Jim Marquis , Yvette Richardson, Paul Markowski , David Dowell,

1. Analysis of the Goshen County, Wyoming, tornadicsupercell on 5 June 2009 during VORTEX2 using EnKF assimilation of mobile radar observations Jim Marquis, Yvette Richardson, Paul Markowski, David Dowell, Josh Wurman, Karen Kosiba, and Paul Robinson Photo by Sean Waugh

2. Goals of EnKF analysis • Increase availability of 3-D kinematic and • thermodynamic data (dual-Doppler and in situ obs • are spatially/temporally limited). Courtesy www.vortex2.org Paul Markowski

3. Goals of Data Assimilation • We want a set of realistically evolving analyses • (i.e., We are not using DA to initialize a forecast). • Analyze roles that mesocyclone-scale processes play in tornadogenesis, maintenance, and decay: • - trajectory analysis, • - vorticity, momentum budgets, • - complete thermodynamic fields, • - mid-upper level features,

4. Model Specifics • WRF-ARW 3.2.1: -Δx,y = 500 m, 80m < Δz < 2km, [120 x 80 x 20] km3 -LFO microphysics (χrain= 8x106, χgraup= 4x103 m-4 ; ρgraup= 900 kg/m3), -open lateral BCs, -no surface fluxes, no radiation, flat terrain. Homogeneous environment:

5. DA Specifics • DART (Anderson et al. 2009): • Ensemble adjustment filter, • 50 members, • Localization: • Gaspari-Cohn (1999) = 0 @ r = 6 km • Ensemble initiation: • 10 randomly placed warm bubbles at model t0 for each member • Ensemble spread maintained with: • Additive noise added to T, Td, U, V every 5 min where radar reflectivity is > 25 dBZ, (Dowell and Wicker 2009) • Perturbations smoothed to 4 km (horiz), 2 km (vert) scales

6. Experiment timeline “synthetic Data” Courtesy www.vortex2.org • Radar velocities assimilated every 2 minutes • OBAN: Cressman weighting • 500 m horizontal grid spacing (for 500m-model grid experiment) • data along conical slices σ2obs= (2 m/s)2

7. Dual-Doppler – EnKF (posterior) kinematics comparison W m/s EnKF Y (km) Dual-Doppler ζ radars X (km) Z = 400 m AGL

8. Comparison of temperature observations and EnKF analyses near the ground: ’ θv(K) Y (km) ζ X (km) Z = 50 m AGL Mobile mesonet Observations (not assimilated) Surface gust fronts • Greatest differences early in the assimilation period. They get smaller with time.

9. Pressure fields • Want pressure for: Important to supercells WRF diagnostic pressure:

10. Pressure diagnosed using individual members vs. retrieval using ensemble mean posteriors kinematic fields (e.g., Gal-Chen 1978, Hane and Ray 1985): Y (km) Retrieved from horiz. momentum eqns Sfc gust front z = 250 m X (km)

11. Trajectories (storm-rel.) calculated from ens. mean analyses Ring (radius = 1 km) of 20 parcels centered on peak ζ at z = 700 m at 2211 UTC, integrated backward in time to 2143 UTC 2211 UTC ’ θρ(K) (Note: Trajectories curtailed because they encounter edges of dual-Doppler coverage) Y (km) z = 200 m Sfc gust front X (km)

12. Boussinesq, inviscid, coriolis-free 3-D Vorticity Equation: = = = Ultimately important for generation of low-level mesocyclone = Baroclinic generation Tilting Stretching

13. More verification: Does ensemble mean vorticity along parcel trajectories match predicted (i.e., integrated) tendency? = = =

14. Lagrangian 3-D vorticity budget for a parcel entering mesocyclone: Ens. mean interpolated to trajectory Y (km) X (km) z = 200 m

15. Lagrangian 3-D vorticity budget for a parcel in the forward flank: Ens. mean interpolated to trajectory Y (km) X (km) ρ

16. Summary: Utility of EnKF analysis • EnKF Kinematic Analyses: • - Compare well with dual-Doppler fields. • - Most trajectories seem believable; • though, Lagrangianvorticity budgets have some problems in some areas of the storm. • EnKF Thermo Analyses: • Mixed success with comparisons to in situ obs. • Pressure fields seem unusable.

17. Acknowledgements • The EnKF experiments were performed using NCAR CISL supercomputing facilities (bluefire) with the Data Assimilation Research Testbed (DART) and WRF-ARW software. • Thanks to: Glen Romine, Lou Wicker, Chris Snyder, Nancy Collins, Jeff Anderson, Don Burgess, Dan Dawson, Robin Tanamachi, Bruce Lee, Cathy Finley, AltugAksoy, FuqingZhang, and Matt parker for consulting. • Thanks to all VORTEX2 crew for their dedication while collecting data on 5 June 2009. • This research is funded by NSF grants: NSF-AGS-0801035, NSF-AGS-0801041. The DOW radars are NSF Lower Atmospheric Observing Facilities supported by NSF-AGS-0734001.

18. Extras

19. Pressure diagnosed with posterior ensemble mean thermodynamic variables vs. Pressure retrieved from posterior ensemble mean kinematic fields (e.g., Hane and Ray 1985, Majcen et al. 2008): Diagnosed p’ Surface gust front Y (km) Retrieved p’ X (km) z = 250 m ζ • Posterior diagnosed pressure doesn’t seem right. • Retrieved pressure fields seemingly more realistic, but vertical • gradients still not trustworthy.

20. Pressure fields diagnosed with posterior means, prior means, and individual members : W>0 z = 250 m

21. Storm structure with/without radar assimilation: Top row: Series of Posterior ens. mean analyses. Z = 150 m Y (km) ζ X (km) Bottom row: Single member forecasted forward from 2157 (no DA). Model errors/idealized conditions require DA for a good storm.

22. Difference between surface obs and near-surface EnKF analyses of thermodynamic fields: θe

23. Some obs-space statistics RMS Innovation Total Spread Consistency Ratio Time UTC

24. Comparison of Dual-Doppler – EnKF (ensemble mean) horizontal vorticity EnKF EnKF Dual-Dop Dual-Doppler Horizontal vorticity vector pattern is similar, though magnitude of EnKFvorticity is greater

25. θ(K) ’ Y (km) ζ X (km)

26. Surface & mid-upper-level features (pre-tornado/ tornadogenesis) (tornado mature) W > 5 m/s (z = 5km) ζ Surface gust front (z = 300m) (tornado weakening) (tornado dissipated) Low-level meso cyclone/tornado stays beneath mid-level updraft

27. Dual-Doppler – EnKF (ensemble mean) kinematics comparison (DOW6 & NOXP) W m/s W (m/s) Y (km) ζ ζ X (km) Z = 400 m AGL

28. θ’(K) ζ MM obs: Low-level wmax trace: