1 / 26

Hurricane Dynamics: Summer Research Highlights

Hurricane Dynamics: Summer Research Highlights. Steve Guimond Florida State University. Motivation. TC intensification is a complex, non-linear process governed by physics on a multitude of scales Synoptic scale Vortex scale Convective scale Hydrometeor scale

krista
Download Presentation

Hurricane Dynamics: Summer Research Highlights

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Hurricane Dynamics: Summer Research Highlights Steve Guimond Florida State University

  2. Motivation • TC intensification is a complex, non-linearprocess governed by physics on a multitude of scales • Synoptic scale • Vortex scale • Convective scale • Hydrometeor scale • Improving TC intensification (for wide range of applications including energy) hinges on better understanding of inner-core dynamics • In nature, the occurrence of hot towers can often be linked to TC intensification (i.e. Guimond et al. 2009) • Many are not convinced • “…there is no direct proof that it matters that convection is that strong” • “…[hot towers] have very little to do with rapid intensification in general”

  3. Hurricane Intensification Roadmap Background Vortex Updraft Collisions & Charging Lightning Latent Heat Microphysics Eddy Heat and Momentum Fluxes Asymmetric heating Balanced response Adjustment Nolan and Grasso (2003) Intensity and Structure Change Symmetric heating Balanced response Adjustment Adjustment

  4. My Contribution • Characterizing 4-D latent heating in RI Hurricane • Airborne dual-Doppler retrieval • 2 km x 2 km x 1 km x ~30 minutes • EDOP nadir pointing retrievals • Max resolution: 100 meters in horizontal, 38 meters in vertical • Understanding inner-core dynamics that is triggered by hot towers • Are small scale details of lightning/heating necessary to capture intensification or are bulk quantities sufficient? • Implications for observing systems  lightning • LANL network ~ 200 m resolution for VHF • Is it necessary for hurricane simulations to become turbulent ? [i.e. λ>>∆ ~ 100 Bryan et al. (2003)] • Explicitly resolving large eddies, entrainment

  5. 4-D Latent Heating

  6. Impact of Retrievals OBS MODEL (retrievals)

  7. Impact of Retrievals OBS MODEL (full microphysics)

  8. Impact of Retrievals OBS MODEL (warm rain only)

  9. Impact of Retrievals OBS MODEL (environment sfc fluxes)

  10. Inner-Core Dynamics

  11. Impact of Barotropic Instability with forcing

  12. Impact of Barotropic Instability with forcing

  13. Balanced Adjustment: 1 km vs 200 meters • Dynamics heavily motivated by observations • Basic-state vortex using Doppler data • Made stable to all wavenumber perturbations • Removed divergence noise • Unbalanced initially • Heating perturbations using EDOP data

  14. Peak Updrafts from EDOP Heymsfield et al. 2009

  15. EDOP Heating Pulse

  16. Balanced Adjustment: 1 km vs 200 meters Horizontal slice of vertical velocity at 10 km height on 1 km grid Horizontal slice of vertical velocity at 10 km height on 200 meter grid

  17. Balanced Adjustment: 1 km vs 200 meters

  18. Balanced Adjustment: 1 km Diagnostics

  19. Conclusions and Ongoing Work • Goal: Understand fundamental impacts of hot towers (HTs) on hurricane intensification (Convective and Vortex Scales) • New version of latent heating retrieval • 4-D distribution of heating in RI Hurricane (first time) • In Guillermo, barotropic instability/mixing appears essential for RI • Balanced adjustment of hot towers at 200 m vs. 1 km and energetic feedbacks onto vortex scale Lightning Project Relevance • Proxy for lightning = latent heat • Help prove the value of lightning data in understanding/predicting dynamics of hurricanes • Physics on fine space/time scales are important • Role of the asymmetric mode

  20. Acknowledgments • David Moulton (help with PDE solver) • Gerry Heymsfield (EDOP and dropsonde data) • Paul Reasor and Matt Eastin (Guillermo edits) References • Roux and Ju (1990) • Braun et al. (2006), Braun (2006) • Gamache et al. (1993) • Heymsfield et al. (1999) • Reasor et al. (2008) • Black (1990)

  21. Latent Heating Retrieval • Based on Roux and Ju (1990) • Solve water budget with Doppler radar • Compute latent heat with vertical velocity & lapse rate • Improvements to algorithm • Examine assumptions (uncover sensitivities) • Reduced uncertainties with ancillary data • Uncertainty estimates on final product

  22. Impact of Retrievals OBS MODEL (retrievals all saturated)

  23. Gravity Waves

  24. EYE EYE a b c d Motivation • What are hot towers? • How are they distributed?

  25. Hurricane Intensification Roadmap Background Vortex Updraft Latent Heat Microphysics Eddy Heat and Momentum Fluxes Asymmetric heating Balanced response Adjustment Nolan and Grasso (2003) Intensity and Structure Change Symmetric heating Balanced response Adjustment Adjustment

  26. Hurricane Intensification Roadmap Background Vortex Updraft Collisions & Charging Lightning Latent Heat Microphysics Eddy Heat and Momentum Fluxes Asymmetric heating Balanced response Adjustment Nolan and Grasso (2003) Intensity and Structure Change Symmetric heating Balanced response Adjustment Adjustment

More Related