Mapping of Topographic Effects on Maximum Sustained Surface wind Speeds in Landfalling Hurricanes
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Reprint 1280
Change in Destructiveness of Landfalling Tropical Cyclones
over China in Recent Decades
Richard C.Y. LI 1, Wen ZHOU 1,
C.M. SHUN & Tsz Cheung LEE
Journal of Climate, vol. 30, p.3367-3379
2017
1 Guy Carpenter Asia-Pacific Climate Impact Center, School of Energy and
Environment, City University of Hong Kong, Hong Kong, China
Change in Destructiveness of Landfalling Tropical Cyclones overChina in Recent Decades
RICHARD C. Y. LI AND WEN ZHOU
Guy Carpenter Asia-Pacific Climate Impact Center, School of Energy and Environment, City University of
Hong Kong, Hong Kong, China
C. M. SHUN AND TSZ CHEUNG LEE
Hong Kong Observatory, Hong Kong, China
(Manuscript received 11 April 2016, in final form 7 January 2017)
ABSTRACT
This study investigates changes in the destructiveness of landfalling tropical cyclones (TCs) over China
during 1975–2014. Using four different TC datasets, it is found that TCs making landfall over east China
(TCEC) have tended to be more destructive in recent decades, with a significant increase in the power dis-
sipation index (PDI) after landfall. Both time series analysis and diagnostic analysis reveal that such an
increase in the PDI of TCEC is associated with concomitant enhancement in landfall frequency as well as
landfall intensity over east China. In contrast, changes in the PDI of TCs making landfall over south China
(TCSC) are less apparent. Examination of different TC-related parameters shows no obvious changes in terms
of landfall frequency, duration, and maximum intensity of TCSC. Diagnostic analysis further suggests that the
reduction in TC occurrence over south China offsets considerably the positive effects of the intensity and the
nonlinear term.
Further examination of the environmental parameters reveals significant changes in the large-scale steering
flow in recent decades, which is characterized by a prominent cyclonic circulation centered over southeast
China. The southeasterly flows on the eastern flank of the cyclonic circulation tend to favor subsequent
landfall of TCs over east China, resulting in an increase in landfall frequency, which contributes in part to the
enhanced PDI of TCs over this region. Meanwhile, the slowing down of the mean translation speed of TCEC
and the weakening of vertical wind shear coupled with warmer SSTs in the WNP tend to favor the in-
tensification of TCEC, leading to an increase in intensity and hence the PDI of TCs over east China.
1. Introduction
China, one of the most densely populated countries in
the world, is adversely affected by tropical cyclones
(TCs). About seven TCs make landfall in China every
year, inflicting huge losses of life and property (Zhang
et al. 2009; Lu and Zhao 2013). During the period 1983–
2006, an average of 472 people were killed each year by
the landfalling TCs, with the greatest casualties occur-
ring in coastal cities in Zhejiang, Fujian, andGuangdong
Provinces (Zhang et al. 2009). Super Typhoon Fred,
landfalling over Zhejiang inAugust 1994; Super Typhoon
Herb, striking Fujian in August 1996; and Tropical Storm
Bilis, invading Fujian in July 2006, are some of the
deadliest TCs that have affected China in recent de-
cades (Zhang et al. 2009). More recently, Super Ty-
phoon Rammasun also wreaked havoc in Hainan
Island, western Guangdong, Guangxi, and Yunnan in
July 2014, resulting in at least 30 deaths and over 26.5
billion renminbi (RMB) direct economic loss (HKO
2015). Throughout the world, TC-induced socioeconomic
losses have also shown a remarkable increase over the
last few decades as a result of population growth, ur-
banization, and climate change (Pielke et al. 2008;
Zhang et al. 2009; Xiao and Xiao 2010). Understanding
changes in the characteristics of landfalling TCs thus
becomes essential for climate change adaptation and
disaster mitigation.
The relationship between climate change and TC ac-
tivity has long been a topic of active research and de-
bate. Based on the power dissipation index (PDI),Corresponding author e-mail: Dr. Wen Zhou, wenzhou@cityu.
edu.hk
1 MAY 2017 L I E T AL . 3367
DOI: 10.1175/JCLI-D-16-0258.1
� 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS CopyrightPolicy (www.ametsoc.org/PUBSReuseLicenses).
several studies have reported a significant increase in the
destructive power of TCs in the western North Pacific
(WNP) and North Atlantic since the mid-1970s
(Emanuel 2005; Webster et al. 2005), which they ar-
gued were induced by anthropogenic warming. By using
the anthropogenic climate change index (ACCI),
Holland and Bruyère (2014) investigated the potential
global warming contribution to global tropical cyclone
activity from 1975 to 2010 and, after accounting for
analysis and observing system changes, found sub-
stantial relationships between ACCI and the observed
increase in the proportion of very intense TCs (Saffir–
Simpson category 4 and 5) in all ocean basins. On the
other hand, other research groups have indicated that
there are still large uncertainties in detecting the human
influence on TC activity in the WNP basin due to the
considerable interdecadal natural variability and the
issues of homogeneity and consistency of TC records
kept by different warning centers (Landsea 2005; Chan
2006, 2008). For future projections of TC activities in
WNP, climate models mostly suggest decreases in TC
frequency but increases in TC intensity and related
precipitation rates in the twenty-first century (e.g., Ying
et al. 2012; Wu et al. 2014; Tsuboki et al. 2015; Knutson
et al. 2015; Walsh et al. 2016). Most of the previous
studies have focused primarily on basinwide TCs; of
these, relatively few have tried to investigate changes in
the properties of TCs after landfall. An increase in TC
activity after landfall is particularly hazardous since
most TC-related casualties occur during this time. A
recent study by Chan andXu (2009) analyzed the annual
frequency of landfalling TCs over East Asia during
1945–2004 but found no obvious trends. Park et al.
(2011), on the other hand, showed that the PDI, as well
as the rainfall of landfalling TCs, has increased signifi-
cantly in recent decades over Japan and the Korean
peninsula. Park et al. (2014) further noted a shift in the
location of maximum intensity of TCs on the East Asian
coastline during 1977–2011 and the potentially growing
threat of TCs over East Asia. Tu et al. (2009) also re-
ported that an abrupt shift in the TC activities in the
vicinity of Taiwan occurred in 2000, mainly due to a
northward shift of the typhoon track over the WNP–
East Asian region. Owing to the vast socioeconomic
influences of landfalling TCs and their uncertain
variation, a comprehensive study is essential to in-
vestigate changes in the destructiveness of landfalling
TCs over China, a topic that has not been examined in
detail in previous studies.
The rest of this paper is organized as follows: section 2
introduces the data and methodology used in this study,
and the climatology and distributions of landfalling TCs
over China are presented in section 3. Section 4
examines the changes in destructiveness of these land-
falling TCs, and section 5 investigates the possible fac-
tors contributing to such changes. Finally, section 6
discusses and summarizes the results.
2. Data and methodology
a. Data
The TC dataset acquired from the Joint Typhoon
Warning Center (JTWC; https://metoc.ndbc.noaa.gov/
web/guest/jtwc/best_tracks/western-pacific) at 6-h in-
tervals is primarily used for investigation in this study
unless otherwise stated. Other best-track datasets from
the Hong Kong Observatory (HKO), the Regional
Specialized Meteorological Center of the Japan Mete-
orological Agency (JMA), and the China Meteorologi-
cal Administration–Shanghai Typhoon Institute (CMA)
were also used to validate our results. Since the maxi-
mum sustained wind speed is recorded differently for
different TC datasets (the JTWC and CMA datasets are
based on 1-min and 2-min sustained wind speed, while
both the HKO and JMA use 10-min sustained wind
speed), an adjustment factor of 1.14 (1.01) was applied
to the HKO and JMA (CMA) datasets for 10- to 1-min
(2- to 1-min) conversion (Knapp et al. 2010; Park et al.
2011; Barcikowska et al. 2012). It should be noted that
using the 10-min sustained wind speed is the World
Meteorological Organization (WMO) recommended
practice for depicting tropical cyclone intensity. The use
of 1-min mean wind as the basis in computing the PDI in
this study is only for the sake of aligning with the original
definition of PDI by Emanuel (2005). It does not have
any implications with regard to the wind averaging pe-
riod practice as recommended by the WMO. We do not
expect that the use of the 1-min wind versus 10-min
mean wind in this study will have significant impact
on the observed trend and the salient findings, as the
conversions between 1-min and 10-min mean winds
involve a linear factor (Harper et al. 2009). To ensure
data reliability, the analysis period of the present study is
restricted primarily to 1975–2014, which roughly corre-
sponds to the period when routine satellite data are
available (Park et al. 2011). Monthly atmospheric data
for the same period were archived from the National
Centers for Environmental Prediction (NCEP)–National
Center for Atmospheric Research (NCAR) reanalysis
(Kalnay et al. 1996), while the monthly National Oceanic
and Atmospheric Administration 28 3 28 Extended Re-
constructed Sea Surface Temperature (ERSST) version 4
data were obtained from the website (http://www.esrl.
noaa.gov/psd/) of NOAA. A landfalling TC in this study
refers to any TC that crosses the coastline of China at
3368 JOURNAL OF CL IMATE VOLUME 30
least once during its lifetime. Although we consider
primarily all the TCs making landfall over China in the
present study, it is worth noting that the results below
will not be affected after excluding those weak tropical
depressions with maximum sustained wind speed less
than 34 kt.
b. Statistical analysis of the potential destructivenessof TCs
One common measure of the potential destructive-
ness of TCs is the PDI, which is defined as the sum of the
cubes of the maximum sustained wind speed over the
entire lifetime of a TC (Emanuel 2005). Since the main
focus of this study is the changes in TC destructiveness
after landfall, the PDI is derived specifically based on
the TCs’ maximum sustained wind speed after landfall.
