Environmental Sensitivity of the Structural
Evolution of Hurricane Irene (2011)
Jason W. Godwin
MPO Student Seminar
24 March 2014
Background
• Tropical cyclone (TC) track forecasts have
substantially improved in the last 20 years, but
intensity forecasts have improved little.
• Being able to predict intensity is largely
dependent on being able to predict the TC
structure.
• Hurricane Irene (2011) is a good case study.
Operational Challenges
• Track forecast had smaller
errors than the five-year
average
• Intensity errors were larger
than the five-year average
• Incomplete eyewall
replacement cycle led to
weaker winds, despite
continued deepening
• Wind field expanded as
pressure fell
• Avila and Cangialosi (2011)
NHC official track forecasts (black) and track
verification (white)
NHC was expecting a strong, compact hurricane…
instead, we got a weaker, broader hurricane
Intensity forecasts (maximum sustained winds)
Consistent high-bias in intensity
forecast
Northeast quadrant gale force wind radius forecasts
Radius of gale-force winds under
forecast
Which environmental features influenced the size and
structure of Irene?
• The NHC noted that the
environmental was
conducive for
strengthening, but why
did Irene not strengthen?
– Warm SSTs
– Weak vertical wind shear
– Moist environment
• Even after reaching peak
intensity, Irene continued
to deepen for another 2436 hours.
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Research Questions
• Part 1: Was the structure of Hurricane Irene
sensitive to synoptic-scale features?
– Vorticity perturbations (Komaromi et al. 2011)
• Part 2: Was the structure of Hurricane Irene
sensitive to moisture?
– Moisture perturbations (Hill and Lackmann 2009)
Part 1: Vorticity Perturbation Technique
• Developed by Komaromi
et al. (2011)
• Allows user to perturb
the relative vorticity at an
specified point, by a
specified amount.
• Rebalances momentum,
mass, and
thermodynamic fields
• Integrate WRF with
Vorticity perturbation experiments
perturbed fields.
showing significant initial condition
sensitivity for the track of Typhoon
Sinlaku (2008)
Methodology
• Apply relative vorticity perturbations on
important synoptic-scale features that may
have influenced the forecast for Hurricane
Irene.
• Compare against control WRF-ARW simulation
and best-track forecast.
• Primarily interested in TC size, structure, and
intensity.
Model
• Version 3.5 of WRF-ARW
• 27 km grid spacing
(interested distant features
on the synoptic scale)
– Kain-Fritsch Cumulus
Parameterization
– WRF Double Moment SixClass (WMD6) Microphysical
Parameterization
• Initialized at 00 UTC on 23
August 2011
• Nested within NCEP-GFS
• Control simulations and
perturbed simulations
Perturbation Experiment #1
• Strengthened shortwave
trough over northwestern
North Dakota.
• Perturbations should be
realistic (i.e. within “normal”
model error) and local
“AFTER THAT TIME...THE TRACK OF IRENE
APPEARS TO BE SENSITIVE TO THE TIMING
AND AMPLITUDE OF SEVERAL SHORTWAVE
TROUGHS MOVING EASTWARD ACROSS THE
UNITED STATES/CANADIAN BORDER. THE
MODELS ARE SHOWING SOME RUN-TO-RUN
VARIABILITY IN HOW MUCH THESE
SHORTWAVES WILL AMPLIFY AND DEEPEN THE
MEAN TROUGH OVER THE NORTHEASTERN
UNITED STATES...WHICH WILL BE CRITICAL
TO HOW SOON IRENE TURNS NORTHWARD OR
EVEN EAST OF DUE NORTH AT DAYS 4 AND
5.” –NHC Forecast Discussion (11 PM EDT
8/22/2011)
300 hPa relative vorticity difference
field (perturbed – control) at 00 UTC
on 08/23/2011
Track
Control simulation
Perturbed simulation
NHC Best-Track
WRF Forecast
Resulted in about a 25 km shift in the track on Day 4, so a small change, but a
change nevertheless. Small cross-track error, but the perturbed run also resulted in
a slightly faster hurricane.
Intensity
Control simulation
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Perturbed simulation
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There was virtually no change in the maximum
sustained winds forecast.
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Wind Radii
Control simulation
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Perturbed simulation
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Again, two very similar forecasts (note that these radii are larger than the NHC ones due to
differences and how the radii are computed, so it’s more important to focus on the trends in
the radii). It appears that the North Dakota perturbation had little impact on the forecast.
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250 hPa PV, winds, and 500 hPa geopotential
Control simulation
Perturbed simulation
00 UTC 28
23 August 2011
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Ongoing work
• Perturb features during the simulation (WRF
restart)
• Perturb the TC vortex itself (upper-level
anticyclone, or low-level cyclone)
Part 2: Moisture Perturbations
• Uses the same technique as Komaromi et al.
(2011) for defining the perturbations, but adjusts
water vapor mixing ratio to start
• Rebalances mass, momentum, and
thermodynamic fields
• Hill and Lackmann (2009) used varying moisture
profiles in WRF-ARW idealized simulations to
investigate how moisture influenced TC size. They
hypothesized that a more moist environment led
to a larger TC.
