1 / 35

Improving Tropical Cyclone Intensity Forecasts Using Lightning Observations

Improving Tropical Cyclone Intensity Forecasts Using Lightning Observations. Mark DeMaria NOAA/NESDIS/StAR, Fort Collins, CO Summer Thunder Workshop Cocoa Beach, Florida July 2009. Lightning in the Eye of Hurricane Felix (2007).

benny
Télécharger la présentation

Improving Tropical Cyclone Intensity Forecasts Using Lightning Observations

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Improving Tropical Cyclone IntensityForecasts Using Lightning Observations Mark DeMaria NOAA/NESDIS/StAR, Fort Collins, CO Summer Thunder Workshop Cocoa Beach, Florida July 2009

  2. Lightning in the Eye of Hurricane Felix (2007) Picture courtesy of Richard Henning, from the Air Force Reserve C-130

  3. Outline • The GOES-R Geostationary Lightning Mapper • Brief summary of previous TC lightning studies • Analysis of large TC data sample from the WWLLN • Experimental rapid intensification forecast algorithm

  4. Geostationary Lightning Mapper (GLM) on GOES-R • GOES-R will include a geostationary lightning mapper (GLM) • Will provide nearly continuous total lightning counts over most of the GOES-E and GOES-W field of view • Higher detection rates over tropical oceans than ground-based networks • Much better temporal resolution than polar satellite data

  5. Annual Lightning Density Over GOES Coverage Area* Reference: *From OTD/LIS instruments, slide provided by Steve Goodman

  6. Lightning Data for Hurricane Studies • Satellite • Lightning Imaging Sensor (LIS) on TRMM • Provides total lightning to ~35oN • Low time resolution • Optical Transient Detector (OTD) • Provides total lightning to ~80oN • Low time resolution • Ground based • National Lightning Detection Network (NLDN) • Near continuous cloud to ground counts and polarity • Restricted to within ~500 km of U.S. • Long-range Lightning Detection Network (LLDN) • Additional stations extend NLDN coverage into Caribbean • World Wide Lightning Locator Network (WWLLN) • Sparse network with nearly global coverage, but low detection frequency

  7. Lightning Structure of Tropical Cyclones from Previous Studies • Bi-modal radial structure • Max in eye-wall and rainbands, with min between • Eyewall lightning much more transient • Inner core lightning sometimes associated with intensification, but sometimes with eyewall replacement and weakening • Asymmetric structure related to environmental wind shear • Increase in lightning might be precursor to tropical cyclone genesis

  8. Analysis of Large Data Sample • WWLLN provides nearly global lightning data • Low detection rate • Use only reprocessed data with new UW algorithm • 2005-2008 • Calibrated by making annual lightning density match that from the TRMM annual climatology • Adjustment factors: 2005 = 38, 2006 = 24, 2007 = 23, 2008=16 • Composite lightning over 6 hour intervals in storm-relative coordinates • Cylindrical grid, r = 100 km,  = 45o • All Atlantic and East Pacific TCs with center over water for following 24 hr • 1057 cases from 66 Atlantic storms • 1019 cases from 69 East/Central Pacific storms • Combine with SHIPS intensity model database • Includes SST, shear, etc