The annual PDI is then calculated by summing the in-
dividual PDIs over a particular year. Calculated this
way, the annual PDI thus takes into account the fre-
quency, intensity, and duration of landfalling TCs and
can be used to represent the activity and destructive
potential of these TCs.
To further confirm the changes in the annual PDI and
to quantitatively assess the relative contributions of
different incorporated parameters (TC frequency, TC
intensity, and the nonlinearity of the previous two
factors) to the overall PDI changes, an alternative di-
agnostic analysis is also carried out. In this method, the
PDI is recalculated for each 58 3 58 grid cell such that its
value can be expressed in terms of the occurrence fre-
quency (F) and the maximum sustained wind speed (y)
of the TCs in that particular grid. The climatological
PDI (denoted by overbars) for each 58 3 58 grid cell A
can thus be written as
PDI(A)5F(A)3 y3(A) , (1)
where F is the TCs’ occurrence frequency, and y is the
TCs’ maximum sustained wind speed in grid cell A. The
PDI anomaly (denoted by prime symbols), with respect
to its climatology, can then be evaluated as
PDI0(A)5PDI(A)2PDI(A)
5F 0(A)y3(A)1F(A)y30(A)1F 0(A)y3
0(A) .
(2)
Equation (2) consists of three terms, which illustrate the
different contributions of these factors to the overall
changes in PDI. The first term F 0(A)y3(A) reveals the
contribution from anomalous TC occurrence frequency
to the overall PDI changes under the condition that the
maximum sustained wind speed is unchanged. The
FIG. 1. (a) The locations (indicated by the triangles) and the mean frequency (indicated by the contours) of TCs
making landfall in China during 1975–2014, and the associated tracks of (b) TCEC and (c) TCSC. The bold curves in
(b) and (c) denote the mean regression trajectories of TCEC and TCSC.
1 MAY 2017 L I E T AL . 3369
second term F(A)y30(A) represents the contribution
from anomalous maximum sustained wind speed, while
the third term F 0(A)y30(A) is the nonlinear term associ-
ated with changes in both the frequency and maximum
sustained wind. Through such a decomposition, changes
in PDI can be quantitatively decomposed and assessed
in terms of the three factors, namely the frequency effect
(first term), the intensity effect (second term), and the
nonlinear effect (third term).
3. Distribution of landfalling TCs over China
In this section, we will first take a look at the climatic
characteristics of landfalling TCs in China. Figure 1
shows the distribution of landfalling TCs in China during
1975–2014. Following previous studies (Kim et al. 2008;
Li and Zhou 2013), the large territory of China is sub-
divided into southChina (SC) and east China (EC) by an
artificial boundary line along 258N. A total of 211 TCs
made landfall in China during 1975–2014. Of these,
150 TCs (71%) made landfall over SC, while the re-
maining 61 TCs (29%) struck the EC coast. Substantial
differences can also be found in the prevailing tracks of
these two groups of TCs. As shown in Figs. 1b and 1c,
TCs making landfall over SC (TCSC) take mainly a
northwestward track, whereas TCs landfalling over
EC (TCEC) are associated primarily with a recurving
track. Figure 2 further shows the monthly variation in
landfalling TCs in China. On average, the landfalling
frequency of TCs is the highest during June–October,
accounting for 97%of the annual total. Therefore, in the
following, the PDI associated with TCEC and TCSC
during the peak season (June–October) will be in-
vestigated to infer any possible changes in recent
decades.
4. Changes in destructiveness of landfalling TCs inChina
a. East China
Figure 3a first shows the variation in the PDI associ-
ated with TCEC during 1975–2014. Apart from clear
interannual variation, a marked positive trend can be
observed in the PDI time series, with an increase of
1.91 3 105 kt3 decade21, which is significant at 95%
confidence based on the Student’s t test. In other words,
in recent decades, TCs have tended to be more active
and destructive after making landfall over EC. A closer
look at the TC-related parameters suggests that both the
landfall frequency and the mean maximum TC intensity
show noticeable increases during 1975–2014, whereas
the mean duration after landfall reveals no obvious
change (Figs. 3b–d and Table 1). This suggests that the
increase in the PDI of TCEC after landfall might be
closely related to the concomitant enhancement in
FIG. 2. Monthly-averaged frequency of (a) TCEC, (b) TCSC, and (c) their sum during 1975–2014.
3370 JOURNAL OF CL IMATE VOLUME 30
landfall frequency as well as the mean maximum in-
tensity in recent decades.
To further confirm the changes in various TC-
related parameters, the results here have also been
tested and verified using different TC datasets, as
depicted in Fig. 4 and Table 1. Similar to the JTWC,
the HKO, JMA, and CMA datasets depict a signifi-
cant increasing trend in the PDI of TCEC, with a value
of 2.66 3 105 kt3 decade21, 1.97 3 105 kt3 decade21,
and 1.44 3 105 kt3 decade21, respectively. The con-
sistency among different TC datasets suggests that the
observed increase in the PDI of TCEC is robust and
detectable. As for the landfall frequency, a prominent
increase can be observed in both the HKO and JMA
datasets, which is consistent with the results of JTWC.
Meanwhile, all four agencies consistently depict a
marked increase in mean maximum intensity after
landfall, while revealing insignificant trends in the
mean duration of TCEC. Comparisons between dif-
ferent TC datasets similarly reveal a positive trend in
the potential destructiveness of TCEC, which aligns
with an associated increase in landfall frequency and
landfall intensity.
To quantitatively assess the factors responsible for
the overall increase in the PDI over EC, an alternative
diagnostic analysis is also carried out by decomposing
FIG. 3. Variations of (a) PDI after landfall (105 kt3), (b) landfall frequency (number), (c) mean duration
after landfall (h), and (d) mean maximum intensity after landfall (kt) of TCEC during 1975–2014. The
corresponding 40-yr linear trends are indicated by the dashed lines. (e) Associated tracks and landfall
locations.
1 MAY 2017 L I E T AL . 3371
the PDI in each 58 3 58 grid into frequency, intensity,
and nonlinear terms based on Eq. (2). Figure 5a shows
the linear trend of the PDI calculated in each 58 3 58grid for TCEC during 1975–2014. A pronounced posi-
tive trend in the PDI can be found in areas extending
from the ocean to the coastal region of EC, suggesting
an increase in destructiveness of TCs over EC. Such an
increase in the PDI of TCEC can be attributed primarily
to the positive frequency effect over EC, accounting for
43% of the local positive trend in the PDI (Figs. 5b,e).
The positive intensity effect ranks second (41%) and
also contributes considerably to the overall positive
trend in the PDI over EC (Figs. 5c,e). The nonlinear
term, on the other hand, is relatively small and plays
only amarginal role compared with the other two terms
(Figs. 5d,e). The results here further indicate that TCEC
has tended to be more destructive in recent decades,
which is a consequence of increases in frequency as well
as intensity over EC.
b. South China
Compared with EC, changes in the PDI associated
with TCSC appear to be less pronounced. The time
series of the PDI reveals an insignificant trend of
1.65 3 105 kt3 decade21 during 1975–2014 (Fig. 6 and
Table 2). Examination of different TC-related param-
eters also shows no obvious change in terms of landfall
frequency, duration, or maximum intensity of TCSC
(Fig. 6 and Table 2). It should be noted that such results
are still valid even if different TC datasets are used
FIG. 4. Variations and linear trends of (a) PDI after landfall (105 kt3), (b) landfall frequency (number), (c) mean
duration after landfall (h), and (d) mean maximum intensity after landfall (kt) of TCEC based on the datasets of
JTWC, HKO, and JMA during 1975–2014.
TABLE 1. The 40-yr linear trends of the PDI after landfall, landfall frequency, duration after landfall, andmeanmaximum intensity after
landfall of TCEC during 1975–2014. Trends that are statistically significant at 95% and 90% confidence are denoted by two asterisks (**)
and one asterisk (*), respectively.
Trends JTWC HKO JMA CMA
PDI after landfall (105 kt3 decade21) 1.91** 2.66** 1.97** 1.44*
Landfall frequency (no. per decade) 0.30* 0.28* 0.30* 0.23
Duration after landfall (h decade21) 0.52 2.72 2.40 0.77
Mean maximum intensity after landfall (kt decade21) 9.92** 8.62** 9.94** 3.88*
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(Fig. 7 and Table 2). Consistent with the results using
JTWCdatasets, changes in the PDI and other TC-related
parameters are not evident for the HKO, JMA, or CMA
datasets. By decomposing the PDI in each 58 3 58 gridinto frequency, intensity, and nonlinear terms, it is simi-
larly noted that changes in the PDI over SC are not sig-
nificant. The reduction in TC occurrence over SC
contributes negatively to the overall PDI increase in SC
and offsets considerably the positive effects of the in-
tensity and the nonlinear term (Fig. 8). The results here
suggest that changes in the destructiveness of TCSC are
less apparent than those of TCEC.
