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Dynamical Seasonal Hurricane
Hindcast Simulations
Tim LaRowY.-K. Lim, D.W. Shin, E. Chassignet and S. Cocke
CDPW Meeting – October 23, 2007- Tallahassee
email: [email protected]
Outline
•Motivation
•Previous Studies
•Detection/Tracking Algorithm
•Experimental Design
•Results
•Atlantic Domain
•Summary/Conclusions/Future
Motivation – Part 1
Can We Simulate Interannual Variability?
1997 Observed Tracks 2005 Observed Tracks
Previous Studies
•Current climate models can simulate many of the features of
observed tropical cyclones that have spatial scales resolvable
by such models. These include: •Warm core structure (upper-tropospheric anticyclonic
circulation above cyclonic low-level circulation) •Existence of strong upward motion andHeavy precipitation accompanying the storm
•Geographical distributions, intraseasonal, and interannual
variability of simulated storms are similar to observed
(Manabe et al. 1970, Manabe 1990, 1992; Wu and Lau 1992
Haarsma et al. 1993; Vitart et al. 2006, 2007;
Bengtsson et al. 1982, 1995,2007;
Camargo et al. 2005; Knutson et al. 2007)
Summary from Previous Studies
• Modeled tropical cyclones tend to be:• too weak• tracks too short and some have a poleward bias• storms too large and • lack of genesis in certain regions.
Problems in part due to low resolution models used. O(200-400km) –
although not the complete story.
Detection Algorithm
•Local relative vorticity maximum greater than 4.5x10-5 s-1 is located at
850hPa.
•Next, the closet local minimum in sea level pressure is detected and defines
the center of the storm. Must exist within a 2°x2° radius of the vorticity
maximum.
•Third, the closest local maximum in temperature averaged between 200hPa
and 500hPa is defined as the center of the warm core. The distance from the
warm core center and the center of the storm must not exceed 2°. The
temperature must decrease by at least 6K in all directions from the warm
core center within a distance of 4°.
Max/Min are located and gradients calculated using bicubic splines which
allow for higher precision than the model resolution.
Tracking Algorithm
After the data base of storm snapshots are collected a check is performed to
see if there are storms within 200km during the next 6 hours.
If no, the trajectory is stopped. If yes, the closest storm to the previous 6
hours storm's trajectory is picked. If more than one storm is identified,
preference is given to storms which are west and poleward of the given
location.
•Trajectories must last more than 2 days, have lowest model level wind
velocity within a 8° radius circle centered on the storm center greater than 17
m s-1 during at least 2 days (does not have to be consecutive days).
Experimental Design
•Atlantic hurricane season (June-November) hindcast simulations from 1986 to 2005 (20 years).
•Weekly updated observed SSTs (Reynolds et al. 2002).
•FSU/COAPS global spectral model – T126L27 resolution ~ 100km
•4 member ensembles for each year. Time lagged ECMWF atmospheric initial conditions centered on 1 June of the respective year. A total of 80 experiments.
•RAS Convective Scheme (Hogan and Rosmond 1991) - Control
NCAR (Zhang and McFarlane 1995) Convection Scheme•6 hourly output
“HTV” Landfalls 1986-2005 - Control
“Gates” Ensemble 1 Ensemble 2 Ensemble 3 Ensemble 4 HURDAT
Texas 8 14 10 4 35
Louisiana-Miss. 3 3 2 5 12
Florida-Georgia-Al. 23 17 17 15 32
Mid-Atlantic 2 4 5 2 13
New England 2 4 5 2 13
Ensemble Summary
Observations Ensemble 1 Ensemble 2 Ensemble 3 Ensemble 4 Ens. Mean
Total # ofStorms
245 242 234 234 249 240
Correlation 0.76 0.51 0.71 0.62 0.78
Variance 25.25 20.2 12.96 18.01 14.89 12.55
“HTV” Landfalls 1986-2005 – Sensitivity to Convection
Scheme
“Gates” NCAR Convection Scheme HURDAT
Texas 21 35
Louisiana-Miss. 6 12
Florida-Georgia-Al. 25 32
Mid-Atlantic 12 13
New England 12 13
Model and Observational Wind-Pressure Relationship-
Atlantic DomainKnutson et al. 2007, BAMS
18km Non-Hydrostatic Model
FSU/COAPS T126 Model(All 80 Ensemble Members)
1980-2005 1986-2005
Wind Pressure Relationship
Min
slp
(h
Pa
)
Wind Speed (m/s)
Lowest Pressure 936hPa
Model Atlantic/Pacific Basin Summary
Atlantic Pacific
Avg. Duration 7.5 days 8.3 days
(8.9 days) (9.6 days)
Avg. Central Pressure 995.9hPa 990.7hPa
850hPa Wind Max 60m/s 66m/s
Max Intensity 936hPa 926hPa
Avg. Number of Storms 11.7 15.9
Summary/Conclusions
Ensemble hindcast results from a relatively high resolution atmospheric model
(T126L27) have been presented for 20-years of the Atlantic Basin hurricane
season using 2 different convection schemes.
Linear correlation of the interannual variability of the tropical storm frequency
against observation was found to be high (0.78) using the Hogan and Rosmond
convection, less so for the Zhang and McFarlane convection scheme.
Large sensitivity in track locations, storm numbers and interannual variability
was found between the two convection schemes and choice of diffusion coefficient
(not shown).
Model appears to simulate the ENSO-Atlantic covariation well.
Summary/Conclusions - cont.
•The model with the best interannual variability was NOT the best in simulating
land falling storms along the east coast of the U.S. and Gulf of Mexico. In part due
to the atmospheric large-scale response to the model's convection and the resulting
large-scale steering flow.
The model's surface wind-pressure relationship was found to be similar to a
20km global model (JMA not shown) and also an 18km non-hydrostatic model
(GFDL). All models fail to produce sufficient CAT3-5 level storms in terms of
surface winds.
Present Work
Better understanding of the sensitivity of tracks and intensity to the
choice of convection, diffusion coefficients and tracking algorithm.
Use selective years from the hindcast experiments and run the
FSU/COAPS regional spectral model to study higher horizontal
resolution impacts on hurricane seasonal statistics.