Steve Guimond

•Main driver of hurricane genesis and Main driver of hurricane genesis and intensity change is latent heat releaseintensity change is latent heat release•Observationally derived 4-D distributions Observationally derived 4-D distributions of latent heating in hurricanes are sparseof latent heating in hurricanes are sparse

• Most estimates are satellite based (i.e. Most estimates are satellite based (i.e. TRMM)TRMM)• Coarse space/timeCoarse space/time• No vertical velocityNo vertical velocity

• Few Doppler radar based estimatesFew Doppler radar based estimates• Water budget (Gamache 1993)Water budget (Gamache 1993)

•Considerable uncertainty in numerical Considerable uncertainty in numerical model microphysical schemesmodel microphysical schemes

• e.g. McFarquhar et al. (2006) and Rogers et al. e.g. McFarquhar et al. (2006) and Rogers et al. (2007)(2007)

Refined latent heating algorithm Refined latent heating algorithm (Roux 1985; Roux and Ju 1990)(Roux 1985; Roux and Ju 1990)

1)1) Observing System Simulation Experiment Observing System Simulation Experiment (OSSE)(OSSE)

2)2) Examine assumptions/Uncover sensitivitiesExamine assumptions/Uncover sensitivities

3)3) ParameterizationParameterization

4)4) Present radar-derived retrievalsPresent radar-derived retrievals

5)5) Uncertainty estimatesUncertainty estimates

6)6) Impact studyImpact study

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

Goal saturation using production of precipitation (Roux and Ju 1990)

Divergence, diffusion and offset are small and can be neglected

FALL DIVERG. ADVEC. STOR.

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Requirements Temperature and pressure (composite eyewall, high-altitude

dropsonde) Vertical velocity (radar)

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gas constant

latent heat of condensation

T temperature

potential temperature

saturation mixing ratio

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Positives…1)Full radar swath coverage in various types of clouds (3-D and 4-

D)2)Only care about condition of saturation, not magnitude

Uncertainties to consider…1)Estimating tendency term (Steady-state ?)

2)Quality of vertical velocity3)Thermo based on composite eyewall dropsonde4)Drop size distribution and feedback to derived parameters

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Courtesy of Matt Eastin

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•NOAA WP-3D dual-Doppler radar NOAA WP-3D dual-Doppler radar observations of Hurricane Guillermo (1997; observations of Hurricane Guillermo (1997; Reasor et al. 2009)Reasor et al. 2009)

•Variational analysis retrieves important variables Variational analysis retrieves important variables (u,v,w) (u,v,w)

•2 km x 2 km x 1 km x ~34 min (10 snapshots = ~5.5 h)2 km x 2 km x 1 km x ~34 min (10 snapshots = ~5.5 h)

•2-D particle data (Robert Black) in 2-D particle data (Robert Black) in Katrina (2005)Katrina (2005)•Statistical fit between reflectivity and liquid water Statistical fit between reflectivity and liquid water contentcontent

Figures from NHC report

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p

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7 -1 -1 -1 -1sq2.5 K, 3.1 K, 3.4 10 m , 2 m s 8 K h or 27% of mean (30 K h )

z

DT w

Dt

Physical uncertaintyPhysical uncertainty

Sampling uncertaintySampling uncertainty

•Bootstrap (Monte Carlo Bootstrap (Monte Carlo method)method)•95 % CI on mean = ~14%95 % CI on mean = ~14%

•NOAA WP-3D dual-Doppler radar observations of NOAA WP-3D dual-Doppler radar observations of Hurricane Guillermo (1997; Reasor et al. 2009)Hurricane Guillermo (1997; Reasor et al. 2009)

•Variational analysis retrieves important variables (u,v,w) 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 km x 2 km x 1 km x ~34 min (10 snapshots = ~5.5 h)

•Nonlinear, compressible, Navier-Stokes solver; LANL’s Nonlinear, compressible, Navier-Stokes solver; LANL’s HIGRAD model (Reisner et al. 2005)HIGRAD model (Reisner et al. 2005)

•Realistic setupRealistic setup•2 km radar domain stretched to boundaries (1300 km2 km radar domain stretched to boundaries (1300 km22), 71 ), 71 levelslevels•Full CoriolisFull Coriolis•Reynolds OI high-resolution SSTReynolds OI high-resolution SST•ECMWF backgroundECMWF background

•State-of-the-art cloud physics (Reisner and Jeffery 2009)State-of-the-art cloud physics (Reisner and Jeffery 2009)

Airborne radar

Environment (ECMWF)

Nudge momentum equations with first radar Nudge momentum equations with first radar compositecomposite

Thermal wind balance

NHC ~ 958 hPa

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Force energy equation with retrievals (no heat Force energy equation with retrievals (no heat from model)from model)

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MICROPHYSICS MICROPHYSICS

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Black = Obs; Green = Retrieval; Red = Freemode

Tangential Wind Vorticity

Retrieval Freemode

•Improved latent heat of condensation Improved latent heat of condensation algorithmalgorithm