5. Possible factors contributing to the enhancedPDI of TCs over east China
The previous section has identified an evident in-
creasing trend in the PDI of TCEC, which is associated
with enhanced landfall frequency as well as landfall in-
tensity in recent decades. In this section, we identify and
discuss several factors that may be closely related to the
PDI changes of TCEC in recent decades.
a. Changes in environmental steering flow
As suggested by previous studies (Gray 1979; Chan
2005), variation in TC tracks and landfall positions is
FIG. 5. Linear trends of (a) PDI (105 kt3 decade21) for TCEC and the contribution of the (b) frequency effect,
(c) intensity effect, and (d) nonlinear effect to the PDI trend during 1975–2014. Regions with trends that are
significant at 90% confidence are shaded by dots. (e) The associated percentage contributions of each of the term to
the overall trend in PDI over EC (as indicated by the rectangles).
1 MAY 2017 L I E T AL . 3373
governed predominantly by changes in the environ-
mental steering flows. Figure 9a shows the 40-yr lin-
ear trend of the steering flow (i.e., wind averaged over
850 to 300 hPa) during 1975–2014. The linear trend is
characterized by a prominent cyclonic circulation
centered over southeast China. The southeasterly
flows at the eastern flank of the cyclonic circulation
tend to favor subsequent landfall of TCs over EC,
FIG. 6. Variations of (a) PDI after landfall (105 kt3), (b) landfall frequency (number), (c) mean duration
after landfall (h), and (d) mean maximum intensity after landfall (kt) of TCSC during 1975–2014. The
corresponding 40-yr linear trends are indicated by the dashed lines. (e) Associated tracks and landfall
locations.
TABLE 2. As in Table 1, except for TCSC.
Trends JTWC HKO JMA CMA
PDI after landfall (105 kt3 decade21) 1.65 20.57 0.63 21.26
Landfall frequency (no. per decade) 20.01 20.02 0.27 20.32
Duration after landfall (h decade21) 20.44 0.58 0.92 20.32
Mean maximum intensity after landfall (kt decade21) 0.02 0.45 3.02 1.83
3374 JOURNAL OF CL IMATE VOLUME 30
while the westerly flows at the southern flank tend to
suppress the number of TCs landfalling over SC.
Such a change in the steering flow is one possible factor
leading to the recent increase in landfall frequency over
EC, contributing in part to the enhanced PDI of TCs
over this region. The prevailing track shift due to cy-
clonic circulation anomaly centered over southeast
China was also reported in the studies by Wu et al.
(2005), Lee et al. (2012), and Zhao and Wu (2014).
Based on numerical model results of global warming
experiments, Wu and Wang (2004) suggested that the
warming trend of sea surface temperature would cause
the shift of prevailing TC tracks. Moreover, by using a
singular value decomposition (SVD) analysis and
IPCC AR4 historical forcing runs, Wang et al. (2011)
suggested that the observed shift of TC tracks was
linked to the leading SVD mode of global sea surface
temperature warming and the associated changes in
large-scale steering flows. However, since there are
considerable interannual and interdecadal variations in
the TC tracks in the WNP (Liu and Chan 2008; Choi
et al. 2010), further observations and research will still
be required to understand the influence and contribution
of natural variability and anthropogenic warming on the
TC track changes in the WNP.
b. Weakened vertical wind shear over EC andbasinwide SST warming in the WNP
On the other hand, the increasing intensity of TCEC
might be related to a remarkable reduction in vertical
wind shear over EC (Fig. 9b). The weakened wind shear
helps maintain TC structure, sustains TC intensity, and
inhibits extratropical transition of TCs (Gray 1968; Baik
and Paek 2001; Chan 2008). This was also identified by
Park et al. (2011), who revealed that the weakened wind
shear over this region as a result of the weakening of the
East Asian jet has also contributed to stronger land-
falling TCs over the Korean peninsula and Japan in re-
cent decades. Apart from the favorable dynamic factor
of weakened vertical wind shear, it is also noted that the
SST in the WNP has revealed a significant warming
trend in the recent decades (Fig. 9c) accompanied by
weak cooling in the central Pacific. Such warming in SST
is particularly evident over the northern part of the
WNP and is consistent with that found in the previous
studies (Park et al. 2013, 2014). The basinwide SST
warming in the WNP also provides favorable thermo-
dynamic background for the intensification of TCs in the
WNP. As pointed out previously by Park et al. (2014),
such increasing zonal SST gradient over the tropical
FIG. 7. Variations and linear trends of (a) PDI after landfall (105 kt3), (b) landfall frequency (number), (c) mean
duration after landfall (h), and (d) mean maximum intensity after landfall (kt) of TCSC based on the datasets of
JTWC, HKO, and JMA during 1975–2014.
