The Impact of Lightning Density Input on Tropical Cyclone Rapid Intensity Change Forecasts
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The Impact of Lightning Density Input on Tropical Cyclone Rapid Intensity Change
Forecasts
Mark DeMaria, John Knaff and Debra Molenar, NOAA/NESDIS, Fort Collins, CO
Robert T. DeMaria CIRA/CSU Fort Collins, COMichael J. Brennan, NWS/National Hurricane Center, Miami, FL
Nicholas Demetriades, Vaisala Inc., Tucson, AZ
Southern Thunder Workshop, Norman, OK July 11-14, 2011
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Outline
• Lightning activity and tropical cyclone intensity change
• Lightning density from WWLLN and rapid intensification (RI)
• Experimental RI forecast algorithm • Results from 2010 NHC GOES-R Proving Ground• Plans for 2011 NHC Proving Ground – Include rapid weakening and rapid intensification
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Lightning and TC Intensity Change• Cecil and Zipser (1999)
– More lightning in weaker storms– Little relationship with TC intensity change– Small OTD sample
• Squires and Businger (2008)– Eyewall lightning outbreaks during rapid intensification of Rita and Katrina
• Price et al. (2009) – Lightning increases related to rapid intensification– Time lag highly variable
• DeMaria and DeMaria (2009)– Rainband lightning most correlated with rapid intensification – Largest inner core lightning density with sheared systems
• Abarca et al. (2011)– Flash density smaller for hurricanes than non-hurricanes– More lightning for intensifying systems – Lightning distribution more symmetric for intensifying systems
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Data Sample for 2010 Experimental Forecast Algorithm
• Full lifecycle of all Atlantic and east Pacific tropical cyclones 2005-2009– Over water only
• Storm environmental variables from SHIPS intensity model database– SST, vertical shear, etc.
• Storm centered lighting density – WWLLN data w/ annual normalization to OTD/LIS– 6-hour composites– 100-km radial intervals 0 to 600 km
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2005-2009 Storm Tracks
East Pacific: 1327 cases from 90 tropical cyclonesAtlantic: 1154 cases from 86 tropical cyclones
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Rapid Intensification (RI)
• Increase in maximum winds of 30 kt or more in 24 hr– Difficult but important forecast problem
• ~10th percentile of long-term climatology • Environmental factors associated with RI– Low shear, large upper-level divergence– High oceanic heat content, warm SST, – high low-level RH– Cold and symmetric cloud tops (from GOES IR)– Some intensification in previous 12 hr
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Lightning Density vs. Radius for RI and non-RI Cases
Atlantic East Pacific
Lightning density also function of vertical shear, SST, initial intensity, etc.
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Experimental Forecast Algorithm:The Lightning-based Rapid Intensification Index (L-RII)
• Linear discriminant analysis– Optimally weights multiple inputs to separate data sample into 2 classes• RI and non-RI cases
• NHC operational RII algorithm includes 8 inputs• Add 2 lightning parameters for L-RII– Inner core density (0-100 km)– Rainband density (300-400 km)
• Versions with and without lightning from same developmental sample
• Provides probability of RI in the next 24 hr
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Normalized Discriminant Weights(Atlantic L-RII Algorithm)
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The GOES-R Proving Ground• GOES-R will include 16 channel advanced baseline
imager and geostationary lightning mapper (GLM)– Scheduled for late 2015
• Proving ground provides real-time demonstrations of GOES-R data and products to NWS forecasters – Run with proxy data
• 6 products demonstrated at NHC– Including experimental rapid intensity algorithm– GLM proxy from Vaisala GLD360 lightning locations
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Normalization of GLD360 data
• Spatially dependent adjustments to GLD360
• Based on 3 month overlap of WWLLN, GLD360– Oct-Dec 2009
Hurricane Ida Nov., 2009
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2010 Storm Tracks
East Pacific: 121 cases from 12 tropical cyclonesAtlantic: 291 cases from 21 tropical cyclones
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RII Verification Metrics
• Bias = ( Pf/Nobs ) - 1
• Brier Score = (1/Nf)[Pf – Pobs]2
• Threat Score = a/(a+b+c) from 2 by 2 contingency table– Area of overlap between forecast and observations – Find max TS for range of probability thresholds
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2010 Verification Results:Impact of Lightning Input (GLD-360)
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Evaluation of GLD360 to WWLLN Adjustment
• 2010 WWLLN data obtained in post season• Compare RII lightning parameters with GLD360 and WWLLN input
• Rerun 2010 RII forecasts with WWLLN-based parameters
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Comparison of RII Input Parameters with WWLLN and Vaisala GLD360
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2010 Verification Results:Impact of Lightning Input (WWLLN)
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Plans for 2011
• Add 2010 storm cases to developmental sample• Run lightning and no lightning version in 2011 NHC
Proving Ground – starts Aug. 1st
• Use real time WWLLN data feed– Consistent with developmental sample
• Generalize RII algorithm to also include over-water rapid weakening cases Decrease in maximum winds of at least 20 kt in 24 hr (~7th percentile)
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Hurricane Lili 2002120 to 80 kt in 18 hr before landfall
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2005-2010 Atlantic SampleLightning Density for RW, Avg, RI Cases
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Use of Lightning Asymmetry
Mean and Standard Deviation are Highly Correlated
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Conclusions • Large sample of lightning and large-scale data created
for Atlantic and east Pacific tropical cyclones• Experimental rapid intensification forecast algorithm
developed – Inner core and rainband lightning discriminators
• Independent cases from 2010 showed reduced bias, improved Brier Score in Atlantic and east Pacific
• 2011 algorithm will also include rapid weakening probability
• Real time runs begin Aug. 1st
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Back-Up Slides
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Qualitative Use of Lightning Time SeriesHurricane Danielle (2010) example
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Qualitative Use of Lightning Time SeriesTropical Storm Fiona (2010) example