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Characteristics of Tropical Cyclone Rapid Intensification over
the Western North Pacific
HIRONORI FUDEYASU
Yokohama National University, Yokohama, Japan

KOSUKE ITO
University of the Ryukyus, Nishihara, JapanYOSHIAKI MIYAMOTO
Keio University, Fujisawa, and RIKEN, Kobe, Japan(Manuscript received 29 September 2017, in final form 8 August 2018)
ABSTRACTThis study statistically investigates the characteristics of tropical cyclones (TCs) undergoing rapid intensification (RI) in the western North Pacific in the 37 years from 1979 to 2015 and the relevant atmosphericand oceanic environments. Among 900 TCs, 201 TCs undergoing RI (RI-TCs) are detected by our definition
as a wind speed increase of 30 kt (15.4 m s21) or more in a 24-h period. RI-TCs potentially occur throughout
the year, with low variation in RI-TC occurrence rate among the seasons. Conversely, the annual occurrenceof RI-TC varies widely. In El Niño years, TCs tend to undergo RI mainly as a result of average locations at thetime of tropical storm formation (TSF) being farther east and south, whereas TCs experience RI less frequently in La Niña years. The occurrence rates of RI-TC increased from the 1990s to the late 2000s. The RI
onset time is typically 0–66 h after the TSF and the duration that satisfies the criteria of RI is 1–2 days. RI
frequently occurs over the zonally elongated area around the eastern Philippine Sea. The development stage
and life-span are longer in RI-TCs than in TCs that do not undergo RI. RI-TCs are small at the time of TSF
and tend to develop as intense TCs as a result of environmental conditions favorable for TC development,
weak vertical wind shear, high convective available potential energy, and tropical cyclone heat potential. The
occurrence rates of RI-TCs that make landfall in Japan and the Philippines are higher than in China and Vietnam.

1. Introduction
Statistical analyses have shown that most category 4
and 5 Atlantic hurricanes undergo rapid intensification(RI) during their lifetimes (Kaplan and DeMaria 2003).
Once a tropical cyclone (TC) begins RI, the TC attains astrong intensity (Lee et al. 2016). Hence, predicting RI is
critically important for disaster prevention. However,
RI prediction remains a significant challenge (Rappaportet al. 2012; Ito 2016).
Strong TCs typically experience two intensifying periods: an initial slow intensification and subsequent RI(e.g., Sitkowski and Barnes 2009). The intensification
rate of the TC strongly depends on diabatic heating in
the core region (e.g., Schubert and Hack 1982), andCorresponding author: H. Fudeyasu, fude@ynu.ac.jp

heating within the radius of maximum wind (RMW)
intensifies the TC more efficiently (e.g., Shapiro andWilloughby 1982; Pendergrass and Willoughby 2009;
Vigh and Schubert 2009; Ito et al. 2011; Fudeyasu andWang 2011; Rogers et al. 2013). Furthermore, a larger
symmetric heating component favors TC intensification(Nolan and Grasso 2003; Nolan et al. 2007). Many observational and modeling studies have shown that symmetric cloud structure is dominant inside the RMWduring RI (Guimond et al. 2010; Harnos and Nesbitt
2011; Kieper and Jiang 2012; Jiang 2012; Miyamoto andTakemi 2013, 2015; Wang and Wang 2014; Zawislak
et al. 2016; Rogers et al. 2013, 2016; Chang and Wu 2017;
Shimada et al. 2017; Miyamoto and Nolan 2018). Modeling studies have indicated that TCs intensify throughfeedback between symmetric convection in the core andlow-level mass convergence during RI, as described in

DOI: 10.1175/JCLI-D-17-0653.1
Ó 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright
Policy (www.ametsoc.org/PUBSReuseLicenses).

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classical theories (Miyamoto and Takemi 2013, 2015;
Chang and Wu 2017). Conversely, other studies show
asymmetric convection is more distinct in the downshear
side than symmetric convection (e.g., Molinari andVollaro 2010; Chen et al. 2011; Nguyen and Molinari
2012; Zhang and Chen 2012; Chen and Zhang 2013;
Chen and Gopalakrishnan 2015; Miller et al. 2015).
A pioneering study of RI by Kaplan and DeMaria(2003) identified large-scale characteristics of TCs undergoing RI (RI-TCs) in the North Atlantic, using theStatistical Hurricane Intensity Prediction Scheme (SHIPS)
database. This statistical study was followed by those, including Kaplan et al. (2010, 2015) and Rozoff and Kossin(2011), who examined these large-scale characteristics for
the Atlantic and eastern North Pacific basins. In particular,
these studies showed that the occurrence of RI-TCs depends on environmental parameters such as a large intensity change during the previous 12 h, weak vertical wind
shear, high relative humidity, large ocean heat content,
large upper-level divergence, high symmetric distributionof brightness temperature, and a large difference between
maximum potential intensity (MPI) and current TC
intensity.
The ocean is a major energy source driving TCs(Leipper and Volgenau 1972; Lin et al. 2008), even asTCs cool the sea surface temperature (SST) of the underlying ocean by producing turbulent mixing or upwelling (Leipper 1967; O’Brien and Reid 1967; O’Brien
1967; Price 1981). It has been proposed that a warm
upper-ocean structure, namely, large ocean heat content, likely contributes to RI by reducing the magnitudeof TC-induced cooling at the ocean surface (e.g., Honget al. 2000; Shay et al. 2000; Cione and Uhlhorn 2003;
Lin et al. 2005, 2008; Wu et al. 2007; Wada 2015).
Miyamoto et al. (2017) developed an analytical model of
one-dimensional ocean mixing through wind forcing
by a TC and a dimensionless quantity representing themagnitude of TC-induced cooling.
Kaplan et al. (2015) showed that the relative importance of parameters differs between the Atlantic and theeastern North Pacific. Although statistical studies havebeen conducted on data from the Atlantic and theeastern North Pacific, few statistical studies have examined RI-TCs in the western North Pacific (WNP),
which is the most active TC region in the world. To ourknowledge, two statistical studies of the WNP focusing
on RI-TCs were by Wang et al. (2015) and Hendricks
et al. (2010, hereafter H10). Wang et al. (2015) investigated the multidecadal variability of RI events inthe WNP, but they did not study annual changes in RITC activity and characteristics of RI-TCs. Using a global
analysis, H10 found that RI is largely controlled underfavorable environmental conditions and that atmospheric