1 MAY 2017 L I E T AL . 3375
Pacific is also closely linked to the strengthened Walker
circulation, which results in strengthened cyclonic flows
and weakened vertical wind shear along the East Asian
coastline during the recent decades.
c. Reduction in mean translation speed
Apart from the weakened wind shear and the
warmer SST, it is also worth noting that there is a sig-
nificant decreasing trend in the mean translation speed
of TCEC over the open ocean before landfall, while
changes in the mean translation speed of TCSC are less
apparent (Fig. 10). With favorable background of in-
creasing SST (Fig. 9c) and deepening of the 268C iso-
therm across the WNP in recent decades (Park et al.
2013), the slowing down of the mean translation speed
allows TCEC to stay longer over the ocean with warmer
SST and deepened warm mixed layer and favors the
intensification of TCEC, which might also help explain
the increase in TC landfall intensity over EC. Yet the
exact cause of this slowing down of the mean translation
FIG. 8. Linear trends of (a) PDI (105 kt3 decade21) for TCSC and the contribution of the (b) frequency effect,
(c) intensity effect, and (d) nonlinear effect to the PDI trend during 1975–2014. Regions with trends that are
significant at 90% confidence are shaded by dots. (e) The associated percentage contributions of each of the term to
the overall trend in PDI over SC (as indicated by the rectangles).
3376 JOURNAL OF CL IMATE VOLUME 30
speed of TCEC is unknown at present and deserves
further study.
6. Discussion and summary
This study investigates changes in the destructiveness
of landfalling TCs over China during 1975–2014. Using
four different TC datasets, it is found that TCEC has
tended to be more destructive in recent decades, with a
significant increase in PDI after making landfall over
EC. Both time series analysis and diagnostic analysis
suggest that this increase in the PDI of TCEC can be
attributed to the concomitant enhancement in landfall
frequency as well as landfall intensity over EC. In con-
trast, changes in the PDI of TCSC are less apparent.
Examination of different TC-related parameters shows
no obvious changes in terms of landfall frequency, du-
ration, or maximum intensity of TCSC. Diagnostic
analysis further suggests that the reduction in TC oc-
currence over SC offsets considerably the positive ef-
fects of the intensity and the nonlinear term.
Examination of large-scale environmental parameters
reveals significant changes in the environmental steering
flow in recent decades, which is characterized by a
FIG. 9. Linear trends of (a) steering flow (ms21 yr21), (b) vertical wind shear (m s21 yr21), and (c) SST (8Cdecade21)
during June–October 1975–2014. Regions with trends that are significant at 90% confidence are shaded by dots.
FIG. 10. Linear trends of mean translation speed (km h21 yr21) of (a) TCEC and (b) TCSC during 1975–2014.
Regions with trends that are significant at 90% confidence are shaded by dots.
1 MAY 2017 L I E T AL . 3377
prominent cyclonic circulation centered over southeast
China. The southeasterly flows on the eastern flank of
the cyclonic circulation tend to favor subsequent landfall
of TCs over EC, resulting in an increase in landfall fre-
quency, which contributes in part to the enhanced PDI
of TCs over this region. Meanwhile, the slowing down of
the mean translation speed of TCEC and the weakening
of vertical wind shear coupled with warmer SST in the
WNP tend to favor the intensification of TCEC, leading
to an increase in intensity and hence the PDI of TCs over
EC.Wu et al. (2014) found the prevailing TC tracks have
shifted westward significantly in recent decades, which
leads to growing TC influence over east China, while
Park et al. (2013) and Park et al. (2014) have similarly
identified a strengthening in TC intensity in southern
Japan and northeast Asia, which they attributed to the
changes in intensification rate and genesis frequency
over these regions. Through a new approach of di-
agnostic analysis of the PDI, the results of the present
study further substantiate and extend the results of these
previous studies by quantitatively assess the relative
contributions of different factors (TC frequency, TC
intensity, and the nonlinearity of these two factors) to
the overall PDI changes of landfalling TCs over EC and
SC, which helps further enhance our understanding on
the changes in TC destructiveness by spotting out the
key factors contributing to the overall PDI changes in
recent decades.
