Hurricane Superintensity John Persing and Michael Montgomery JAS, 1 October 2003 Kristen Corbosiero AT796 18 April 2007.

Slides:



Advertisements
Similar presentations
Putting to rest WISHE-ful misconceptions Roger K. Smith....LMU Munich In collaboration with: Michael Montgomery..NPS Monterey John Persing....NPS Monterey.
Advertisements

Hurricane Dynamics 101 Roger K. Smith University of Munich.
5.6.1 Hurricane : introduction
Where Do the Hurricanes Come From?. Radiation Vapor/Cloud/precipitation Shallow convection Boundary layer turbulence Mesoscale convective system Thunderstorm.
First Law of Thermodynamics The internal energy dU changes when: 1.heat dQ is exchanged between a parcel and its environment 2.work is done by a parcel.
Hurricanes and climate ATOC 4720 class22. Hurricanes Hurricanes intense rotational storm that develop in regions of very warm SST (typhoons in western.
Vertical Structure of the Atmospheric Boundary Layer in Trade Winds Yumin Moon MPO 551 September 26, 2005.
Sensitivity of High-Resolution Simulations of Hurricane Bob (1991) to Planetary Boundary Layer Parameterizations SCOTT A. BRAUN AND WEI-KUO TAO PRESENTATION.
Weismann (1992) Weisman, M. L., 1992: The role of convectively generated rear- inflow jets in the evolution of long-lived mesoconvective systems. J. Atmos.
A Simplified Dynamical System for Understanding the Intensity-Dependence of Intensification Rate of a Tropical Cyclone Yuqing Wang International Pacific.
Tropical storms and the First Law of Thermodynamics ATMO 435.
USE OF HS3 DATA TO UNDERSTAND THE TROPICAL CYCLONE OUTFLOW LAYER John Molinari, Kristen Corbosiero, Stephanie Stevenson, and Patrick Duran University at.
HWRF Model Sensitivity to Non-hydrostatic Effects Hurricane Diagnostics and Verification Workshop May 4, 2009 Katherine S. Maclay Colorado State University.
Some Preliminary Modeling Results on the Upper-Level Outflow of Hurricane Sandy (2012) JungHoon Shin and Da-Lin Zhang Department of Atmospheric & Oceanic.
Tropical cyclone intensification Roger Smith Ludwig-Maximilians University of Munich Collaborators: Michael Montgomery, Naval Postgraduate School, Monterey,
+ Effects of Climate Change on Ocean Storms Chloe Mawer.
1 26 April 2013 Future WorkResultsMethodologyMotivation Chip HelmsComposite Analyses of Tropical Convective Systems Composite Analyses of Tropical Convective.
10-15% of eye trajectories escape into the eyewall with more frequent escapes during passes with stronger mesovortices along the eyewall edge Escape trajectories.
Chris Birchfield Atmospheric Sciences, Spanish minor.
19 December ConclusionsResultsMethodologyBackground Chip HelmsSensitivity of CM1 to Initial θ' Magnitude and Radius Examining the Sensitivity of.
Applications of ATMS/CrIS to Tropical Cyclone Analysis and Forecasting Mark DeMaria and John A. Knaff NOAA/NESDIS/STAR Fort Collins, CO Andrea Schumacher,
1 22 July 2013 Future WorkResultsMethodologyMotivation Chip HelmsComposite Analyses of Tropical Convective Systems Composite Analyses of Tropical Convective.
PRECIPITATION PROCESSES AT FRONTS. POSSIBLE CONDITIONS PRESENT AT FRONT 1.Air ahead of the front is stable to all forms of instability Forcing mechanism.
Cumulus Clouds. What goes on inside a cumulus cloud?
Prediction of Atlantic Tropical Cyclones with the Advanced Hurricane WRF (AHW) Model Jimy Dudhia Wei Wang James Done Chris Davis MMM Division, NCAR Jimy.
Tropical cyclone intensification Roger Smith Ludwig-Maximilians University of Munich Collaborators: Michael Montgomery, Naval Postgraduate School, Monterey,
Sensitivity of Tropical Cyclone Inner-Core Size and Intensity to the Radial Distribution of Surface Entropy Flux Wang, Y., and Xu, 2010: Sensitivity of.
Hurricane structure and intensity change : Effects of wind shear and Air-Sea Interaction M é licie Desflots Rosenstiel School of Marine & Atmospheric Science.
Benjamin A. Schenkel University at Albany, State University of New York, and Robert E. Hart, The Florida State University 6th Northeast.
Sensitivity of Simulated Tropical Cyclone Structure and Intensity to Horizontal Resolution Speaker: Wang, Jian-Cyuan Advisor: Prof. Yang, Ming-Jen Megan.