VOLUME 31

conditions in the WNP favor TC intensification. However, H10 did not examine some important features
relevant to TCs that have been examined in the statistical and modeling studies cited above, for example, TC
structure and ocean heat content. The analysis period
for RI-TC in H10 was six years from 2003 to 2008; annual changes in RI-TC activity were not investigated in
the study. Furthermore, H10 used a different definitionof RI from that widely used in statistical analyses of RI,
30 kt (15.4 m s21) in a 24-h period: their definition was
38 kt (19.5 m s21) in a 24-h period for the WNP and 35 kt(18.0 m s21) in a 24-h period for the Atlantic.
Therefore, in this study we statistically investigatedthe characteristics of RI-TCs and RI-TCs associatedwith the environmental physical parameters that influence RI, including both atmospheric and oceanic features. The analysis period was 37 years, from 1979 to2015, in which annual changes in RI-TC activity were
examined. For the analysis, RI was defined as an increase in wind speed of 30 kt or more in a 24-h period.

2. DataThis study examined 900 TCs occurring over the WNP
during the 37 years from 1979 to 2015 with tropical storm(TS) intensity or greater, that is, with a maximum sustained wind speed at least 35 kt, as derived from the best
track (BT) data created by the Regional Specialized
Meteorological Center (RSMC) Tokyo–Typhoon Center of the Japan Meteorological Agency (JMA). To accurately detect RI-TCs, TCs that reached TS intensity
over the eastern North Pacific and then entered the
WNP were excluded, as well as TCs that retained TS
intensity beyond the end time listed in the BT data.
We detected RI-TCs and TCs that did not experience
RI (NR-TCs), where RI is defined as an increase in windspeed of 30 kt or more in a 24-h period. Similar to theprevious studies (e.g., Kaplan and DeMaria 2003), thefrequency distributions of the 24-h intensity changes of
900 TCs were analyzed (Fig. 1). Our threshold corresponds to approximately the 96th percentile, which issimilar to the results of Kaplan and DeMaria (2003) for
the Atlantic; their RI threshold corresponded to the95th percentile.
Throughout the lifetime of each TC, we determined
the times at which the following events occurred: TSformation (TSF), time at which a TC satisfies the RI
definition (RI onset), end time of RI, time when a TC
achieves maximum intensity (maturity), and time of
decay. The end of RI corresponded to the time at which
the development rate no longer satisfied the criteria of
the RI definition. The decay time referred to the time atwhich the intensity is below the TS intensity.

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FIG. 1. (a) Occurrence rate and (b) cumulative frequency distributions of 24-h intensity change of TCs over the
37-yr analysis period. This study focused only on TCs that had TS intensity or greater.

In this work, a one-tailed bootstrap-based test with
10 000 resamples and a conventional t test were employed to check if the difference in general characteristics of TC structures and environmental parameters
between RI-TC and NR-TC is statistically significant.
We call the differences ‘‘significant’’ if the confidence
level is over 95% in both statistical tests. Statistical TC
characteristics, such as location, intensity (a maximum
sustained wind speed and central pressure), and size inthe horizontal direction (averaged radius of 30-kt sustained wind) were derived from the BT data.
We also investigated differences in environmental
physical parameters between RI-TCs and NR-TCs. Atmospheric information was retrieved from the Japanese
55-year Reanalysis (JRA-55; Kobayashi et al. 2015)(details available online at http://jra.kishou.go.jp/JRA55/index_en.html). JRA-55 collected data every 6 hwith a horizontal resolution of 1.258 for both longitude
and latitude from 1958 to the present. Oceanic data were
derived from the three-dimensional variational-based
parent domain output from the Four-Dimensional
Variational Ocean Reanalysis for the Western North
Pacific (FORA-WNP30; Usui et al. 2017) (details available online at http://synthesis.jamstec.go.jp/FORA). These
data have a horizontal resolution of 0.58 for both longitude
and latitude, with 54 vertical levels from 0.5- to 6000-m
depth and a 6-h time interval from 1982 to 2015. Note that
this study did not use the nested high-resolution domain
output of the FORA-WNP30 with a horizontal resolutionof 0.18 because the nested domain was limited to the areathat did not cover the WNP completely.
Using JRA-55 and FORA-WNP30, we evaluateddifferences in the following environmental physical parameters: magnitude of vertical wind shear, atmosphericrelative humidity, MPI, convective available potential
energy (CAPE) derived from the MPI equation, SST,
tropical cyclone heat potential (TCHP), depth of the
268C oceanic isotherm, 0–100-m-depth average ocean