Overall, this study has highlighted a potential in-
crease in the destructiveness of TCs making landfall
over EC, which is coincident with the corresponding
changes in large-scale environmental factors in recent
decades. It should be noted that although PDI is a
widely adopted parameter for assessing the potential
destructiveness of a storm, it may not fully reflect all
hazardous impacts of TCs, including torrential rain and
storm surge induced by landfalling TCs. Given the
significant socioeconomic impacts of landfalling TCs,
follow-up studies will still be necessary to keep in view
the changes in these TCs and to further explore the
underlying factors and mechanisms by means of nu-
merical experiments, in particular on the connection
between global warming and the shift in the prevailing
track of TCs in the WNP. Moreover, against the
background of global warming and sea level rise, the
risk of extreme weather and storm surge induced by
landfalling TCs to coastal cities should be further in-
vestigated to assist in developing relevant disaster
mitigation and adaptation measures.
Acknowledgments. This research is supported by
National Natural Science Foundation of China (NSFC
41675062).
REFERENCES
Baik, J.-J., and J.-S. Paek, 2001: Relationship between vertical wind
shear and typhoon intensity change, and development of
three-predictor intensity prediction model. J. Meteor. Soc.
Japan, 79, 695–700, doi:10.2151/jmsj.79.695.
Barcikowska, M., F. Feser, and H. von Storch, 2012: Usability
of best track data in climate statistics in the western North
Pacific. Mon. Wea. Rev., 140, 2818–2830, doi:10.1175/
MWR-D-11-00175.1.
Chan, J. C. L., 2005: The physics of tropical cyclone mo-
tion. Annu. Rev. Fluid Mech., 37, 99–128, doi:10.1146/
annurev.fluid.37.061903.175702.
——, 2006: Comment on ‘‘Changes in tropical cyclone number,
duration, and intensity in a warming environment.’’ Science,
311, 1713, doi:10.1126/science.1121522.——, 2008: Decadal variations of intense typhoon occurrence in
the western North Pacific. Proc. Roy. Soc., 464, 249–272,
10.1098/rspa.2007.0183.
——, andM. Xu, 2009: Inter-annual and inter-decadal variations of
landfalling tropical cyclones in East Asia. Part I: Time series
analysis. Int. J. Climatol., 29, 1285–1293, doi:10.1002/joc.1782.
Choi, K.-S., B. J. Kim, D. W. Kim, and H.-R. Byun, 2010: Inter-
decadal variation of tropical cyclone making landfall over the
Korean Peninsula. Int. J. Climatol., 30, 1472–1483, doi:10.1002/
joc.1986.
Emanuel, K. A., 2005: Increasing destructiveness of tropical cy-
clones over the past 30 years. Nature, 436, 686–688,
doi:10.1038/nature03906.
Gray, W. M., 1968: Global view of the origin of tropical distur-
bances and storms. Mon. Wea. Rev., 96, 669–700, doi:10.1175/
1520-0493(1968)096,0669:GVOTOO.2.0.CO;2.
——, 1979: Hurricanes: Their formation, structure and likely role
in the tropical circulation. Meteorology over the Tropical
Oceans, D. B. Shaw, Ed., Royal Meteorological Society,
155–218.
Harper, B. A., J. D. Kepert, and J. D. Ginger, 2009: Guidelines for
converting between various wind averaging periods in tropical
cyclone conditions. World Meteorological Organization Rep.
TCM-VI/Doc. 2.3, 62 pp.
HKO, 2015: Tropical cyclones in 2014. Hong Kong Observatory
Rep., 120 pp.
Holland, G., and C. L. Bruyère, 2014: Recent intense hurricane
response to global climate change. Climate Dyn., 42, 617–627,
doi:10.1007/s00382-013-1713-0.
Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Re-
analysis Project. Bull. Amer. Meteor. Soc., 77, 437–471,
doi:10.1175/1520-0477(1996)077,0437:TNYRP.2.0.CO;2.
Kim, J., C. Ho, H. Kim, C. Sui, and S. K. Park, 2008: Systematic
variation of summertime tropical cyclone activity in the
western North Pacific in relation to the Madden–Julian oscil-
lation. J. Climate, 21, 1171–1191, doi:10.1175/2007JCLI1493.1.
Knapp, K.R.,M. C. Kruk,D.H. Levinson, H. J. Diamond, andC. J.
Neumann, 2010: The International Best Track Archive for
Climate Stewardship (IBTrACS): Unifying tropical cyclone
data. Bull. Amer. Meteor. Soc., 91, 363–376, doi:10.1175/
2009BAMS2755.1.