•Computation of saturation (production of Computation of saturation (production of precipitation) performed well in numerical model precipitation) performed well in numerical model settingsetting

•Need observational validation of computed Need observational validation of computed saturationsaturation

•Precipitation storage term shown to be Precipitation storage term shown to be important for retrievalsimportant for retrievals

•Developed parameterization based on advectionDeveloped parameterization based on advection

•Uncertainty estimates for heating magnitudesUncertainty estimates for heating magnitudes

•Insensitive to thermo, sensitive to vertical Insensitive to thermo, sensitive to vertical velocityvelocity

•Physical and sampling uncertainty = ~ 15 – 25 %Physical and sampling uncertainty = ~ 15 – 25 %

•Likely first 4D view of latent heating in RI Likely first 4D view of latent heating in RI TCTC

• Assuming saturation of entire TC inner-core Assuming saturation of entire TC inner-core inappropriateinappropriate

• Need to determine saturation state for |w| ≤ ~ 5 Need to determine saturation state for |w| ≤ ~ 5 m/s m/s

• For |w| > ~ 5 m/s saturation better For |w| > ~ 5 m/s saturation better assumptionassumption

• Latent heat retrieval simulation vs. freemode Latent heat retrieval simulation vs. freemode simulationsimulation

• Retrievals: Reduce RMSE and explain 20 – 25 Retrievals: Reduce RMSE and explain 20 – 25 % more variance in wind% more variance in wind

• Larger errors in freemode run: Larger errors in freemode run:

1)1) Transport of water vapor (advection & Transport of water vapor (advection & diffusion)diffusion)

2)2) Microphysics scheme (limits on heat Microphysics scheme (limits on heat release)release)

•Deeper understanding of dynamics responsible Deeper understanding of dynamics responsible for TC intensification triggered by convection for TC intensification triggered by convection

•Fundamental property = latent heat releaseFundamental property = latent heat release

•Nolan and Montgomery (2002; NM02), Nolan and Nolan and Montgomery (2002; NM02), Nolan and Grasso (2003; NG03) and Nolan et al. (2007)Grasso (2003; NG03) and Nolan et al. (2007)

•Azimuthal mean heating Azimuthal mean heating dominatesdominates

•Pure asymmetric heating Pure asymmetric heating negligible impactnegligible impact

•Vorticity anomalies extract energy before Vorticity anomalies extract energy before axisymmetrizingaxisymmetrizing

• Nolan studies use simple, linear heating Nolan studies use simple, linear heating prescriptionsprescriptions

• Does observational heating structure Does observational heating structure matter?matter?

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• Reproduce nonlinear results of Nolan Reproduce nonlinear results of Nolan and Grasso (2003)and Grasso (2003)

• Able to reproduce the symmetric heating Able to reproduce the symmetric heating perturbation results to a LARGE degree.perturbation results to a LARGE degree.

• Asymmetric heating caseAsymmetric heating case NOT SO EASY! NOT SO EASY!

•HIGRAD (Reisner et al. 2005; Reisner and HIGRAD (Reisner et al. 2005; Reisner and Jeffery 2009)Jeffery 2009)

•Equation set…Equation set…

•DiscretizationDiscretization

•Temporal Temporal semi-implicit (higher order an semi-implicit (higher order an option)option)

•Space Space finite volume on A-grid (non- finite volume on A-grid (non-staggered)staggered)

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•Attempt to mirror settings in WRF simulations of Attempt to mirror settings in WRF simulations of NG03NG03

•DryDry

•Same domain (600 km sq. box) and grid Same domain (600 km sq. box) and grid spacing (2 km)spacing (2 km)

•Higher vertical resolution (71 levels) and model Higher vertical resolution (71 levels) and model top (22 km)top (22 km)

•Same Coriolis frequency (5.0 x 10Same Coriolis frequency (5.0 x 10-5-5 s s-1-1))

•Free slip of momentum and scalars on lower Free slip of momentum and scalars on lower boundaryboundary

•Relaxation to Jordan sounding on sides and topRelaxation to Jordan sounding on sides and top

•Diffusion coefficients set to constant 40 mDiffusion coefficients set to constant 40 m22/s/s

•Time step = 20 s, 6 h runsTime step = 20 s, 6 h runs

(1) Stable vorticity profile from NM02

(2) Compute u and v by solving Poisson equations

(3) Baroclinic structure following NM02

CLEAN VORTEX TO START

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•How get balanced vortex at t = 0 ?How get balanced vortex at t = 0 ?