temperature, and ocean cooling parameter. Atmospheric relative humidity was calculated in atmosphericlayers—850–700 (RHLO), 700–500 (RHMD), and 500–
300 hPa (RHHI)—within an annulus of 200–800 km
from the TC center. As was used in several previous
studies (e.g., Knaff et al. 2005), this annular average wasused to estimate environmental parameters in this study.
To remove the effect of terrain, the averages for parameters were not included over land. The magnitude ofvertical wind shear was defined as the difference inhorizontal winds between 200 and 850 hPa (SHRD) andbetween 500 and 850 hPa (SHRS). The zonal components of the vertical wind shear in these layers were also
created (USHRD and USHRS, respectively).
The oceanic parameters—SST, TCHP, depth of the
268C oceanic isotherm, and 0–100-m-depth averageocean temperature—were calculated within a circulararea with an 800-km radius from the TC center tostratify distinct features by RI conditions. Statisticalanalyses for the atmospheric and oceanic parameters
were used to associate TCs with each factor over the 34
years from 1982 to 2015, the same as the available periodof FORA-WNP30.
We examined the differences in MPI and CAPE between the RI and NR conditions. MPI was originallyproposed by Emanuel (1986); the revised version presented by Bister and Emanuel (1998) was used in ourstudy. MPI was calculated from atmospheric data within
an annulus of 200–800 km from the TC center over 34
years, the same as the available period of both JRA-55
and FORA-WNP30. To compare atmospheric stability
between RI-TC and NR-TC environments, we used
E-CAPE, a version of CAPE calculated from the simple
equation presented in MPI theory, which is an approximate form [equations are introduced in detail by
Emanuel (1994) and Bister and Emanuel (2002)].
E-CAPE was calculated within an annulus of 200–800 km
from the TC center.

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TCHP was estimated by summing ocean heat content
from the surface to the depth of the 268C isotherm(Leipper and Volgenau 1972; Wada 2015), as follows:
Z26

Q 5 Cp å ri (Ti 2 26)Dzi ,

(1)

z50

where Q is TCHP (kJ cm22), Cp is specific heat at constant pressure, Ti is water temperature (8C) at the ith
level, Dzi is layer water thickness at the ith level (m), andri is the density of water at the ith level. The parameter Z26 is the depth (m) of the 268C isotherm (m).
TCHP was calculated within a circular area with an
800-km radius from the TC center over 34 years from
FORA-WNP30.
Miyamoto et al. (2017) developed an ocean coolingparameter that is a dimensionless quantity representing
the magnitude of ocean cooling by turbulent mixing in
the upper ocean caused by wind forcing. The quantity isdefined as the ratio of wind forcing (related to windspeed, TC size, and speeds of TC motion) and ocean
stability (determined by temperature profile), as follows:
2F 2 t 2
Co 5 2 ms0 4 ,r agGh0(2)

where Co is the nondimensional ocean cooling parameter, Fms0 is the surface momentum flux (kg m21 s22), t is
the mixing time scale (s), a is the thermal expansion
coefficient (K21), g is gravitational acceleration (m s22),
G is the temperature lapse rate below the mixed layer(K m21), and h0 is the mixed layer depth (m). The momentum flux is calculated by using MPI and a fixed dragcoefficient. The time scale of mixing is defined as theratio of a size parameter (namely, the RMW andthe 30-kt sustained wind) to the speed of TC motion.
The definition of the size parameter can be found in
Miyamoto et al. (2017), and this study used the average
RMW (40 km at the TSF and 25 km at the maturity). The
speed of TC motion was defined as the distance from thetime to 6 h later. Note that the ocean cooling parameter
was calculated below the TC center over 34 years from
FORA-WNP30.

3. Resultsa. Annual and interannual variation in RI-TC
Among the 900 TCs over the analysis period from1979 to 2015, 201 RI-TCs (22% of the total) and 699 NRTCs were detected by our definition. Figure 2 shows thetotal number of RI-TCs for each month during theanalysis period. There was large variability in seasonality among the number of RI-TCs; many of these

FIG. 2. Monthly total number of RI-TC occurrences over the 37-yr
analysis period.

occurred in summer and autumn. Because this seasonalvariation was partly due to seasonal variation among all
TC occurrences, we examined the rates of RI-TC occurrence by the monthly total of TCs. The differences in
the monthly occurrence rates of RI-TC were low, at amonthly rate of 10%–30% (not shown). Hence, RIs
potentially occur throughout the year with relatively low
variation of RI-TC occurrence rate in the seasonality.
Figure 3 shows the annual number and RI-TC occurrence rate over the WNP from 1979 to 2015. In 2015,
12 RI-TCs was the most frequent number, followed by
10 RI-TCs in 1982 and 2004. In contrast, only one RI-TC
was observed in 1988, 1990, and 1999. As shown in
Fig. 3b, the RI-TC occurrence rates, the number of RITCs divided by the number of TCs per year, varied
widely from about 5% to nearly 50%.
Table 1 shows the 5-yr mean of RI-TC occurrence rates
from the early 1980s to the early 2010s. The rates of RI-TC
occurrence increased from the 1990s to the late 2000s, with apeak in the late 2010s (34%). Ito (2016), counting an RI
event from a 6-hourly individual record, reported that the
RI occurrence rate had nearly doubled within the past 25
years. The increases of RI-TCs in the late 2000s were also
seen in the dataset published by the JTWC (Wang et al.
2015). It could result from a climatological change in thephysical parameters that will be investigated in this study orchange in the policy of constructing a best track dataset.
The distribution of high SST over the WNP was foundto be a key condition determining RI-TC occurrence. It
is therefore possible that relatively high/low SSTs over
the WNP were related to El Niño–Southern Oscillation(ENSO), resulting in annual variability in the number of
RI-TC occurrences. In this study, ENSO years wereselected by the JMA definition: El Niño (La Niña) was
such that the 5-month running mean SST deviation for
Niño-3 (58S–58N, 1508–908W) continues 0.58C (20.58C)
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FIG. 3. Annual variation in RI-TC occurrence over the 37-yr analysis period. (a) Number of RI-TCs per year and (b) RI-TC occurrence
rates normalized by the annual total. Filled bars indicate El Niño years; white bars are La Niña years; and gray bars are neutral years, whenneither phenomenon occurred.

