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Steve Guimond

Tropical Cyclone Inner-Core Dynamics : Part 1. A Latent Heat Retrieval and its Effects on Intensity and Structure Change Part 2. The Impacts of Effective Diffusion on the Axisymmetrization Process. Steve Guimond.

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Steve Guimond

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  1. Tropical Cyclone Inner-Core Dynamics:Part 1. A Latent Heat Retrieval and its Effects on Intensity and Structure ChangePart 2. The Impacts of Effective Diffusion on the Axisymmetrization Process Steve Guimond

  2. Part 1: A Latent Heat Retrieval and its Effects on Intensity and Structure Change

  3. Motivation • Main driver of hurricane genesis and intensity change is latent heat release • Observationally derived 4-D distributions of latent heating in hurricanes are sparse • Most estimates are satellite based (i.e. TRMM) • Coarse space/time • No vertical velocity • Few Doppler radar based estimates • Water budget (Gamache 1993) • Considerable uncertainty in numerical model microphysical schemes • e.g. McFarquhar et al. (2006) and Rogers et al. (2007)

  4. Approach Refined latent heating algorithm (Roux 1985; Roux and Ju 1990) • Observing System Simulation Experiment (OSSE) • Examine assumptions/Uncover sensitivities • Parameterization • Present radar-derived retrievals • Uncertainty estimates • Impact study

  5. Algorithm Examination Non-hydrostatic, full-physics, quasi cloud resolving (2-km) MM5 simulation of Hurricane Bonnie (1998; Braun 2006)

  6. Structure of Latent Heat • Goal saturation using production of precipitation (Roux and Ju 1990) • Divergence, diffusion and offset are small and can be neglected

  7. Structure of Latent Heat

  8. Structure of Latent Heat

  9. Magnitude of Latent Heat • Requirements • Temperature and pressure (composite eyewall, high-altitude dropsonde) • Vertical velocity (radar)

  10. Putting it Together Positives… • Full radar swath coverage in various types of clouds (3-D and 4-D) • Only care about condition of saturation, not magnitude Uncertainties to consider… • Estimating tendency term (Steady-state ?) • Quality of vertical velocity • Thermo based on composite eyewall dropsonde • Drop size distribution and feedback to derived parameters

  11. Do we really need saturation? Aircraft (z = 1.5 – 5.5 km) Courtesy of Matt Eastin

  12. Examining Uncertainties

  13. Storage Parameterization

  14. Observations • NOAA WP-3D dual-Doppler radar observations of Hurricane Guillermo (1997; Reasor et al. 2009) • Variational analysis retrieves important variables (u,v,w) • 2 km x 2 km x 1 km x ~34 min (10 snapshots = ~5.5 h) • 2-D particle data (Robert Black) in Katrina (2005) • Statistical fit between reflectivity and liquid water content

  15. Hurricane Guillermo (1997) Figures from NHC report

  16. Uncertainty Estimates Physical uncertainty Sampling uncertainty • Bootstrap (Monte Carlo method) • 95 % CI on mean = ~14%

  17. Impact Study

  18. Observations and Model • NOAA WP-3D dual-Doppler radar observations of Hurricane Guillermo (1997; Reasor et al. 2009) • Variational analysis retrieves important variables (u,v,w) • 2 km x 2 km x 1 km x ~34 min (10 snapshots = ~5.5 h) • Nonlinear, compressible, Navier-Stokes solver; LANL’s HIGRAD model (Reisner et al. 2005) • Realistic setup • 2 km radar domain stretched to boundaries (1300 km2), 71 levels • Full Coriolis • Reynolds OI high-resolution SST • ECMWF background • State-of-the-art cloud physics (Reisner and Jeffery 2009)

  19. Vortex Initialization Airborne radar Environment (ECMWF)

  20. Vortex Initialization • Nudge momentum equations with first radar composite Thermal wind balance NHC ~ 958 hPa

  21. Perturbations: Retrieval Run • Force energy equation with retrievals (no heat from model) 5.1 h t = 44 t = 78 t = 10 t = 0 ∆t = 34 ∆t = 34

  22. Perturbations: Freemode Run • Initial water vapor forcing from heat retrieval conversion MICROPHYSICS MICROPHYSICS 5.1 h t = 44 t = 78 t = 10 t = 0 ∆t = 34 ∆t = 34

  23. Results: Integrated Error

  24. Results: RMS Error

  25. Results: Explained Variance

  26. Comparisons: t = 0 h

  27. Comparisons: t = 4.67 h

  28. Space & Time Averaged Structure Black = Obs; Green = Retrieval; Red = Freemode Tangential Wind Vorticity

  29. Water Vapor Transport Retrieval Freemode

  30. Conclusions: Part I • Improved latent heat of condensation algorithm • Computation of saturation (production of precipitation) performed well in numerical model setting • Need observational validation of computed saturation • Precipitation storage term shown to be important for retrievals • Developed parameterization based on advection • Uncertainty estimates for heating magnitudes • Insensitive to thermo, sensitive to vertical velocity • Physical and sampling uncertainty = ~ 15 – 25 % • Likely first 4D view of latent heating in RI TC

  31. Conclusions: Part I • Assuming saturation of entire TC inner-core inappropriate • Need to determine saturation state for |w| ≤ ~ 5 m/s • For |w| > ~ 5 m/s saturation better assumption • Latent heat retrieval simulation vs. freemode simulation • Retrievals: Reduce RMSE and explain 20 – 25 % more variance in wind • Larger errors in freemode run: • Transport of water vapor (advection & diffusion) • Microphysics scheme (limits on heat release)

  32. Part 2: The Impacts of EffectiveDiffusion on the Axisymmetrization Process

  33. Background/Motivation • Deeper understanding of dynamics responsible for TC intensification triggered by convection • Fundamental property = latent heat release • Nolan and Montgomery (2002; NM02), Nolan and Grasso (2003; NG03) and Nolan et al. (2007) • Azimuthal mean heating  dominates • Pure asymmetric heating  negligible impact • Vorticity anomalies extract energy before axisymmetrizing

  34. Question to Consider • Nolan studies use simple, linear heating prescriptions • Does observational heating structure matter?

  35. First Step • Reproduce nonlinear results of Nolan and Grasso (2003) • Able to reproduce the symmetric heating perturbation results to a LARGE degree. • Asymmetric heating case NOT SO EASY!

  36. Numerical Model • HIGRAD (Reisner et al. 2005; Reisner and Jeffery 2009) • Equation set… • Discretization • Temporal semi-implicit (higher order an option) • Space  finite volume on A-grid (non-staggered)

  37. Numerical Model Setup • Attempt to mirror settings in WRF simulations of NG03 • Dry • Same domain (600 km sq. box) and grid spacing (2 km) • Higher vertical resolution (71 levels) and model top (22 km) • Same Coriolis frequency (5.0 x 10-5 s-1) • Free slip of momentum and scalars on lower boundary • Relaxation to Jordan sounding on sides and top • Diffusion coefficients set to constant 40 m2/s • Time step = 20 s, 6 h runs

  38. Vortex on Cartesian Mesh • Stable vorticity profile from NM02 • Compute u and v by solving Poisson equations • Baroclinic structure following NM02 • CLEAN VORTEX TO START

  39. Vortex Initialization • How get balanced vortex at t = 0 ? • Solving for fields and starting model  oscillations • Used nudging approach 1K WN3 thermal wind balance

  40. Symmetric vs. Asymmetric symmetric asymmetric -8.8 x 10-2 hPa -2.7 x 10-2 hPa GR10: NG03:

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