  9. Tropical Cyclone Tracks2005-2008

  10. Lightning Density for Hurricane Felix 01 Sept. 2007 12 UTC – 03 Sept. 2007 21 UTC

  11. Azimuthal Mean Structure

  12. 0-100 km Lightning DensityAll Cases 2005-2008

  13. Cases with 0-100 km Lightning Density > 60 strikes/km2-year • Atlantic • Irene 050808, 35 kt, SST=27.7, weakening in high shear • Maria 050903, 50 kt, SST=28.5, intensifying in low shear • Philippe 050921, 45 kt, SST=29.6, weakening in high shear • Noel 071101, 50 kt, SST=28.8, ET transition in high shear • East Pacific • Adrian 050518 40 kt, SST=30.4, intensifying in low shear • Emilia 060723 50 kt, SST=28.8, weakening near land • John 060831 110kt, SST=30.1, weakening near land • Kristy 060905 35 kt, SST=27.4, steady state in low shear • Rosa 061109 35 kt, SST=29.5, weakening in high shear • Barbara 070531 35 kt, SST=30.6, intensifying in high shear near land • Kiko 071017 35 kt, SST=29.2, steady state in high shear • 10 of 11 cases were tropical storms • Only 4 of 11 intensified in the following 24 hr • High shear, warm SST, possible East Pac land influence

  14. Correlation of Lightning Density and 36 Max Wind Change

  15. Correlation of Lightning Density and SST

  16. Correlation of Lightning Density and Vertical Shear

  17. Low shear regime Low shear regime High shear regime High shear regime Vertical Shear vs. 200-300 km Lightning Density Atlantic East Pacific

  18. Discrimination of Rapid Intensification Cases • RI defined by max wind increase of 30 kt or more in next 24 hr • Kaplan and DeMaria (2003) definition • ~95th percentile • One of NHC’s primary forecast problems • Stratify sample into RI and non-RI cases • Different relationships in low-shear and high-shear regimes

  19. Lightning Density for Atlantic RI and non-RI Cases Low Shear High Shear

  20. Lightning Density for East Pacific and non-RI Cases Low Shear High Shear

  21. Experimental Rapid Intensity Forecast Algorithms • Discriminant analysis version • Generalization of operational version with lightning input • Rule-based system • Better suited to nonlinear relationships • Possible real time tests in 2010 • WWLLN or LLDN?

  22. Scaled WWLLN-LLDN Comparison2008 Annual Mean Lightning Density

  23. Scaled WWLLN-LLDN Comparison2008 Annual Mean Lightning Density

  24. 6 7 8 9 10 1 2 3 4 5 Diurnal Variation in WWLLN Detection Frequency?

  25. Summary • GOES-R will include the GLM • WWLLN data provides large data sample for TC lightning studies • Max lightning density near the storm center • Less lightning in east Pacific storms • Vertical shear/lightning relationship is nonlinear • Positive correlation in low shear regime • Negative correlation in high shear regime • Lightning correlation with intensity change enhanced in low shear regime • Max correlation at 200-400 km radius • Lightning density is discriminator of rapid intensity change, especially in the low shear regime

  26. Future Work • Examine lightning asymmetry • Develop experimental rapid intensity forecast algorithms • Discriminant analysis • Rule-based systems • Possible tests in GOES-R satellite proving ground in 2010 • Extend work to TC genesis

  27. Back-up Slides

  28. Radial Lightning Structure Reference: Convective Structure of Hurricanes as Revealed by Lightning Locations, Molinari et al 1999, MWR

  29. Lightning Time Evolution Reference: Convective Structure of Hurricanes as Revealed by Lightning Locations, Molinari et al 1999, MWR

  30. Rita and Katrina Inner Core Lightning Hurricane Rita Hurricane Katrina Fig. 3 Fig. 12 Reference: The Morphology of Eyewall Lightning Outbreaks in Two Category 5 Hurricanes, Squires and Businger 2008, MWR

  31. Vertical Shear and Lightning Structure Reference: The Effects of Vertical Wind Shear on the Distribution of Convection in Tropical Cyclones, Corbosiero and Molinari 2002, MWR

  32. LIS/OTD and WWLLN ComparisonAnnual Mean Lightning Density LIS/OTD Scaled 2007 WWLLN

  33. Lightning and TC Genesis Reference: East African Lightning as a Precursor of Atlantic Hurricane Activity, Price et al 2007, Geophysical Research Letters

  34. 4 3 2 1 Lightning Regions for WWLLN TC Genesis Study Main Development Region

  35. 2004 Lightning Density and TC Genesis Time Series

More Related