August. There were 10 El Niño years (1982, 1983, 1987,
1991, 1992, 1997, 2002, 2009, 2014, and 2015) and 8 La
Niña years (1984, 1985, 1988, 1995, 1998, 1999, 2007, and2010) (Fig. 3). The average number of annual occurrences (6.7) and the RI-TC occurrence rate (28%) in El
Niño years was approximately double those in La Niña
years (3.4, 15%). In neutral years when neither phenomenon occurred, the average number of annual occurrences was 5.6 with the RI-TC occurrence rate of 23%.
To avoid the different results provided by the different definitions of ENSO years, this study investigated
the annual variability in the RI-TC occurrence number(rate) related to ENSO. As one of the results, the scatter
diagram in Fig. 4 shows the relationship between the RITC occurrences rate and an annual mean SST deviation for
Niño-3. Occurrence rates of RI-TC are higher with increasing annual mean SST deviation. The annual variability
in the RI-TC occurrences rate is highly correlated with SST
deviation for Niño-3 with a correlation coefficient of 0.41.
Thus, TCs in an El Niño year tended to undergo RI, whereas
TCs in a La Niña year experienced RI less frequently.

b. Distribution of RI events

the total), followed by 24–30 h (18%) and 36–42 h(16%). The RI onset above 3 days after the TSF wasvery low. Figure 5b shows the distribution of the RI
duration, defined by the period between RI onset and RI
end. A 24-h duration was the most frequent (30% of thetotal), and the number of RI occurrences decreased as
RI duration increased. It should be noted that there
were no RI-TCs with an RI duration greater than 60 h.
Figure 6 shows the distributions of locations of RI
onset. RI was most frequently observed in the elongatedregion around the eastern Philippine Sea, whereas it wasrare for RI to occur in the northern part of the WNP and
the South China Sea. This study defined the RI zone atlongitudes of 1218–1438E and latitudes of 98–218N. The
RI zone detected in this study was similar to that reported by H10, which used a different RI definition.

c. Statistical characteristics of RI-TCs
This study examined the statistical characteristics of
RI-TCs, comparing NR-TC averages at the TSF, thematurity, and the decay. At the TSF, there were nodifferences in the average intensities of RI-TCs andFigure 5a shows RI onset time from the TSF. A peakin RI onset occurred at 12–18 h after the TSF (19% of
TABLE 1. Frequency of occurrence of RI-TCs and NR-TCs, andtheir respective rates of occurrence. Data are classified into 5-yr
intervals.

Early 1980s
Late 1980s
Early 1990s
Late 1990s
Early 2000s
Late 2000s
Early 2010sRI

NR

RI rate (%)

37
19
21
13
27
38
27

87
116
118
97
93
74
85

30
14
15
12
23
34
24

FIG. 4. Scatter diagram showing the relationship between annual
mean SST deviation for Niño-3 and RI-TC occurrence rates overthe 37-yr analysis period.

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FIG. 5. Occurrence rates of (a) RI onset time from TSF and (b) RI duration between RI onset and RI end over the
37-yr analysis period.

NR-TCs, because all TCs had reached TS intensity by thistime. However, the size of TCs in the horizontal direction,
defined as the radius of a 30-kt sustained wind, was significantly different (Table 2). The average radius of a
30-kt sustained wind of RI-TCs was smaller than that of NRTCs. In contrast, the average radius of a 30-kt sustained
wind of RI-TCs was significantly larger at the maturity.
Because RI-TCs tended to develop into intense TCs to beshown later, an increase in the radius of a 30-kt sustained
wind resulted from an increase in the intensity of RI-TCs.
In terms of average intensity, RI-TCs had significantly
lower TC central pressure and higher maximum wind.
To determine the tendency of an intense TC to develop,
we also examined the occurrence of specific classes of
TC intensity, defined using the Saffir–Simpson hurricane
wind scale (Simpson 1974). During the 37-yr analysis
period, 1 category 5 TC [.135 kt (69.5 m s21)], 20 category 4 TCs [114–135 kt (58.6–69.5 m s21)], and 113 category 3 TCs [96–113 kt (49.4–58.1 m s21)] were classed
as major TCs, that is, having a maximum wind speed of
96 kt or more. Among 134 major TCs, 101 RI-TCs weredetected. To compare the distributions more clearly, theoccurrence rates of RI-TCs and NR-TCs were divided
by the number of occurrences for major TCs and weakTCs (TS and category 1 TC). The occurrence rate of RITCs among major TCs (75%) was 3 times larger thanthat of NR-TCs (Fig. 7). Conversely, the occurrence rateof RI-TCs among weak TCs was less than 10%. Thus,
most RI-TCs developed into major TCs, whereas most
NR-TCs remained as weak TCs. These results are consistent with those of a previous study by Kaplan and
DeMaria (2003) over the Atlantic, in which most category 4 or 5 hurricanes were found to undergo RI.

