Findings of Previous Studies Oceans impact on tropical cyclone
(TC) intensity: Upwelling and vertical mixing of the cool ocean due
to the vortex can have a negative feedback On the other hand,
eddies can contribute to rapid intensification (RI) Inner core
processes: concentric eyewall cycles Collapse of inner eyewall
results in weakening Contraction of outer eyewall can strengthen a
TC Vertical Shear Low vertical shear results in RI
Slide 4
Findings of Previous Studies Continued Interaction of a TC with
an upper-level trough Studies are conflicting on this matter Other
important factors Deep layer of warm water Time of Day Eye diameter
And many others
Slide 5
Goal of the Study Determine if RI mechanisms proposed in
previous studies can be confirmed for a large dataset Compare
characteristics of RI and non-RI storms Develop a method for
estimating the probability of RI Serves as a rapid intensity index
(RII)
Slide 6
Rapid Intensification (RI) definition) 95th percentile of
over-water 24-hour intensity changes of Atlantic basin tropical
cyclones that developed from 1989 to 2000 Maximum sustained surface
wind speed increase of 15.4 m/s (30 kt) over a 24-h period.
Slide 7
Data Statistical Hurricane Intensity Prediction Scheme (SHIPS)
database Contains synoptic information every 12 hours the NHC
Hurricane Database (HURDAT) file used to analyze data 6-hour
estimates of various variables All Atlantic basin TCs from 1989 to
2000 Variables measured starting at t=0 hours Non-developing
depression information in NHC B Decks If TC is over land for 1
hour, it is an over-water system. 163 TCs (tropical depressions,
tropical storms, and hurricanes) for a total of 2621 cases.
Slide 8
Predictors
Slide 9
Maximum Potential Intensity(MPI) MPI = min[X, 85] X = A +
B(exp)[C(SST-SST 0 )] A = 34.2 m/s B = 55.8 m/s C=0.1813 0 C -1 SST
0 = 30 0 C
Slide 10
Frequency Distribution Tropical storms had more changes
exceeding 3 m/s than hurricanes or tropical depressions Tropical
storms are further from their MPI and are better organized
initially, so they can intensify faster.
Slide 11
Distribution of Intensity Change Sample size: 50 TCs, 159 RI
cases 4.4%, 7.4%, and 5.4% of the tropical depression, tropical
storm, and hurricane samples underwent RI, respectively.
Slide 12
Systems that featured RI 60% of systems were hurricane strength
83% reached major hurricane intensity All category 4 and 5
hurricanes underwent RI at least once 31% of all Atlantic TCs and
38% of all named storms underwent RI
Slide 13
Seasonality and Location of RI RI occurs mostly south of 30 0 N
Fewer RI cases in eastern Caribbean and eastern Gulf of Mexico.
Most RI during August and September.
Slide 14
Large-Scale Conditions Statistical significance determined by
2-sided t test that assumes unequal variances * = 95%, **=99%,
***=99.9% RI systems tend to be located farther south and west than
Non-RI systems RI systems have a more westerly component of
motion
Slide 15
Large-Scale Conditions Continued RI systems have high SST,
RHLO, and POT No statistical significance between VMX, JDAY, and
SPD for RI and non-RI Most statistically significant differences
for SST, RHLO, POT, SHR, and U200. RI have low SHR and REFC,
situated in a 200-hPa flow Impact of troughs on TC depends on
environment RI cases have low VMX RI occurs most frequently from 10
to 15 degrees N, and generally decreases with increasing LAT RI
tend to commence east of 40 0 W and from 80 0 to 100 0 W Slow storm
speed negatively impacts TC intensity. 92% of RI cases have SSTs
about 27 0 C RI cases have high POT, RHLO and relative humidity RI
cases have low SHR and REFC
Slide 16
Estimating Probability of RI Only done for statistical
significance of 95% or greater RI threshold = RI sample mean RI
probability = number of RI cases satisfying RI threshold / number
of cases in entire sample that satisfy the threshold. Various sets
of predictors combined into 5 predictors (at 99.9% statistically
significant): DVMX, SHR, SST, POT, and RHLO The resulting data on
next slide:
Slide 17
Predictor Probability Data
Slide 18
Key Findings from Study Definition of RI proposed for Atlantic
TCs The RI cases tended to occur farther south and west than the
non-RI cases. The RI cases were farther from their maximum
potential intensity and developed in regions of warmer water and
higher lower-tropospheric relative humidity than the non- RI cases.
