1. 111 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration The WRF Lightning Forecast Algorithm: Performance review and updates to allow characterization of lightning jumps in simulated storms Photo, David Blankenship Guntersville, Alabama E. W. McCaul, Jr. 1, J. L. Case 2, T. Chronis 3, and S. J. Goodman 4 1.USRA Huntsville; 2. ENSCO NASA SPoRT; 3. Univ. of Alabama Huntsville; 4. NOAA/NESDIS GOES-R GLM Science Meeting September, 2016

2. 222 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Motivation: Compare coverage CAPE vs LFA LTG1

3. 333 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration LFA Objectives Given LTG link to large ice, and a cloud-scale model like WRF, which prognoses hydrometeors, LFA seeks to: 1.Create WRF forecasts of LTG threat (1-48 h), based on simple proxy fields from explicitly simulated convection; 2. This statistically calibrated threat should yield accurate quantitative peak total flash rate densities and threat areas for the strongest storms, based on LMA or other total LTG observations; 3. Strongest storms prioritized due to their impact and predictability; weaker storms should be handled reasonably well; 4. Robust algorithm needed for use in making proxy LTG data, and for potential uses with DA

4. 444 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration LFA Objectives Since LFA is designed to retain sensitivity to storm time variations, we ask: do LFA lightning jumps occur? 1.Extend existing WRF p-p software to time tendencies of fields, based on 2 min discretization (5 time steps) 2.As storms approach a gridpoint, time tendencies of FRD are positive; as storms recede, tendencies are negative 3.Using existing hourly max routine, compute 1-h max of positive tendencies, and 1-h min of negative tendencies 4.If storms are steady and quasi-symmetric, these tendencies cancel; if unsteady, there are residuals: jumps, lulls 5. Sum the positive and negative tendencies to create plots of FRD jumps, lulls; compare to other fields, obs

5. 555 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Calibration Curve LTG1 (FLX) F 1 = 0.042 FLX F 1 > 1.50 r = 0.67 Units of F 1 are fl/km 2 /5 min

6. 666 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Calibration Curve LTG2 (VII) F 2 = 0.2 VII F 2 > 0.4 r = 0.83 Units of F 2 are fl/km 2 /5 min

7. 777 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Construction of blended threat: 1. LTG1 and LTG2 both originally calibrated to yield correct peak flash rate density (FRD) for strongest storms, based on LMA; 2. The peaks of LTG1 and LTG2 also tend to be coincident in all simulated storms, but LTG2 covers more area; 3. Thus, weighted averages of the 2 threats will also yield the correct peak FRDs; set a threshold to get areas correct; 4. To preserve most of time variability in LTG1, use large weight w 1 5. To preserve areal coverage from LTG2, avoid very small weight w 2 6. Tests using 0.95 for w 1, 0.05 for w 2, yield satisfactory results; 7. Thus, set LTG3 = 0.95*LTG1 + 0.05*LTG2; LTG3 > 0.072

8. 888 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration LTG Threat Methodology: Advantages Can provide quantitative estimates of FRD fields; use of well-chosen thresholds allows for accurate threat areal coverage; Methods based on LTG physics; should be accurate, robust and regime-independent; Methods are fast and simple; based on fundamental model output fields; no need for complex, expensive electrification modules; LFA is flexible; for new model config, adjust LTG1 calibration constant (to get good FRD) and LTG3 threshold (to get good threat area)

9. 999 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration LTG Threat Methodology: Disadvantages Methods are only as good as the numerical model output; models usually do not make storms in the right place at the right time; models sometimes do bad forecasts; saves at >5 min can miss LTG jumps; Small number of cases, lack of extreme LTG events means uncertainty in original calibrations; Calibrations should be redone whenever model is changed, or error bars acknowledged regarding sensitivities to grid mesh, model microphysics; Method does not distinguish 3-d LTG structure, but crude IC-CG partitioning may be possible

10. 10 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration WRF Configuration (LFA study) Typical Case 2-km horizontal grid mesh 51 vertical sigma levels Dynamics and physics: –Eulerian mass core –Dudhia SW radiation –RRTM LW radiation –YSU PBL scheme –Noah LSM –WSM 6-class microphysics scheme (graupel; no hail) 8h forecast initialized at 00 UTC with AWIP212 NCEP EDAS analysis; Also used METAR, ACARS, and WSR- 88D radial vel at 00 UTC; Eta 3-h forecasts used for LBCs