analysis period. RI-TCs most frequently occurred in the
RI zone and southeast of the RI zone, whereas it wasrare for RI-TCs to occur in the northern part of the
WNP and the South China Sea. Table 2 shows the average locations of RI-TCs and NR-TCs at the TSF.
There were significant differences in the average locations at the TSF. RI-TCs occurred on average significantly farther to the east and south than NR-TCs.
Table 2 also shows the direction of TC movements at
the TSF, which are determined by the east–west andnorth–south components of the distances moved between the TSF and 1 day later. NR-TCs tended to bemoving northward at the TSF; this trend was significantly different from that of RI-TCs. On the other hand,the east–west component of the movement between RITCs and NR-TCs at the TSF did not differ significantly.
Table 2 shows the averages of two measures of TC
duration: one is the duration of the development stage
from the TSF to the maturity, and the other is the lifespan from the TSF to the decay. The duration of thedevelopment stages of RI-TCs and NR-TCs differedsignificantly. The mean duration of the development

d. Movement and lifetime of RI-TCs
Figure 8 shows the distributions of occurrence rate of
RI-TC and NR-TC locations at the TSF over the 37-yr

FIG. 6. Locations of the number of RI-TCs at RI onset over the
37-yr analysis period. Box area indicates the RI zone (longitudes of1218–1438E and latitudes of 98–218N).

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FUDEYASU ET AL.

TABLE 2. Statistical summary of characteristics of RI-TCs (RI) and NR-TCs (NR), and their sum (ALL), over the 37-yr analysis period.
Significant differences at the confidence level over 95% in both statistical tests, a one-tailed bootstrap-based test with 10 000 resamples andconventional t test, are indicated in italics. Numbers in parentheses are the difference ratios normalizing each variable by subtracting thesample mean and dividing by the standard deviation.

Time of TSF

One day after time of TSF
Mature time

Decaying time

NumberAvg lat (8N)
Avg lon (8E)
Radius of 30-kt wind(n mi; 1 n mi 5 1.852 km)
Dlon (8)Dlat (8)Duration from TSF (day)Max wind (kt)
Min pressure (hPa)Radius of 30-kt wind (n mi)
Duration from TSF (day)

RI

NR

ALL

201
13.9 (247%)
141.7 (46%)
99.2 (228%)699
16.6 (11%)
134.4 (211%)115.7 (6%)

900
16.0
136.0
112.0

23.1 (227%)
1.3 (230%)
3.6 (42%)96.1 (189%)
932.1 (2151%)
252.1 (34%)
5.5 (103%)22.3 (2%)
1.8 (5%)2.8 (210%)
61.1 (241%)
973.3 (42%)
215.1 (27%)
3.8 (214%)

22.5
1.7
3.0
68.9
964.1
223.4
4.0

stages of RI-TCs was 3.6 days, longer than that of NRTCs (2.8 days). The longer mean duration of the development stages of RI-TCs was partly due to theirtendency to form farther southeastward. The longer
duration of the development stage resulted in a longer
life-span for RI-TCs than for NR-TCs.
Along the trajectory, we examined the number oflandfalls in each country (Japan, China, Vietnam, and
the Philippines) (Fig. 9). TC landfall was defined as theintersection of the TC trajectory with a coastline, as
described by Fudeyasu et al. (2015). In total, 51 RI-TCs
that made landfall in China (including the islands of
Taiwan) were the most frequent, followed by the 48 RITCs in the Philippines, 34 RI-TCs in Japan, and 19 RITCs in Vietnam. The proportion of RI-TCs that madelandfall among the total landfall occurrences for eachcountry is shown as a percentage in Fig. 9. The rates of
RI-TC occurrence in Japan (33%) and the Philippines(31%) were higher than those in China (22%) and
Vietnam (17%).
Table 3 shows characteristics of RI-TCs and NR-TCs
that made landfall in each country, the locations of theTSF, the duration from the TSF to landfall, and the intensity at landfall. There were significant differences in
the average locations of the TSF between RI-TCs and
NR-TCs that made landfall in each country. The average
duration of RI-TCs to make landfall in each country wasapproximately double that of NR-TCs. The averageintensity of RI-TCs at landfall in each country was significantly greater than that of NR-TCs. These landfall
results will be important in disaster prevention planningfor each country.

compare the characteristics of environmental parameters among RI-TC and NR-TC correctly, this study
considered 67 RI-TCs and 157 NR-TCs that were located in the RI zone at the TSF from July to Octoberover the 34 years from 1982 to 2015, the same as theavailable period of both JRA-55 and FORA-WNP30.
Table 4 shows the averaged atmospheric environmental
parameters at the times of the TSF and the maturity, andTable 5 shows the oceanic environmental parameters.
Relative humidity between lower, mid-, and upper
troposphere (RHLO, RHMD, and RHHI, respectively)
at both the TSF and maturity did not differ significantly,
which does not agree with H10. This discrepancy may berelated to the detected TCs located in the RI zone at thee. Environmental parameters around RI-TCs

FIG. 7. Occurrence rates of RI-TCs and NR-TCs divided by the
number of major TCs (category 3–5 TCs) and weak TCs (TS andcategory 1 TC) over the 37-yr analysis period. Filled bars indicate
RI-TCs.

