1. Lightning data assimilation in the Rapid Refresh and evaluation of lightning diagnostics from HRRR runs Steve Weygandt, Ming Hu, Curtis Alexander, Stan Benjamin, Eugene McCaul 1 NOAA ESRL, Global Systems Division, Assimilation and Modeling Branch 1 USRA, Huntsville, AL NO LTG assim WITH LTG assim +1h RAP forecast 02z 26 Jan 2012

2. — Advanced community codes (ARW and GSI) — Retain key features from RUC analysis / model system (hourly cycle, radar DFI assimilation, cloud analysis) — RAP guidance for aviation, severe weather, energy applications Rapid Refresh and HRRR NOAA hourly updated models Rapid Refresh-13 RUC-13 RUC  Rapid Refresh (01 May 2012) Rapid Refresh v2 — Many improvements, target NCEP implement early 2014 HRRR – Runs as nest within RAP v2 NCEP GSD HRRR-3

3. RAP: Data assimilation engine for HRRR 3 RAP Data Assimilation cycle Observations Hourly cycling model HRRR

4. Rapid Refresh Hourly Update Cycle 1-hr fcst 1-hr fcst 1-hr fcst 11 12 13 Time (UTC) Analysis Fields 3DVAR Obs 3DVAR Obs Back- ground Fields Partial cycle atmospheric fields – introduce GFS information 2x/day Fully cycle all land-sfc fields Hourly ObservationsRAP 2012 N. Amer Rawinsonde (T,V,RH)120 Profiler – NOAA Network (V)21 Profiler – 915 MHz (V, Tv)25 Radar – VAD (V)125 Radar reflectivity - CONUS2km Lightning (proxy reflectivity)NLDN, GLD360 Aircraft (V,T)2-15K Aircraft - WVSS (RH)0-800 Surface/METAR (T,Td,V,ps,cloud, vis, wx) 2200- 2500 Buoys/ships (V, ps)200-400 Mesonet (T, Td, V, ps)flagged GOES AMVs (V)2000- 4000 AMSU/HIRS/MHS radiancesUsed GOES cloud-top pressure/temp13km GPS – Precipitable water WindSat scatterometer2-10K

5. Radar reflectivity assimilation Digital filter-based reflectivity assimilation initializes ongoing precipitation regions Forward integration,full physics with radar-based latent heating -20 min -10 min Initial +10 min + 20 min RUC / RAP HRRR model forecast Backwards integration, no physics Initial fields with improved balance, storm-scale circulation + RUC/RAP Convection suppression

6. Rapid Refresh (GSI + ARW) reflectivity assimilation example Low-level Convergence Upper-level Divergence K=4 U-comp. diff (radar - norad) K=17 U-comp. diff (radar - norad) NSSL radar reflectivity (dBZ) 14z 22 Oct 2008 Z = 3 km

7. Objectives for different model resolutions Parameterized convection (13-km RAP) - storm detection in radar coverage voids Explicit convection resolving (~3-km) Very high-resolution (1-km and less) - Specification of sub-storm-scale features - Fusion of dual-pol radar data and total lightning mapper data to specify detailed microphysics Methods Use as proxy reflectivity, specify latent heat Variational / ensemble methods Assimilation of lightning data

8. 1.Map lightning density to proxy reflectivity -- sum ground flashes per grid-box over 40 min period (-30  +10 min) REFL max = min [ 40, 15 + (2.5)(LTG)] Sin distribution in vertical RAP assimilation of lightning data LTG and REFL max REFL max and vertical REFL profile OLD specified relationship: NEW seasonally averaged empirical relationships:

9. Summer Winter OLD specification in RUC NEW Seasonally dependent empirical Lightning Flash Rate  max reflectivity

10. SUMMER Reflectivity profile as a function of column maximum reflectivity Max dbz 35-40 Max dbz 40-45 Max dbz 45-50 Max dbz 30-35

11. WINTER Reflectivity profile as a function of column maximum reflectivity Max dbz 30-35 Max dbz 35-40 Max dbz 40-45 Max dbz 45-50