Probability of RI prediction involved 5 factors: previous 12- h
intensity change, sea surface temperature, low-level relative
humidity, vertical shear, and the difference between the current
intensity and the maximum potential TC intensity
Slide 19
Future Work Add additional predictors: Upper-ocean heat content
Geostationary Operational Environmental Satellite (GOES) infrared
satellite imagery Use More sophisticated statistical methods
Slide 20
Kaplan 2010 Paper
Slide 21
Goals Develop a revised rapid intensity index (RII) Both for
Atlantic and eastern North Pacific basin Create versions of RII for
2 other RI thresholds: 25 and 35 kt (Kaplan 2003s was 30 kt) Verify
the revised RII using basin samples for all 3 thresholds
Slide 22
Methodology Mostly same procedures and data as in the Kaplan
2003 paper. Subtropical cases are included. 4 new predictors
added:
Slide 23
Methodology Differences from 2003 SHRD is evaluated after the
storm vortex is removed POT is determined using an adjusted
inner-core SST computed using an algorithm derived exclusively for
the Atlantic basin. Large-scale predictors are averaged along the
storm track from t=0 to t=24 h as opposed to being evaluated at t=0
hours Cases used for the study had to pass through screening first:
POT must be as large as the RI threshold
Slide 24
Methodology Differences Continued Cases where the values of any
of the 8 predictors are outside the range of RI predictor
magnitudes of the RI cases in the development sample arent
used
Slide 25
RI distribution Tracks for 35-kt are more restricted Few North
of 30 0 N Concentrated in central Atlantic between 10 0 N and 20 0
N and 20 0 and 60 0W
Slide 26
RI Predictor Data RI systems have high PER, OHC, D200, RHLO,
PX30, and SDBT RI systems have low SHRD and SDB
Slide 27
Scaled Version of RII Kaplan 2003 paper couldnt account for the
degree to which conditions were favorable or unfavorable. Each
predictor is assigned a scaled value between 0 (least conductive)
and 1 (most conductive) for RI (S p ) Sum all the scaled values (R
S ) R S = 0 if any of the S p = 0 Place R S values into 4 quartiles
Lowest R S in the first quartile Equal number of RI cases in each
quartile Probability is calculated by dividing number of RI cases
by total number of cases in each quartile.
Slide 28
Linear Discriminant version of RI Accounts for relative
importance of each predictor R S = 0 samples excluded Each weight,
W n, is multiplied by the corresponding S p, then add everything (R
d ) The R d s are put into quartiles and the probabilities
calculated in the same way as the scaled version
Slide 29
RI Predictor Weight Results Kinematic predictors (D200 and
SHRD) have at least twice the weight of thermodynamic predictors
(POT, RHLO, and OHC) for all thresholds Predictors can be treated
as independent of each other
Slide 30
RII Skill Calculation First, compute the Brier Score (BS)
Convert R s and R d values to RI probabilities (0 to 1) by linearly
interpolating Subtract from 0 if RI is not observed Subtract from 1
when RI is observed Square that number Compute the Brier Skill
Score (BSS): BSS = [1-(BSM/BSC)] x 100 BSM= BS of RII forecast BSC=
BS of climatological forecast 100%= prefect skill
Slide 31
RI Skill Data
Slide 32
Probabilistic Verification Cross validation method Storms from
each of the individual years that composed the 12-year
developmental sample are excluded RII is rederived for each RI
threshold using only cases from the remaining 11-year sample That
RII is run on the cases from the excluded year Repeat the procedure
for each of the individual years in the 12 year sample and tabulate
results
Slide 33
Probabilistic Verification Data
Slide 34
Deterministic Verification Choose a single probability
threshold The value of the discriminant function that matches the
climatological probability of false detection (POFD) POFD =
climatological probability of RI/ (1 + climatological probability
of RI for each RI threshold) Repeat the calculation of POFD for
each quartile and each threshold
Slide 35
Probability Thresholds
Slide 36
Conclusions Revised RII index made for Atlantic and North
Pacific Basins Separate RII index made for 25kt and 35 kt
Probability of detection (POD) for the RII ranged from 15% to 59%
(53% to 73%) while the false alarm ratio (FAR) ranged from 71% to
85% (53% to 79%) in the Atlantic (eastern North Pacific) basins,
respectively. So, generally pretty good.