As shown in the previous section, the distributions of
RI-TC and NR-TC locations at the TSF are different. To

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FIG. 8. Locations of occurrence rate of (a) RI-TCs and (b) NR-TCs at the TSF over the 37-yr analysis period. The
region of occurrence rate more than 2% is heavily shaded, the region of 1%–2% are lightly shaded, while the regionof 0.2%–1% are intermediately shaded. Box area indicates the RI zone.

TSF in summer and autumn in the present study. The
vertical wind shears (SHRS, SHRD, USHRS, andUDHRD) of RI-TCs were significantly weaker in RITCs at both the TSF and maturity. The E-CAPE andmaximum wind speeds derived from the MPI theory
were significantly greater in RI-TCs at both the TSF andmaturity. According to MPI theory, large-scale environments associated with RI were more favorable for
TC development.
There were significant differences in oceanic environmental parameters at both the TSF and maturity(Table 5); TCHP, 0–100-m-depth average temperature,and the 268C isotherm depth were higher in RI-TCs.
These results were consistent with those of previous
studies, indicating that higher upper-ocean heat content
yielded stronger TCs (e.g., Hong et al. 2000; Shay et al.
2000; Cione and Uhlhorn 2003; Lin et al. 2005, 2008; Wu
et al. 2007; Wada 2015). It is interesting to note that the
average SST at TSF did not differ significantly between
RI-TCs and NR-TCs. At the maturity, the average SSTof RI-TCs was significantly higher than that of NR-TCs.
The average ocean cooling parameter at TSF did not
differ significantly between RI-TCs and NR-TCs, because the maximum wind speed at the TSF did not differ
between RI-TCs and NR-TCs. At maturity, the ocean
cooling parameter of RI-TCs was significantly smaller
than that of NR-TCs, namely, the small negative effectof TC-induced cooling at the ocean surface in RI-TCs.
The difference in speeds of TC motion between RI-TCs
and NR-TCs was not also significant at the maturity (notshown), suggesting that the small cooling parameter in
RI-TCs at maturity was a result of upper-ocean structure, whereas the size and wind speed of RI-TCs werelarger, which tends to increase the cooling parameter.
Differences in the mean value are also shown in
Tables 2, 4, and 5. To see the relative importance of eachphysical variable, we calculated normalized difference
ratios, by subtracting the sample mean ( p) from eachvariable (e.g., p) and dividing by the standard deviation( r), that is, ( p 2 p)/r. Overall the difference ratios forthe vertical wind shears between RI-TCs and NR-TCs
were larger at the TSF than at the maturity. In contrast,
the difference ratios for the oceanic environmental
parameters—CAPE and MPI—were larger at the maturity than at the TSF.
This study examined how the RI zone was connectedby the physical environmental parameters. On the oceaneast of the Philippines is a broad region of higher SST
and E-CAPE, including the RI zone and outside of the
RI zone (not shown). Figure 10 shows the distribution of
0–100-m-depth averaged temperature and the zonal
component of vertical wind shear between 200 and
850 hPa averaged from July to October. An area of ahigh 0–100-m-depth averaged temperature more than
288C extended eastward up to 1608E from east of thePhilippines along the latitude of 108–208N. The higher
vertical wind shear of more than 15 m s21 extended
westward up to 1408E from the eastern North Pacificalong the latitude of 108N. The region where the zonal

FIG. 9. Number of TCs that made landfall in Japan, China,
Vietnam, and the Philippines over the 37-yr analysis period. Filledbars indicate RI-TCs. Percentage values are RI-TC occurrence
rates divided by the total number of TCs that made landfall in eachcountry.

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FUDEYASU ET AL.

TABLE 3. Statistical summary of characteristics of RI-TCs and NR-TCs that made landfall, by country. Significant differences at theconfidence level over 95% in both statistical tests, a one-tailed bootstrap-based test with 10 000 resamples and conventional t test, areindicated in italics.
Japan

Time of TSF

LandfallAll TCAvg lat (8N)
Avg lon (8E)
Duration from TSF (day)Max wind (kt)
Min pressure (hPa)China

VietnamPhilippines

RI

NR

RI

NR

RI

NR

RI

NR

34
13.6
146.9
8.2
71.4
960.8

69
19.4
136.1
4.5
57.4
975.9

51
15.5
135.6
5.7
61.7
967.0

182
17.0
125.8
3.6
51.4
977.5

19
12.3
135.6
6.5
53.9
975.5

92
14.8
119.0
3.3
47.4
982.8

48
11.2
138.7
3.7
84.3
939.9

109
12.2
133.8
2.6
59.8
972.4

component of weak vertical wind shear overlapped withthe higher 0–100-m-depth averaged temperature east of
the Philippines is consistent with the RI zone.