Energy Production, Frictional Dissipation, and Maximum Intensity of a Numerically Simulated Tropical Cyclone 4/ 蘇炯瑞 Wang, Y., and J. Xu, 2010: Energy.
Richard Rotunno NCAR *Based on:
Jonathan L. Vigh and Wayne H. Schubert January 16, 2008.
Air-Sea Exchange in Hurricanes by Peter G. Black & Hurricane Intensity and Eyewall Replacement by Robert A. Houze Jr. Lynsie M. Schwerer Atmospheric Science.
(C, B, A, C, D, D, B, A) x x x x x.
How Small-Scale Turbulence Sets the Amplitude and Structure of Tropical Cyclones Kerry Emanuel PAOC.
Tropical Cyclone Structure
Three Lectures on Tropical Cyclones Kerry Emanuel Massachusetts Institute of Technology Spring School on Fluid Mechanics of Environmental Hazards.
The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology The Tropical Cyclone Boundary Layer 4:
How Do Outer Spiral Rainband Affect Tropical Cyclone Structure and Intensity? The working hypothesis is based on the fact that the outer rainbands are.
Possible Aerosol Effects on Lightning Activity and Structure of Hurricanes Khain, A., N. Cohen, B. Lynn, and A. Pokrovsky, 2008: Possible aerosol effects.
Tropical Cyclones: Steady State Physics. Energy Production.
Shuyi S. Chen Joseph Tenerelli Rosenstiel School of Marine and Atmospheric Science University of Miami Effects of Environmental Flow and Initial Vortex.
Overview of Tropical Cyclones AOS 453 April 2004 J. P. Kossin CIMSS/UW-Madison.
Research on the HWRF Model: Intensification and Uncertainties in Model Physics Research on the HWRF Model: Intensification and Uncertainties in Model Physics.
Hurricane Physics Kerry Emanuel Massachusetts Institute of Technology.
Sensitivity of Tropical Cyclone Intensity to Ventilation in an Axisymmetric Model Brian Tang, and Kerry Emanuel J. Atmos. Sci., 69, 2394–2413.
Idealized Tropical Cyclone Structure. Tropical Cyclone Extension of the Warm Core middle –level vortex to the surface. Inducement of Ekman pumping Non-linear.
Benjamin A. Schenkel University at Albany, State University of New York, and Robert E. Hart, The Florida State University 38 th.
Analysis of Typhoon Tropical Cyclogenesis in an Atmospheric General Circulation Model Suzana J. Camargo and Adam H. Sobel.
Cumulus Clouds. Instabilities Resulting in Vertical Overturning 1.Thermal Instability (Assuming uniform vertical pressure gradient) a) Static (Parcel.
Andrea Schumacher, CIRA/CSU, Fort Collins, CO Mark DeMaria and John Knaff, NOAA/NESDIS/StAR, Fort Collins, CO NCAR/NOAA/CSU Tropical Cyclone Workshop 16.
Ventilation of Tropical Cyclones Brian Tang ATM 741 3/21/16.
Rapid Intensification of Tropical Cyclones by Organized Deep Convection Chanh Q. Kieu, and Da-Lin Zhang Department of Atmospheric and Oceanic Science University.
INNER CORE STRUCTURE AND INTENSITY CHANGE IN HURRICANE ISABEL (2003) Shuyi S. Chen and Peter J. Kozich RSMAS/University of Miami J. Gamache, P. Dodge,
Shuyi S. Chen, Robert A. Houze Bradley Smull, David Nolan, Wen-Chau Lee Frank Marks, and Robert Rogers Observational and Modeling Study of Hurricane Rainbands.
The Centre for Australian Weather and Climate Research A partnership between CSIRO and the Bureau of Meteorology The Tropical Cyclone Boundary Layer 2:
A Lagrangian Trajectory View on Transport and Mixing Processes between the Eye, Eyewall, and Environment Using a High-Resolution Simulation of Hurricane.
Evolution of Hurricane Isabel’s (2003) Vortex Structure and Intensity
TC Structure Theta_e Structure Grid 3: Vertical motion surfaces 15:30 UTC 26 August, m/s – red -1 m/s -blue +0.5 m/s – red -0.5 m/s -blue.
Robert Fovell Meteorology – Lecture 21 Robert Fovell
Yumin Moon & David S. Nolan (2014)
Water Budget of Typhoon Nari(2001)
The Genesis of Hurricane Guillermo: TEXMEX Analyses and a Modeling Study BISTER AND EMANUEL.
Tropical Cyclone Intensity Change
Tropical Cyclone Structure
Impacts of Air-Sea Interaction on Tropical Cyclone Track and Intensity
Scott A. Braun, 2002: Mon. Wea. Rev.,130,
GEORGE H. BRYAN and RICHARD ROTUNNO 2009, J. Atmos. Sci., 66,
Presentation transcript:

Hurricane Superintensity John Persing and Michael Montgomery JAS, 1 October 2003 Kristen Corbosiero AT April 2007

Outline 1. Superintense relative to what? MPI theories (Energetic & Thermodynamic) 2. Motivation for the current study 3. Superintensity in the Rotunno-Emanuel model 4. The eye as a latent heat reservoir 5. Three-dimensional modeling and observational evidence for superintensity 6. Summary and conclusions

NHC Official Forecast track and intensity errors for the Atlantic Ocean Maximum Potential Intensity (MPI) theories were formulated to try to get a handle on what processes determine the upper bound on intensity

MPI Theory Modern MPI theory led by Kerry Emanuel (1986, 1988, 1995, 1998) and Greg Holland (1997) Both theories assume moist adiabatic ascent in the eyewall and are governed by SST, surface RH, and the thermal structure of the upper troposphere Figure 1, Camp and Montgomery (2001)

Holland MPI, T-MPI (T for thermodynamic), relies heavily on prescribed environmental and eye soundings, and convective instability (CAPE) that develops in the eyewall Emanuel MPI, E-MPI (E for energetic), relies on air-sea heat and momentum exchange (WISHE)

E-MPI is based on a balance between frictional dissipation and energy production in the inflowing boundary layer air, or a point balance between moist entropy and angular momentum Ψ o ∂χ/∂r 2 = –C k /C d (1 + c|V|)|V|(χ sea – χ) Entropy balance Ψ o ∂R 2 /∂r 2 = 2(1+c|V|)|V|rV Momentum balance Ψ o = radial streamfunction (inflow) χ ≡ (SST – T out )(s inflow – s env ) s env = c p lnΘ e C k, C d = air-sea exchange coefficients for entropy and angular momentum c = empirical constant V = tangential wind speed R = angular momentum Entropy lost due to radial advection = Entropy gain from ocean Momentum gain from inflow = Momentum lost to ocean due to friction These two balance equations can be combined (with some fancy algebra) to get an equation for the maximum tangential wind of an axisymmetric, steady state vortex (Equations 2-5)

Current E-MPI maps from K-R I

Most tropical cyclones do not reach their 2-D, symmetric, steady state derived E-MPI Among the factors neglected are vertical wind shear, convective asymmetries, secondary eyewalls, sea spray and wind-induced ocean cooling

Motivation Hausman (2001) documented a systematic increase in intensity with increasing resolution using an axisymmetric hurricane model (Ooyama 2001) The simulations converged at ~1 km resolution to an intensity of nearly 140 m s -1 which far exceeded the E-MPI Based on this and other high resolution simulations that exhibited superintensity, Persing and Montgomery (2001) used the axisymmetric model of Rotunno and Emanuel (1987) to investigate the assumptions of E-MPI and document those assumptions that are violated in the simulations and that can explain superintensity

20-21 day average fields of the 4x resolution (3.75 km) run with the Rotunno Emanuel (1987) model This 2-D, non-hydrostatic model produces realistic hurricane structure

Time series of maximum V t from the model (solid), E-MPI, (dotted) and simplified MPI from Equation 6 (dashed) The 2x, 4x and 8x runs all exceed their MPI around day 5 and reach an approximate steady state at day 10 The default run reaches steady state at its MPI around day 9, but then exceeds the MPI and reaches a new steady state by day 20

V max from E-MPI as a function of SST and T outflow The boxes denote the range of E- MPI values in the simulations, while the stars are the actual superintense results

RunDefault2x4x8x Max V t Max Daily V t Median V t Mean RMW Min SLP Median SLP Max W Max Daily W V t = tangential wind (m s -1 ) RMW = radius of maximum wind (km) SLP = sea level pressure (hPa) W = updraft velocity (m s -1 ) Default = 15 km horizontal resolution

RunDefault2x4x8x Max V t Max Daily V t Median V t Mean RMW Min SLP Median SLP Max W Max Daily W Convergence in intensity is reached by the 4x simulation, but not in updraft strength Intensity changes can not be explained solely in terms of the shrinking of the RMW

Default run (15 km) temperature and potential temperature ( Θ ) anomalies This run had two steady states, one at its MPI (day 12, top) and one well above it (day 28, bottom) There is a substantial difference in eye structure between the two states

Equivalent potential temperature ( Θ e ) for the default run The Θ e maximum that develops by day 18 at 3 km inside the 20 km radius is a possible source of heat to eyewall convection if mixed outward (a violation of MPI theory!)