11. 11 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration WRF Configuration (NSSL) Typical Case 4-km horizontal grid mesh 35 vertical sigma levels Dynamics and physics: –Eulerian mass core –Dudhia SW radiation –RRTM LW radiation –MYJ PBL scheme –Noah LSM –WSM 6-class microphysics scheme (graupel; no hail) 36h forecast initialized at 00 UTC with AWIP212 NCEP EDAS analysis on 40 km grid; 0-36-h NAM forecasts used for LBCs

12. 12 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration WRF Configuration (NCAR HRRR) Typical Case 3-km horizontal grid mesh 40 vertical sigma levels Dynamics and physics: –Eulerian mass core –RRTMG LW, SW radiation –MYJ PBL scheme –Noah LSM –Thompson 2-moment microphysics scheme in rain, cloud ice 48h forecast initialized at 00 UTC with continuous cycling EAKF assimilation ICs derived from 15 km EAKF ensembles interpolated to 3km mesh Unique randomly perturbed LBCs used for each of 10 members

13. 13 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration LFA recalibration for HRRR: Gained access to NCAR HRRR-like ensembles only in Dec 2015; selected cases archived Lack of AL severe weather in 2016 has required us to expand case search nationwide; Nationwide search has required us to begin using NLDN, other data for validation; Lack of AL severe weather has slowed progress on assessment of thresholds needed in HRRR for optimum areal coverage, which cannot be studied with data other than LMA; HRRR recalibration studies are still in progress.

14. 14 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration LFA validation for HRRR: Compare peak HRRR LFA FRD with obs peak FRD; Compare peak HRRR LFA area with obs peak area; NCAR HRRR has no radar DA, resembles cold start, so examine only hours 6-30 as “day 1”; Define peak HRRR LFA data based on mean peak data from 10 ensemble members; Define observed peak FRD, area data using LMA data, or NLDN data, if necessary.

15. 15 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Time series of HRRR LFA, NLDN FRD: 29 April 2016 case Only 9 ensemble members shown; solid line = NLDN data; Result; peak LFA FRD resembles peak NLDN FRD (atypical)

16. 16 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Time series of HRRR LFA, NLDN FRD: 19 July 2016 case Only 9 ensemble members shown; solid line = NLDN data; Result; peak LFA FRD >> peak NLDN FRD (typical)

17. 17 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration LFA validation findings for HRRR: Peak NCAR HRRR LFA FRD usually >> observed peak FRD; problem traced to use of erroneous FRD calibration constant in NCAR HRRR runs; we will adjust it! Peak HRRR LFA area comparison with observed peak area still under investigation (not enough LMA cases); HRRR 10 ensemble members sometimes exhibit surprisingly large range of solutions.

18. 18 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration LTG Jump Methodology: Expand existing WRF post-processor routine to create maps of hourly extrema in field tendencies; Save data at 2 min intervals (5 time steps) and do one-sided time differencing; As storms approach, tendencies > 0; as they recede, tendencies < 0; apply revised software to create 1-h fields of max positive tendency, min negative tendency; Sum the fields of max pos. tendency, min neg. tendency; this tends to cancel advection; To remove start/end artifacts, extend tendency calcs 6 mins prior to and after each hour; map the results

19. 19 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration LTG Jump Methodology: Advantages Method can show size, shape, structure of LTG jumps and lulls; Mapped results allow easy study of relationships with topography or other storm or meteorological fields; Tendency calculations can be applied to other model fields, so that relationships to LTG jumps and lulls can be examined spatially; Method can also be applied to LMA FRD data, for ready comparison of structural features with obs

20. 20 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration LTG Jump Methodology: Disadvantages Methods are only as good as the numerical model output; models usually do not make storms in the right place at the right time; jumps, lulls are only general characterizations of what storms might do Only 1 prototype case (27 April 2011 Superoutbreak) studied so far, need to extend to many other cases Method has difficulty depicting events for stationary or rapidly training storms Artifacts at start, end of 1-h periods can occur, or at end of a simulation Method can yield biases in summed tendencies if storm perturbations are not circularly symmetric

