remote sensing and modeling of hurricane intensification steve guimond and jon reisner atmospheric...
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Remote Sensing and Modeling of Hurricane
IntensificationSteve Guimond and Jon ReisnerAtmospheric Dynamics EES-2
FSU
Why study hurricanes?
• Societal– Protection of life and property
• Energy (DOE LANL)– Northern Gulf of Mexico
• Largest portion of domestic oil & gas exploration, production, processing Economy
• DOD (Navy)
Why study hurricanes?
• Societal– Protection of life and property
• Energy (DOE LANL)– Northern Gulf of Mexico
• Largest portion of domestic oil & gas exploration, production, processing Economy
• DOD (Navy)
LSU
Solutions?
• Mitigating risks relies heavily on accurate, timely forecasts– Track– Intensity– Structure
• However, problems with forecasting…
Methods for solution
• Main reason for forecasting troubles:– Incomplete understanding and observation of
hurricane physics• Understanding
• State-of-the-art atmospheric model (Reisner et al. 2005)– Compressible Navier-Stokes– Explicit cloud microphysics– Superior numerics
– Observation• Unique airborne dual-doppler radar dataset
– Rapidly intensifying Hurricane Guillermo (1997)– High resolution:
» 2 km spatial» 30 minute temporal
• LANL dual-frequency lightning array
Basic Hurricane Dynamics
• Diabatic systems– Latent heat extracted from ocean and
released in deep convection
• Forces direct and indirect circulations– Energy mass momentum
Updraft
Background Vortex
Latent Heat
Microphysics
Eddy Heat and Momentum
Fluxes
Balanced respons
e
Adjustment
Symmetric
heating
Asymmetricheating
Adjustment
Balanced respons
e
Adjustment
Intensity and
Structure Change
Hurricane Intensifica
tion Roadmap
Nolan and Grasso (2003)
Airborne Doppler Radar
• 3-D reflectivity and latent heat animations
• Latent heat retrieved following Guimond (2008)
Simulations
• Environment and boundary conditions– ECMWF re-analysis
• Stretched Grid– 2km radar domain extending to 15 km
• Quiet environment
• Constant SST (29ºC)
• Forcing from radar derived latent heat
Angular Momentum Budgets
• Useful for explaining mechanics of storm spin-up
• Computed in cylindrical coordinate system– dr = 2 km– 85 azimuthal points
€
∂Ma
∂t= −
1
ρr
∂[rρ uMa ]
∂r−
1
ρ
∂[ρ wMa ]
∂z−
1
ρr
∂[rρ ′ u Ma′]
∂r−
1
ρ
∂[ρ ′ w Ma′]
∂z+ rFθ
€
Ma = rv +for
2
2
Angular Momentum Budgets: Run 1
€
∂Ma
∂t= −
1
ρr
∂[rρ uMa ]
∂r−
1
ρ
∂[ρ wMa ]
∂z−
1
ρr
∂[rρ ′ u Ma′]
∂r−
1
ρ
∂[ρ ′ w Ma′]
∂z+ rFθ
Angular Momentum Budgets: Run 1
€
∂Ma
∂t= −
1
ρr
∂[rρ uMa ]
∂r−
1
ρ
∂[ρ wMa ]
∂z−
1
ρr
∂[rρ ′ u Ma′]
∂r−
1
ρ
∂[ρ ′ w Ma′]
∂z+ rFθ
Summary/Conclusions
• Radar retrieved heating produces realistic comparison to actual storm even in “idealized” setting
• Latent heat initialization believed superior to vortex insertion methods
• Role of eddies large initially, then axisymmetrization process takes over– Hydrostatic and gradient wind adjustment
Future Work: Lightning
• Basic physics– Lightning proxy for intense convective activity,
requires…• Supercooled liquid water, ice and graupel collisions• Strong updraft and latent heating
• New LANL ground-based detection array– Operates in VLF & VHF radio bands– Precise 4D locations– Detects cloud-ground and intracloud strokes– 24/7 monitoring over large regions
• Placed in Louisiana area, offshore oil rigs
Updraft
Background Vortex
Latent Heat
Particle Growth
Lightning
Microphysics
Eddy Heat and Momentum
FluxesBalanced response
Adjustment
Symmetric heating
Asymmetricheating
Adjustment
Balanced response
Adjustment
Collisions
Intensity and
Structure Change
Hurricane Intensification
Roadmap
Nolan and Grasso (2003)