12. 44 dBz 36 dBz 40 dBz 30 dBz Max dbz 30 - 35 Max dbz 35 - 40 Max dbz 40 - 55 Max dbz 45 - 50 AVERAGE Reflectivity profile as a function of column maximum reflectivity Summer Winter Summer Winter Summer Winter Summer Winter

13. Applications lightning DA technique Can apply technique to lightning data and satellite-based indicators of convective initiation  GLD-360 lightning data -- good long-range coverage Especially helpful for oceanic convection  SATCAST cloud top cooling rate data -- good Convective Initiation (CI) indicator Avoiding model delay in storm development SATCAST  work by Tracy Smith using data provided by John Mecikalski proxy flash rate = - 2 x cloud-top cooling rate (K/15 min)

14. Radar coverage Observed reflectivity Sat obs 24 Apr 2012 16z Latent heating- based temper- ature tendency No radar echo No radar coverage Lightning flash rate 16z Rapid Refresh oceanic lightning assimilation example

15. Observed reflectivity Sat obs 24 Apr 2012 16z No radar echo No radar coverage Rapid Refresh oceanic lightning assimilation example with LTG NO LTG LTG DA  slight impact on RAP forecast storm clusters 16z +1h GSD RAP forecasts 17z 16z

16. 21z 9 Jan Prim 19z + 2h fcst Dev 19z + 2h fcst ~ 11z LTG 1915z LTG NO LTG assim WITH LTG assim Radar

17. Assimilation of “satcast” cloud-top cooling rate CI-indicator data 17z SATCAST cooling rate (K / 15 min) 18z IR image 18z 5 July 2012 Cloud-top cooling rate helpful for initializing developing convection in GSD RAP retro tests 5 July 2012

18. WITH satcast assim NO satcast assim 18z+1h 19z Obs Reflect Assimilation of “Satcast” cooling rates provides more realistic short-range forecast of convective initiation and development

19. 18z+2h 20z Assimilation of “Satcast” cooling rates provides more realistic short-range forecast of convective initiation and development Obs Reflect WITH satcast assim NO satcast assim

20. Experimental HRRR lightning forecast guidance McCaul algorithm LTG1 Graupel flux a -15 C (cores) LTG2 Vertical integrated ice (anvils) LTG3 0.95 LTG1* + 0.05 LTG2* 2011 version: scale core by anvil 2012 version: scale anvil by core

21. Components of combined lightning threat (LTG3) (2011 version) 01z LTG2 LTG1 LTG3 Flases / km^2 / 5min

22. HRRR Combined lightning threat (LTG3) vs. radar and NALMA 23z HRRR LTG3 Obs radar NALMA lightning 19z + 4h (North Alabama Lightning Map- ping Array)

23. HRRR Combined lightning threat (LTG3) vs. radar and NALMA 00z Obs radar NALMA lightning HRRR LTG3 19z + 5h (North Alabama Lightning Map- ping Array)

24. HRRR Combined lightning threat (LTG3) vs. radar and NALMA 01z Obs radar NALMA lightning HRRR LTG3 19z + 6h (North Alabama Lightning Map- ping Array)

25. 1800z LTG2 LTG3 Lightning threat components (2012) Refl. 18z+3h Forecast 10 Jan 2013 LTG1 Flases / km^2 / 5min

26. 1800z LTG2 LTG3 Lightning threat components (2012) Refl. 18z+6h Forecast 10 Jan 2013 LTG1 Flases / km^2 / 5min

27. 1800z LTG2 LTG3 Lightning threat components (2012) Refl. 18z+9h Forecast 10 Jan 2013 LTG1 Flases / km^2 / 5min

28. 1800z Refl. 18z+12h Forecast 10 Jan 2013 LTG2 LTG1 LTG3 Lightning threat components (2012) Flases / km^2 / 5min

29. Summary Preliminary evaluation of impact from assimilation of two novel convection indicators:  GLD-360 lightning data -- good long-range coverage Helpful for oceanic convection  Satcast cloud top cooling rate data -- good CI Avoid model delay in storm development Preliminary look at lightning parameters from HRRR 3-km forecasts Qualitative assessment ongoing Plan HRRR runs from RAP w/ and w/o LTG, satcast