Collaborations with the public and private
sectors - Innovative tools and procedures
- Preparing for new datasets to help ease
transition - Looking ahead to the GLM and polarimetric radar
- Will have the tools necessary to make optimal use
of these data
24References
- Lakshmanan, V., T. Smith, G. J. Stumpf, and K.
Hondl, 2007 The warning decision support system
- integrated information (WDSS-II). Weather and
Forecasting, 22, No. 3, 592-608. -
- Lericos, T. P., H. E. Fuelberg, A. I. Watson, and
R. L. Holle, 2002 Warm season lightning
distributions over the Florida peninsula as
related to synoptic patterns. Wea. Forecasting,
17, 83-98. -
- McNamara, T. M., 2002 The horizontal extent of
cloud-to-ground lightning over the Kennedy Space
Center, M.S. Thesis, Air Force Institute of
Technology, 114 pp. - Murphy, M. J., K. L. Cummins, and L. M. Maier,
2000 The analysis and interpretation of
three-dimensional lightning flash information.
16th Int. Conf. on IIPS for Meteorology,
Oceanography, and Hydrology, Long Beach, CA,
Amer. Meteorol. Soc., 102-105. - Nelson, L. A., 2002 Synthesis of 3-dimensional
lightning data and radar to determine the
distance that naturally occurring lightning
travels from thunderstorms, M.S. Thesis, Air
Force Institute of Technology, 85 pp. - Rudlosky, S.D., and H. E. Fuelberg, 2007
Characteristics of positive cloud-to-ground
lightning. M.S. Thesis, Florida State University. -
- ___, and ___, 2007 The relation between
lightning and wildfires in Florida, Third
Conference on Meteorological Applications of
Lightning Data, American Meteorological Society
(AMS), New Orleans, Louisiana, Jan 21 Jan 23,
2008, P2.6. -
Shafer, P. E., and H. E. Fuelberg, 2006 A
statistical procedure to forecast warm season
lightning over portions of the Florida peninsula.
Wea. Forecasting, 21, 851-868. ___, and ___,
2007 A perfect prognosis scheme for forecasting
warm season lightning over Florida. Accepted by
Mon. Wea. Rev. Smith, J. R., H. E. Fuelberg,
and A. I. Watson, 2005 Warm season lightning
distributions over the northern Gulf of Mexico
coast and their relation to synoptic-scale and
mesoscale environments. Wea. Forecasting, 20,
415-438. Stano, G. T., 2007 Developing
empirical lightning forecast guidance for the
Kennedy Space Center. Ph.D. Dissertation,
Florida State University. Wagner, G. A., H. E.
Fuelberg, D. Kann, R. Wynn, and S. Cobb, 2005 A
GIS-based approach to lightning studies for west
Texas and New Mexico. Second Conference on
Meteorological Applications of Lightning Data,
American Meteorological Society (AMS), Atlanta,
Georgia, Jan 30 Feb 1, 2006. Wolf, P., 2006
Anticipating the initiation, cessation, and
frequency of cloud-to-ground lightning utilizing
WSR-88D reflectivity data, available from the
author at NWS Jacksonville FL.
25- Lightning Parameterization Module
- WRF CHEM
- Accurately specify NOx produced by lightning
- Tropospheric ozone forecasts
- WDSS-II
- Relate storm parameters to lightning