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Lightning Assimilation Techniques for Enhanced Weather Forecasting

Explore the use of ensemble Kalman filter for lightning assimilation in the WRF model, enhancing forecast accuracy in data-sparse regions. Analysis of techniques, case studies from 2002-2006, and future work discussed.

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Lightning Assimilation Techniques for Enhanced Weather Forecasting

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  1. WRF-EnKF Lightning Assimilation Real-Observation ExperimentsOverview Cliff Mass, Greg Hakim, Phil Regulski, Ryan Torn Department of Atmospheric Sciences University of Washington February 15, 2008

  2. Overview • WRF-EnKF Overview • Lightning Assimilation Technique Review • Project Review • Model Estimate Experiments • Case Studies • December 2002 • October 2004 • November 2006 • Conclusions • In-progress/Future work

  3. The Use of EnKF for Lightning Assimilation • In this work the ensemble Kalman filter is applied using the WRF model (WRF-EnKF). • The covariance statistics from EnKF that spread the impact of observations are flow-dependent • Lightning observations are ideal to provide WRF-EnKF with more observational information in areas with few in situ observations (e.g. Pacific Ocean) • Impact of lightning observations will propagate into areas of high forecast impact (West coast and beyond)

  4. Lightning Assimilation Techniques • Original Lightning Experiment (LTNG2) • NLDN/LR lightning strike is detected • Lightning strike is converted into lightning rate from nearby LTNG observations • Lightning rate converted into convective rainfall rate using Pessi/Businger convective rain rate/lightning rate relationship • Convective rainfall (mm) is assimilated into WRF-EnKF • Successful test on Dec. 2002 case

  5. Lightning Assimilation Techniques • Minimal Counting Technique Lightning Experiment (LTNG4) • NLDN/LR lightning strike is detected • Lightning strike is converted into lightning rate from nearby LTNG observations • Once any nearby lightning strikes are used to calculate a lightning density they are no longer available as an assimilation point (although they are still used to calculate LTNG densities) • Lightning rate converted into convective rainfall rate using Pessi/Businger convective rain rate/lightning rate relationship • Convective rainfall (mm) is assimilated into WRF-EnKF • Successful testing on Dec. 2002 case

  6. Project Review • Research Completed • Dec. 2002 Test Case - Analysis and 12-hr Forecasts • Oct. 2004 Test Case - Analysis • Nov. 2006 Test Case - Analysis • Modifications to LTNG2 and LTNG4 models to improve analysis and forecasts • In-progress • Forecast analysis of Oct. 2004 Test Case • Forecast analysis of Nov. 2006 Test Case • 1-hr assimilation of cumulative convective rain rate data (previously using 6-hr cumulative totals) for LTNG2 and LTNG4 models

  7. Recent ExperimentsCan we further improve Dec 2002 performance? • Model-estimate and observations of cumulative convective precipitation calculated by LTNG density occasionally have large innovations leading to large increments in the model’s dynamical fields, possibly leading to locally unbalanced states • Set a upper bound on assimilated cumulative convective precipitation • Minimal Counting Technique Lightning Experiment (LTNG4) w/ modifications (LTNG5) • Same techniques as LTNG4 but with upper bound (18mm) • Less improvement in analysis and forecasts • Original LTNG4 still best performing model to test further on new regimes • Original Lightning Experiment (LTNG2) w/ modifications (LTNG6) • Same techniques as LTNG2 with upper bound (18mm) • Less improvement in analysis and forecasts • Original LTNG2 still best performing model to test further on new regimes • Another solution • Reduce cumulative value of convective rain assimilated from 6- to 1-hr block (In-progress)

  8. Case Study #1 – December 2002Minimum SLP recorded at extra-tropical cyclone’s center Limiting upper bound of cumulative convective precipitation degrades analysis performance (LTNG5/6) NCEP (black dashed) is NCEP subjective analysis