The reservoir of high Θ e develops in two steps: 1)Elimination of the initial mid-level Θ e minimum by convectively forced subsidence 2)Strong upward moisture flux under the eye

The 4x run (3.75 km) resolves the storm evolution in much greater detail including: 1) The concentration of strong subsidence just inside the eyewall 2) The large and deep 360+ K Θ e reservoir in the eye 3) The eyewall updrafts are not moist neutral (violation!) Figure 17 of Rotunno and Emanuel (1987)

The ultimate source of high Θ e in the 4x run (3.75 km) run is upward moisture flux from the ocean at significantly reduced surface pressures The heat flux is actually slightly negative in the eye due to subsidence warming Moisture flux Heat flux

4x run (3.75 km) half day trajectories in radius-height space There are 3 source regions for air entering the eyewall updraft: 1) From the eye (dotted) 2) From boundary layer (PBL) inflow (solid) 3) From low level inflow above the PBL (dashed)

4x run (3.75 km) half day trajectories in Θ e -height space Downdraft air is indistinguishable from PBL inflow air by the time it reaches the eyewall Parcels with lower trajectories have the highest Θ e Parcels increase their Θ e as they rise in the eyewall above the PBL, requiring an additional source of heat other than the ocean…the eye!

The waviness of the trajectories in the eye and on the inner edge of the eyewall indicate parcels are detraining into the eye and being reintroduced to the eyewall frequently. Thus, 2 key assumptions of MPI theory have been violated: 1) Entropy exchange between the eye and eyewall is trivial 2) The eyewall updraft is moist neutral

1.3 km resolution MM5 simulation Hurricane Bob (1991) from Braun (2002) also shows the eye as a source of air for eyewall updrafts

4x run Θ e before and after addition of a heat sink in lower eye to mimic the elimination of the eye heat reservoir The storm weakened from 90 to 55 m s -1, but was still above its E-MPI

Secondary circulation from the model and calculated from Eliassen’s (1951) balanced vortex model using the model derived heat and momentum forcings The model is evolving largely in hydrostatic and gradient wind balance How does high Θ e air from the eye produce a stronger storm?

E-MPI theory assumes that all of the heat added to the eyewall is in the PBL from the ocean in a near perfect Carnot engine Isothermal expansion Adiabatic expansion Adiabatic compression Isothermal compression

How does high Θ e air from the eye produce a stronger storm? E-MPI theory assumes that all of the heat added to the eyewall is in the PBL from the ocean in a near perfect Carnot engine Warming phase Cooling phase

Isothermal expansion Adiabatic compression How does high Θ e air from the eye produce a stronger storm? Add eyewall to the warming phase and consider the warming of a parcel relative to the moist adiabat at the top and bottom of the eyewall Warming phase Cooling phase

How does high Θ e air from the eye produce a stronger storm? Persing and Montgomery suggests the following ad hoc modification of SST in E-MPI theory: SST ’ = SST + Δ Θ e = SST + ( Θ e,out – Θ e,sfc ) Δ Θ e ≈ 8 K in the 4x simulation, increasing the SST from 26° to 34° C, increasing the MPI to ~80 m s -1 This value is still slightly below the actual model intensity of 90 m s -1, but much greater than the E-MPI of 55 m s -1, and provides the largest increase in intensity of any of the assumptions tested

Evidence of superintensity (eye turbo-boost) in 3-D models Invertible moist potential vorticity (left) and Θ e (right) from Braun (2002) Maximum Θ e is located on the SE, outward advecting side of the cyclonic eyewall mesovortex (+)

5 km MM5 idealized TC simulation of Frank and Ritchie (2001) E-MPI would be ~65 m s -1

Dropsondes reveal low level eye Θ e can be higher than in the eyewall Left: Hurricane Jimena Willoughby (1998) Below: Hurricane Isabel Aberson et al. (2006)

Dropsonde composites by LeeJoice (2000) found that in the 0-3 km layer, eye Θ e was K higher than the eyewall The eye has a significant vertical gradient of Θ e, while the eyewall does not

Is most of the mixing accomplished by large mesovortices, small misovortices, instabilities or waves? Is mixing continuous or are there large, transient mixing events that temporally deplete the eye reservoir?

Θ e (red) and 2-D streamlines (blue) overlaid with q l >.3 g kg -1 (light green) and q l >1 g kg -1 (dark green) in height-angular momentum space

Summary and Conclusions At high spatial resolution, 2-D axisymmetric hurricane simulations produce steady state storms that greatly exceed their E-MPI The cause of this superintensity was found to be the entrainment of high entropy air from the low level eye into the eyewall updraft In the real world, in the face of the many negative influences on intensity (vertical wind shear, convective asymmetries, and ocean feedbacks), this additional source of heating may be important factor in TC intensity