Moisture Perturbation Experiment #1
• Performed a dry
perturbation in which
the TC core, and near
storm environment
were “dried out”.
• Reducing moisture
should act to cool the
warm core (via
evaporative cooling)
and reduce convective
instability.
700 hPa water vapor mixing
ratio difference (perturbed –
control) and sea-level pressure
at 00 UTC on August 23, 2011
Track
Control simulation
Perturbed simulation
NHC Best-Track
WRF Forecast
The perturbed simulation shows significant degradation of the track forecast with large crosstrack errors, and a much slower storm. It is likely that this is due to a weaker, shallower storm
compared to the control simulation.
Intensity
Control simulation
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Perturbed simulation
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As expected, the drier storm core and near-storm environment leads
to a weaker storm, though later in the forecast period, the perturbed
simulation begins to “catch up” to the control simulation as moisture
off the southeastern U.S. coast begins to be entrained by Irene.
Wind radii
Control simulation
Perturbed simulation
The drier storm environment results in a smaller storm,
which is consistent with Hill and Lackmann (2009).
10-meter winds and sea level pressure
Control simulation
Perturbed simulation
Max winds: 32.4
27.6 m/s | Min pressure: 956
33.0
37.1
41.2
41.1
999 hPa
977
961
948
951
Max winds: 38.4
27.6 m/s | Min pressure: 950
25.4
26.4
37.9
39.5
999 hPa
993
986
961
953
00 UTC 28
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23 August 2011
Ongoing work
• Try the “opposite” experiment where the
storm and its environment are moistened.
• Dry/moisten outside of the storm or ahead of
the storm.
• Perform dry/moist experiments on a 3 km grid
to analyze storm-scale convection.
Preliminary conclusions/future work
• Distant vorticity perturbations have little
impact on the ultimate track, intensity, and
structure on the model forecasts.
– Further testing is needed later in the model
forecast, and with the TC vortex itself.
• Moisture perturbations show a large amount
of sensitivity.
Questions?
References
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Avila, Lixion A., and John Cangialosi, 2011: Hurricane Irene. Tropical Cyclone
Report, 45 pp.
Hill, Kevin A., Gary M. Lackmann, 2009: Influence of Environmental Humidity
on Tropical Cyclone Size. Mon. Wea. Rev., 137, 3294-3315.
Kain, John S., J. Michael Fritsch, 1990: A One-Dimensional
Entraining/Detraining Plume Model and Its Application in Convective
Parameterization. J. Atmos. Sci., 47, 2784–2802.
Komaromi, William A., Sharanya J. Majumdar, Eric D. Rappin, 2011: Diagnosing
Initial Condition Sensitivity of Typhoon Sinlaku (2008) and Hurricane Ike
(2008). Mon. Wea. Rev., 139, 3224–3242.
Lim, Kyo-Sun Sunny, Song-You Hong, 2010: Development of an Effective
Double-Moment Cloud Microphysics Scheme with Prognostic Cloud
Condensation Nuclei (CCN) for Weather and Climate Models. Mon. Wea. Rev.,
138, 1587–1612.
Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang, and
J. G. Powers, 2005: A description of the advanced research WRF version 2.
NCAR Tech. Note NCAR/TN-468+STR, 88 pp.
How are the perturbations generated?
(Komaromi et al. 2011)
•
𝑅 − 𝑟 𝑝 − 𝑝𝑡𝑜𝑝
𝛼
𝑅 𝑝𝑏𝑜𝑡 − 𝑝𝑡𝑜𝑝 𝑚𝑎𝑥
α is related to the amount of perturbation at distance from the center of the perturbation (r) at
pressure attitude (p). R is the maximum radius of the perturbation, pbot and ptop are the bottom and
top of the perturbation, respectively, and αmax is the maximum perturbation.
𝜁1 = 𝜁0 + 𝜁 ′ = [1 + 𝛼 𝑟, 𝑝 ]𝜁0
The new relative vorticity field (ζ1) is given as the sum of the original relative vorticity (ζ0) and the
perturbation relative vorticity (ζ’).
The rebalanced streamfunction is obtained by using a successive over relaxation technique to invert
the Laplacian: 𝜁′ = 𝛻 2 𝜓′
Wind field derived from: 𝑣 ′ = 𝑘 × 𝛻𝜓′, 𝑣 = 𝑣0 + 𝑣′
•
Height: 𝜙 ′ =
•
Temperature: T = −
•
Moisture perturbations are derived similarly, except that water vapor mixing ratio (q) is the
perturbed quantity instead of relative vorticity. The height field is then rebalanced by re-computing
virtual temperature and using the hypsometric equation, then the wind field is derived using
geostrophy.
𝛼 𝑟, 𝑝 = 2
•
•
•
𝑓0
𝜓′
𝑔
1 𝜕𝜙
𝑅 𝜕ln(𝑝)