  9. Case Studies • Case #1: December 16-21, 2002 • Analysis • LTNG Analysis Impact of SLP, H500 fields • 12-hr Forecasts • GFS Analysis v. Fcst 12-hr Control • GFS Analysis v. Fcst 12-hr LTNG2 • GFS Analysis v. Fcst 12-hr LTNG4

  10. Major Findings • EnKF allows lightning to have a substantial influence on atmospheric analyses • The influence can be widespread over the domain

  11. Case Study #1 – December 2002Impact of Lightning Assimilation: LTNG2

  12. Case Study #1 – December 2002Impact of Lightning Assimilation: LTNG4

  13. Case Study #1 – December 2002Impact of Lightning Assimilation: LTNG2

  14. Case Study #1 – December 2002Impact of Lightning Assimilation: LTNG4

  15. Case Study #1 – December 2002Impact of Lightning Assimilation: LTNG2

  16. Case Study #1 – December 2002Impact of Lightning Assimilation: LTNG4

  17. Case Study #1 – December 2002Impact of Lightning Assimilation: LTNG2

  18. Case Study #1 – December 2002Impact of Lightning Assimilation: LTNG4

  19. Case Study #1 – December 2002Impact of Lightning Assimilation: LTNG2

  20. Case Study #1 – December 2002Impact of Lightning Assimilation: LTNG4

  21. Case Study #1 – December 2002Impact of Lightning Assimilation: LTNG2

  22. Case Study #1 – December 2002Impact of Lightning Assimilation: LTNG4

  23. Case Study #1 – December 2002Impact of Lightning Assimilation: LTNG2

  24. Case Study #1 – December 2002Impact of Lightning Assimilation: LTNG4

  25. The Impact on Forecasts Were Mixed

  26. Case Study #1 – December 200212-hr Forecast Comparison: Control

  27. Case Study #1 – December 200212-hr Forecast Comparison: LTNG2

  28. Case Study #1 – December 200212-hr Forecast Comparison: Control

  29. Case Study #1 – December 200212-hr Forecast Comparison: LTNG4

  30. Case Study #1 – December 200212-hr Forecast Comparison: Control

  31. Case Study #1 – December 200212-hr Forecast Comparison: LTNG2

  32. Case Study #1 – December 200212-hr Forecast Comparison: Control

  33. Case Study #1 – December 200212-hr Forecast Comparison: LTNG4

  34. Case Study #1 – December 200212-hr Forecast Comparison: Control

  35. Case Study #1 – December 200212-hr Forecast Comparison: LTNG2

  36. Case Study #1 – December 200212-hr Forecast Comparison: Control

  37. Case Study #1 – December 200212-hr Forecast Comparison: LTNG4

  38. Case Study #1 – December 200212-hr Forecast Comparison: Control

  39. Case Study #1 – December 200212-hr Forecast Comparison: LTNG2

  40. Case Study #1 – December 200212-hr Forecast Comparison: Control

  41. Case Study #1 – December 200212-hr Forecast Comparison: LTNG4

  42. Case Studies • Case #2: October 4-7, 2004 • Analysis • LTNG Analysis Impact of SLP, H500 fields • Number of LTNG strikes during test case is much smaller than Dec. 2002 case

  43. Case Study #2 – October 2004Impact of Lightning Assimilation: LTNG4

  44. Case Study #2 – October 2004Impact of Lightning Assimilation: LTNG4

  45. Case Study #2 – October 2004Impact of Lightning Assimilation: LTNG4

  46. Case Study #2 – October 2004Impact of Lightning Assimilation: LTNG4

  47. Case Study #2 – October 2004Impact of Lightning Assimilation: LTNG4

  48. Case Study #2 – October 2004Impact of Lightning Assimilation: LTNG4

  49. Case Study #2 – October 2004Impact of Lightning Assimilation: LTNG4

  50. Case Study #2 – October 2004Impact of Lightning Assimilation: LTNG4

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