4. Discussion
The annual variation in RI-TC activity in the WNPover 37 years was investigated in this study. Although we
examined how atmospheric and oceanic environmental
physical parameters using JRA-55 and FORA-WNP30
are related to the annual variation in RI-TC occurrence,
we did not find high correlation between the annual
variation in RI-TC occurrence and environmental parameters (not shown). We consider the uncertainty associated with the atmospheric and oceanic information
derived from JRA-55 and FORA-WNP30 caused bynonphysical trends that result from changes in the observing system (e.g., Parker 2016) and the sparsity ofobservations over the WNP. We need reliable reanalysis
data that include both atmosphere and ocean to evaluate

environmental physical parameters leading to the longterm trends of RI-TCs. However, we focus on clarifying the characteristics of TC or environmental
physical parameters that are favored by the RI events,
and the detailed analysis on the long-term scale tendency of each physical parameter or policies is left for
future works.
A higher (lower) occurrence rate of RI-TC in El Niño
(La Niña) years could be explained by the distribution of
TC locations at the TSF. Previous studies (e.g., Wang
and Chan 2002) have shown a longitudinal shift in themean TC locations at the TSF during ENSO years: in El
Niño (La Niña) years, more TCs tend to form in the east(west) than in the TC formation location by the climatological mean. Chen et al. (1998) showed that the frequency of TC formation during the summer from June
to August in El Niño (La Niña) years increased (decreased) in the southern part of the WNP.
Figure 11 shows the distribution of locations of TCs at
the TSF in El Niño and La Niña years. Locations of

TABLE 4. As in Table 2, but for atmospheric environmental physical parameters around RI-TCs and NR-TCs that are located in the RI
zone at the TSF in summer and autumn from July to October over the 34 years from 1982 to 2015.

TSF time

Mature time

RHLO (%)
RHMD (%)
RHHI (%)
SHRS (m s21)
SHRD (m s21)
USHRS (m s21)
USHRD (m s21)
E-CAPE (J kg21)
MPI max wind (m s21)
RHLO (%)
RHMD (%)
RHHI (%)
SHRS (m s21)
SHRD (m s21)
USHRS (m s21)
USHRD (m s21)
E-CAPE (J kg21)
MPI max wind (m s21)

RI

NR

ALL

90.8 (230%)
81.7 (215%)
54.9 (220%)
2.4 (232%)
5.9 (244%)
2.4 (232%)
5.4 (236%)
15 092.8 (35%)
124.2 (35%)
90.8 (26%)
81.8 (1%)
54.9 (3%)
3.0 (223%)
6.8 (231%)
3.0 (227%)
5.9 (223%)
19 035.3 (93%)
138.5 (101%)

91.0 (9%)
82.0 (6%)
56.0 (8%)
3.1 (12%)8.0 (16%)
3.1 (12%)7.6 (14%)
14 553.5 (215%)
121.8 (215%)
90.8 (1%)
82.0 (25%)
55.4 (21%)
3.7 (9%)8.6 (11%)
3.7 (9%)7.6 (9%)14 013.4 (241%)117.8 (232%)

90.9
81.9
55.7
2.9
7.0
2.9
7.0
14 716.4
122.6
90.8
81.9
55.3
3.5
8.1
3.5
7.1
15 529.9
124.0

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JOURNAL OF CLIMATEVOLUME 31

TABLE 5. As in Table 2, but for oceanic environmental physical parameters.

TSF time

Mature time

SST (8C)
TCHP (kJ cm22)
268C depth (m)0–100-m average T (8C)
Ocean cooling parameter
SST (8C)
TCHP (kJ cm22)
268C depth (m)0–100-m average T (8C)
Ocean cooling parameter

RI-TCs at the TSF in both El Niño and La Niña years
were mainly in the RI zone, as shown in Fig. 8. In La
Niña years, the locations of TCs at the TSF appeared to
the north and west of the RI zone, resulting in the decreases in the occurrence rate of RI-TC. In contrast,
locations of TCs at the TSF in El Niño years extended
east of the RI zone, resulting in the increase in the occurrence rate of RI-TC.
The relationship between the distribution of TC locations at the TSF and the occurrence rate of RI-TCs
could be a possible reason for the trend of TCs thatmake landfall in each country. Figure 12 shows the distribution of TC locations at the TSF stratified by thelandfall occurrences for each country. Locations of TCs
at the TSF that made landfall in Japan and the Philippines were mainly in the RI zone or southeast of the RIzone, whereas the locations of TCs at the TSF that madelandfall in China and Vietnam were partly in the South
China Sea; namely, the trend of occurrence rate of RI-TCs
that made landfall in each country could be explained by
the distribution of TC locations at the TSF.

RI

NR

ALL

29.2 (16%)
96.5 (26%)
93.6 (27%)
28.2 (25%)
1.6 (215%)
28.6 (38%)
59.1 (34%)
68.0 (38%)
26.7 (54%)
4.1 (2160%)

29.1 (27%)
87.5 (213%)
87.7 (213%)
27.8 (212%)
2.0 (6%)28.1 (210%)
45.7 (221%)57.6 (220%)25.7 (215%)
7.5 (5%)

29.2
90.2
89.5
27.9
1.8
28.3
50.5
61.4
26.1
7.2

Fudeyasu et al. (2006) found that TCs that makelandfall on the Korean Peninsula or in Japan in El Niño
years tended to have a longer life-span and greater intensities. They considered that an increase in the numbers of intense TCs that make landfall on the Korean
Peninsula or in Japan in El Niño years could be attributed to an increase in the number of TCs that formed in
the southeastern part of the WNP. Although Fudeyasu
et al. (2006) did not focus on TCs that experience RI,
trends of intense TCs that made landfall on the Korean
Peninsula or in Japan related to ENSO years weresimilar to the statistical characteristics of RI-TCs provided by this study.