21. 21 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration LTG Jump Methodology: Preliminary results We present four 1-h panels for each of three fields (LFA LTG1, WRF wmax, WRF sfc p') for 21UTC < t < 22UTC near HSV on 27 April 2011 For each field shown, we present 4 panels: 1. Hourly max of the field itself; 2. Hourly max of pos. tendency of the field; 3. Hourly min of neg. tendency of the field; 4. Sum of panels 2+3 to eliminate steady advection, reveal the anomalies (jumps and lulls) Plots show wmax dominates LTG jumps, lulls; p' plots reveal added linkages, show generality of methods Plots of jumps, lulls are sensitive to storm shape

22. 22 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Map of NSSL WRF LFA: 1-h max LTG1 Cell motion ~100 km/h; long stripes = persistent cells

23. 23 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Map of NSSL WRF LFA: 1-h max d(LTG1)/dt Cell motion ~100 km/h; black contours show cells as identified from 1-h max of LTG1 itself

24. 24 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Map of NSSL WRF LFA: 1-h min d(LTG1)/dt Cell motion ~100 km/h; black contours show cells as identified from 1-h max of LTG1 itself

25. 25 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Map of NSSL WRF LFA: 1-h sum d(LTG1)/dt Cell motion ~100 km/h; black contours show cells as identified from 1-h max of LTG1 itself

26. 26 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Map of NSSL WRF LFA: 1-h max wmax Cell motion ~100 km/h; black contours show cells as Identified from 1-h max of LTG1 itself

27. 27 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Map of NSSL WRF LFA: 1-h max d(wmax)/dt Cell motion ~100 km/h; black contours show cells as identified from 1-h max of LTG1 itself

28. 28 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Map of NSSL WRF LFA: 1-h min d(wmax)/dt Cell motion ~100 km/h; black contours show cells as identified from 1-h max of LTG1 itself

29. 29 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Map of NSSL WRF LFA: 1-h sum d(wmax)/dt Cell motion ~100 km/h; black contours show cells as identified from 1-h max of LTG1 itself

30. 30 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Map of NSSL WRF LFA: 1-h min p' Cell motion ~100 km/h; black contours show cells as Identified from 1-h max of LTG1 itself

31. 31 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Map of NSSL WRF LFA: 1-h max d(p')/dt Cell motion ~100 km/h; black contours show cells as identified from 1-h max of LTG1 itself

32. 32 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Map of NSSL WRF LFA: 1-h min d(p')/dt Cell motion ~100 km/h; black contours show cells as identified from 1-h max of LTG1 itself

33. 33 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Map of NSSL WRF LFA: 1-h sum d(p')/dt Cell motion ~100 km/h; black contours show cells as identified from 1-h max of LTG1 itself

34. 34 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Future Work: 1. Complete study of data from 2016 NCAR ensembles; data from diverse cases still being collected (2016=QUIET); 2. Refine methods of assessing time tendencies in WRF; 3. Apply LFA time tendency assessments to a wide range of cases, to evaluate accuracy and robustness: - validate LFA jumps, lulls against obs: amplitude, number; - see how WRF LFA jumps depend on storm type, shape; 4. Study how LFA jumps relate to storm dynamical changes; 5. Apply LFA to “dry” summer storms in w USA, Alaska.

35. 35 WoF, Feb 2012 Earth-Sun System Division National Aeronautics and Space Administration Acknowledgments: This research was first funded by the NASA Science Mission Directorate’s Earth Science Division in support of the Short-term Prediction and Research Transition (SPoRT) project at Marshall Space Flight Center, Huntsville, AL, and more recently by the NOAA GOES-R R3 Program. Thanks to NOAA, and also Gary Jedlovec, Rich Blakeslee, and Bill Koshak (NASA), for ongoing support of this research. Thanks also to Paul Krehbiel, NMT, Bill Koshak, NASA, Walt Petersen, NASA, for helpful discussions. Ms. In progress for recent updates. For initial published paper, see: McCaul, E. W., Jr., S. J. Goodman, K. LaCasse and D. Cecil, 2009: Forecasting lightning threat using cloud-resolving model simulations. Wea. Forecasting, 24, 709-729.