•Solving for fields and starting model Solving for fields and starting model oscillationsoscillations

•Used nudging approachUsed nudging approach i

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•Discrepancy with asymmetric NG03 likely due Discrepancy with asymmetric NG03 likely due to symmetric secondary circulation in basic-to symmetric secondary circulation in basic-state vortexstate vortex

•NG03 did not consider a secondary circulationNG03 did not consider a secondary circulation

•Secondary circulations are ubiquitous features of Secondary circulations are ubiquitous features of real TCsreal TCs

•Suggests impact of asymmetric mode important Suggests impact of asymmetric mode important for more realistic numerically simulated TCs for more realistic numerically simulated TCs

•Diffusion (sub-grid model) in HIGRAD Diffusion (sub-grid model) in HIGRAD responsible forresponsible for

1)1)Significant, secondary circulation in vortexSignificant, secondary circulation in vortex

2)2)Variability in vorticity anomalies produced from Variability in vorticity anomalies produced from heatingheating

•Inherent uncertainty with diffusion Inherent uncertainty with diffusion parameterization in models at cloud resolving parameterization in models at cloud resolving resolutions (e.g. 1 - 2 km)resolutions (e.g. 1 - 2 km)

•Need turbulence resolving resolution (~ 50 m) Need turbulence resolving resolution (~ 50 m) simulations to understand role of asymmetric simulations to understand role of asymmetric modemode

•Thanks to PhD Committee (Paul Reasor, Mark Thanks to PhD Committee (Paul Reasor, Mark Bourassa, Bob Hart, Michael Navon, Chris Jeffery, Bourassa, Bob Hart, Michael Navon, Chris Jeffery, Gerry Heymsfield, Ming Cai and X. Zou)Gerry Heymsfield, Ming Cai and X. Zou)

•Jon Reisner for mentoring and modeling expertiseJon Reisner for mentoring and modeling expertise

•Dave Nolan for discussion, re-running WRF and Dave Nolan for discussion, re-running WRF and figures.figures.

•Scott Braun, Robert Black, Dave Moulton and Matt Scott Braun, Robert Black, Dave Moulton and Matt Eastin for providing data, figures and assistance.Eastin for providing data, figures and assistance.

•Funded by The Los Alamos National Laboratory Funded by The Los Alamos National Laboratory through an LDRD project with Dr. Chris Jeffery the PIthrough an LDRD project with Dr. Chris Jeffery the PI

•Funding also from NASA ocean vector winds and Funding also from NASA ocean vector winds and NOAA grantsNOAA grants

Future WorkFuture Work

•Extend latent heating simulations out ~ 12 h and Extend latent heating simulations out ~ 12 h and use Guillermo Day 2 observations for validation.use Guillermo Day 2 observations for validation.

•How does radial inflow affect asymmetric heat How does radial inflow affect asymmetric heat perturbation?perturbation?

•Accelerated, more vigorous axisymmetrization?Accelerated, more vigorous axisymmetrization?

•Excite instability in inner-core?Excite instability in inner-core?

•Turbulence modeling to reduce uncertainty in Turbulence modeling to reduce uncertainty in diffusion parameterization, impact of asymmetric diffusion parameterization, impact of asymmetric heating.heating.

Radial flow and associated secondary circulation driven by dissipation Free slip along boundaries has been set correctly

Wind components are barotropic in lowest layer.

Thus, only a function of diffusive fluxes Why does diffusion/turbulence scheme play a

different role in HIGRAD than WRF? Eddy diffusivity was set to same values as NG03 WRF

runs Stress tensor similar to WRF (also tried Laplacian in

HIGRAD) Must come down to…design of numerical solution

procedure

HIGRAD WRF

(1)Fully implicit in time (1)Time-split

(2)A grid (2)C grid

(3)No artificial filters (3)Divergence damping, etc.

•Bootstrap (Monte Carlo method)Bootstrap (Monte Carlo method)•Auto-lag correlation Auto-lag correlation ~30 degrees of freedom ~30 degrees of freedom•95 % CI on mean = 101 - 133 K/h or ~14%95 % CI on mean = 101 - 133 K/h or ~14%•Physical uncertainty Physical uncertainty 8 K/h or ~27 % of mean (30 K/h) 8 K/h or ~27 % of mean (30 K/h)

AAM Budget for 1K WN3: t = AAM Budget for 1K WN3: t = 10 min10 min

θ’

AAM Budget for 1K WN3: t = AAM Budget for 1K WN3: t = 20 min20 min

AAM Budget for 1K WN3: t = AAM Budget for 1K WN3: t = 30 min30 min

AAM Budget for 1K WN3: t = AAM Budget for 1K WN3: t = 50 min50 min

AAM Budget for 1K WN3: t = AAM Budget for 1K WN3: t = 60 min60 min

Radial Flow: t = 30 minRadial Flow: t = 30 min

HIGRADHIGRAD WRFWRF

Radial Flow: t = 6 hRadial Flow: t = 6 h

HIGRADHIGRAD WRFWRF

With HIGRAD, I can reproduce these WRF results:

(1)Min pressure perturbation for:  Localized heat sources; Symmetric heat sources(2)Perturbation radial velocity for symmetric heat source(3)Vertical velocity for symmetric heat source(4)Perturbation tangential velocity for symmetric heat source(5)Perturbation vbar at surface for symmetric heat source