5. Conclusions
We conducted a statistical investigation of the characteristics of TCs undergoing RI in the WNP associatedwith environmental parameters that are known to influence RI, using records of 900 TCs that occurred over
the WNP during the 37 years from 1979 to 2015. Among

FIG. 10. Distribution of (a) 0–100-m-depth average temperature and (b) zonal components of vertical wind shear
between 200 and 850 hPa, averaged from July to October over 34 years from 1982 to 2015. Contour intervals are(a) 18C and (b) 5 m s21. Shading in (a) indicates a region larger than 288C. The region with a vertical shear of 10–
15 m s21 in (b) is heavily shaded, while the region less than 10 m s21 is lightly shaded. Box area indicates the
RI zone.

1 NOVEMBER 2018

FUDEYASU ET AL.

8927

FIG. 11. Distribution of TC locations at the TSF and SST anomaly stratified in (a) El Niño and (b) La Niña years
over the 37-yr analysis period. Crosses (closed circles) represent the locations of RI-TCs (NR-TCs) at the TSF. The
distribution of SST anomaly is averaged from July to September over the 37-yr analysis period. Contour interval is
0.38C, and shading indicates areas larger than 08C. Box area indicates the RI zone.

these 900 TCs, 201 RI-TCs met our criteria of a windspeed increase of 30 kt or more in a 24-h period. Our
results, comparing characteristics of RI-TCs and NRTCs, are summarized below.
RI-TCs can potentially occur throughout the year withlow variation in RI-TC occurrence rate among theseasons.
d The annual occurrence rates of RI-TCs are highlyvariable, from about 5% to nearly 50%.
d

The RI is most frequently observed in the elongatedregion around the eastern Philippines (RI zone;
longitudes of 1218–1438E and latitudes of 98–218N),
which is consistent with regions of high 0–100-m-depth
averaged temperature and weak vertical wind shear
averaged from July to October.
d The RI onset tends to occur 0–66 h after the TSF,
with a peak at 12–24 h.
d The RI duration is typically 1–2 days, with a peak at
24 h. RI does not continue longer than 2.5 days.
dFIG. 12. Distribution of TC locations at the TSF stratified by landfalling in (a) Japan, (b) China, (c) Vietnam, and(d) the Philippines. Box area indicates the RI zone.

8928

JOURNAL OF CLIMATEThe average location of RI-TCs at the TSF is farther tothe east and south than that of NR-TCs.
d TCs in El Niño years tend to undergo RI mainly as aresult of the average locations of TCs at the TSF being
farther east of the RI zone, whereas TCs in La Niña
years experience RI less frequently.
d The
rates of RI-TC occurrence increased fromthe 1990s to the late 2000s, with a peak in the late
2010s.
d The average radius of a 30-kt sustained wind of RITCs at the TSF is smaller than that of NR-TCs. In
contrast, the average radius of RI-TCs at maturity islarger because of an increase in the intensity of RITCs.
d The occurrence rates of RI-TCs that make landfall inJapan and the Philippines are higher than those of RITCs in China and Vietnam. The trends in occurrence
rate of RI-TCs that made landfall in each country
could be explained by the distribution of TC locations
at the TSF.
d The development stage and life-span are longer in RITCs than in NR-TCs.
d RI-TCs tend to develop as intense TCs as a result of
their formation in environments favorable for TC
development. Note that with favorable environments
for TC intensification, the RI event does not always occur.
d Vertical wind shear is weaker around RI-TCs than
NR-TCs at the TSF and maturity.
d Average values of TCHP, 0–100-m-depth averagetemperature, and depth of the 268C isotherm of RITCs are significantly higher than those of NR-TCs atboth the TSF and maturity.
d The
average SST and ocean cooling parameters
between RI-TCs and NR-TCs at the TSF do not differ
significantly, but at the maturity, SST around RI-TCs
is higher and the ocean cooling parameter is smaller
than that of NR-TCs.
d The difference ratios for the vertical wind shear
between RI-TCs and NR-TCs are larger at the TSF
than at the maturity. In contrast, the difference ratios
for the oceanic environmental parameters, CAPE and
MPI, are larger at the maturity than at the TSF.
d

Studies on the relationship between large-scale environmental parameters that influence RI and annual variability in RI-TC occurrence are needed. Further, the exact
reasons why the rates of RI-TC occurrence increased fromthe 1990s to the late 2000s remain unclear. The statisticalcharacteristics of RI-TCs and large-scale environmental
factors, which we investigated in this study, will be usefulfor climate and TC intensity prediction. In particular,
characteristics describing the landfall of RI-TCs in eachcountry will be important for disaster prevention.

VOLUME 31

Acknowledgments. The authors thank Dr. A. Wada
for the helpful comments and support of data analysis.
This study utilized the dataset of JRA-55 provided by
the Japan Meteorological Agency (JMA). Also thisstudy utilized the dataset of FORA-WNP30, which was
kindly provided by the Japan Agency for Marine-Earth
Science and Technology (JAMSTEC) and the Meteorological Research Institute of JMA (JMA/MRI). This work
is supported by MEXT KAKENHI Grants 17H02956,
16K13884, and Kyoto University Disaster Prevention Research Institute’s collaborative research program 29G-05.

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