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Severe Weather/Lightning: Operational Perspective

Severe Weather/Lightning: Operational Perspective. Brian Carcione WFO Huntsville, Alabama. Introduction. Through improved modeling, research, etc., short/medium-range prediction of ingredients for severe convective storms has improved greatly

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Severe Weather/Lightning: Operational Perspective

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  1. Severe Weather/Lightning:Operational Perspective Brian Carcione WFO Huntsville, Alabama

  2. Introduction • Through improved modeling, research, etc., short/medium-range prediction of ingredients for severe convective storms has improved greatly • Severe weather: > 1” hail, > 58 MPH wind gusts, ortornadoes • Bigger challenges persistin the “near” term (0-6 hr) SPC Day 4-8 Outlook issued 23 April 2011

  3. Near-Term Overview • Local severe weather operations boil down to anticipationand validation • Anticipation: how will things evolve/change? • Validation: are expected/current conditions valid/reasonable? • Main questions during severe weather: • Where & when will storms develop? • How will storm impacts evolve, or how is environment evolving? • Which storms have the greatest chance of threatening life and property?

  4. Near-Term Overview • Models/analyses like the SPC Mesoanalysis site or HRRR/RAP are increasingly reliable and useful, but there are limitations (and always will be) • Anticipation, not validation • Forecasters often seek a “sanity check” of environmental data, often looking at direct observations (balloon data, surface obs, etc.) • Validation, not anticipation

  5. Where & when will storms develop? • Indirect: • CIMSS NearCast • Direct: • University of Alabama in Huntsville SATCAST • CIMSS Cloud Top Cooling SATCAST 1925 UTC CTC 1945 UTC

  6. How will storm impacts evolve? • CIMSS NearCast • MODIS/VIIRS Air Mass RGB • Assimilation of ABI data into NWP/analyses Multiple large hail reports 2130-2200 UTC 16 May 2012 – 1930 UTC

  7. Which storms have the greatest chance of threatening life/property? • CIMSS Cloud Top Cooling • Total Lightning Information • Pseudo-Geostationary Lightning Mapper • Earth Networks Total Lightning Network

  8. PGLM - 2 March 2012 (1445 UTC) Huntsville

  9. PGLM - 2 March 2012 (1459 UTC)

  10. Future Challenges • Operational meteorologists must cope with increasing “firehose” of data, while providing more services • New models with increasing resolution, Dual-Pol Radars (2-3x the base data), GOES-R/JPSS • Decision Support, Social Media, etc.

  11. Algorithms & Applications • Lightning jump algorithm for GLM/ENTLN/LMAs has tremendous potential (albeit with some caveats) • Other brainstorms: • Thermal boundary detection • Wind/wind shear calculations • Varied lightning safety applications • Assimilation into Warn-On-Forecast

  12. UAH SATCAST (Initiation, identification/tracking) Unified Algorithm Concept • CIMSS NearCast (Thermal Environment) • What if we put many of the existing concepts together? • Intermediate step between Warn-On-Detection (current) and Warn-On-Forecast (future) • Possibly less expensive computationally than high-res, high-refresh NWP? Available at local WFO? • Forecaster interactivity: manually start the algorithm on a cell, or interrupt if not feasible • CIMSS Cloud-Top Cooling (Intensification) • CIMSS NearCast (Thermal Environment, GLM Check) • GLM/Lightning Jump (Severe Intensification)

  13. Closing Thoughts • Next-gen satellite data has great potential to help with severe weather operations, both anticipation and validation, bridging an important gap between NWP and radar • Algorithms/data need to answer at least one of the “key questions” mentioned earlier • Research & operations communities must continue to engage one another to answer the right questions, in the right ways

  14. Thank you!Any questions? brian.carcione@noaa.gov Acknowledgements: Geoffrey Stano (SPoRT), Kris White and Chris Darden (NWS)

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