Knutson, T. R., J. J. Sirutis, M. Zhao, R. E. Tuleya, M. Bender,
G. A. Vecchi, G. Villarini, and D. Chavas, 2015: Global
projections of intense tropical cyclone activity for the late
twenty-first century from dynamical downscaling of
CMIP5/RCP4.5 scenarios. J.Climate, 28, 7203–7224, doi:10.1175/
JCLI-D-15-0129.1.
3378 JOURNAL OF CL IMATE VOLUME 30
Landsea, C.W., 2005: Hurricanes and global warming.Nature, 438,
E11–E12, doi:10.1038/nature04477.
Lee, T.-C., Y.-Y. Leung, M.-H. Kok, and H.-S. Chan, 2012: The
long term variations of tropical cyclone activity in the South
China Sea and the vicinity of Hong Kong. Trop. Cyclone Res.
Rev., 1, 277–292, doi:10.6057/2012TCRR02.01.
Li, R. C. Y., and W. Zhou, 2013: Modulation of western North
Pacific tropical cyclone activities by the ISO. Part II: Tracks
and landfalls. J. Climate, 26, 2919–2930, doi:10.1175/
JCLI-D-12-00211.1.
Liu, K. S., and J. C. L. Chan, 2008: Interdecadal variability of
western North Pacific tropical cyclone tracks. J. Climate, 21,4464–4476, doi:10.1175/2008JCLI2207.1.
Lu,X., andB. Zhao, 2013:Analysis of the climatic characteristics of
landing tropical cyclones in East China. J. Trop. Meteor., 19,145–153.
Park, D.-S. R., C.-H. Ho, J.-H. Kim, and H.-S. Kim, 2011: Strong
landfall typhoons in Korea and Japan in a recent decade.
J. Geophys. Res., 116, D07105, doi:10.1029/2010JD014801.
——, ——, ——, and ——, 2013: Spatially inhomogeneous trends
of tropical cyclone intensity over the western North Pacific
for 1977–2010. J. Climate, 26, 5088–5101, doi:10.1175/
JCLI-D-12-00386.1.
——, ——, and ——, 2014: Growing threat of intense tropical cy-
clones to East Asia over the period 1977–2010. Environ. Res.
Lett., 9, 014008, doi:10.1088/1748-9326/9/1/014008.Pielke, R. A., Jr., J. Gratz, C. W. Landsea, D. Collins, M. A.
Saunders, and R. Musulin, 2008: Normalized hurricane dam-
age in the United States: 1900–2005. Nat. Hazards Rev., 9,
29–42, doi:10.1061/(ASCE)1527-6988(2008)9:1(29).
Tsuboki, K., M. K. Yoshioka, T. Shinoda, M. Kato, S. Kanada, and
A. Kitoh, 2015: Future increase of supertyphoon intensity
associated with climate change. Geophys. Res. Lett., 42, 646–
652, doi:10.1002/2014GL061793.
Tu, J.-Y., C. Chou, and P.-S. Chu, 2009: The abrupt shift of typhoon
activity in the vicinity of Taiwan and its association with
western North Pacific–East Asian climate change. J. Climate,
22, 3617–3628, doi:10.1175/2009JCLI2411.1.
Walsh, K. J. E., and Coauthors, 2016: Tropical cyclones and climate
change. Wiley Interdiscip. Rev.: Climate Change, 7, 65–89,doi:10.1002/wcc.371.
Wang, R., L. Wu, and C. Wang, 2011: Typhoon track changes as-
sociated with global warming. J. Climate, 24, 3748–3752,
doi:10.1175/JCLI-D-11-00074.1.
Webster, P. J., G. J. Holland, J. A. Curry, and H. R. Chang, 2005:
Changes in tropical cyclone number, duration, and intensity
in a warming environment. Science, 309, 1844–1846,
doi:10.1126/science.1116448.
Wu, L., andB.Wang, 2004:Assessing impacts of global warming on
tropical cyclone tracks. J. Climate, 17, 1686–1698, doi:10.1175/
1520-0442(2004)017,1686:AIOGWO.2.0.CO;2.
——, ——, and S. Geng, 2005: Growing typhoon influence on East
Asia.Geophys. Res. Lett., 32, L18703, doi:10.1029/2005GL022937.
——, and Coauthors, 2014: Simulations of the present and late-
twenty-first-century western North Pacific tropical cyclone
activity using a regional model. J. Climate, 27, 3405–3424,
doi:10.1175/JCLI-D-12-00830.1.
Xiao, F., and Z. Xiao, 2010: Characteristics of tropical cyclones in
China and their impacts analysis. Nat. Hazards, 54, 827–837,doi:10.1007/s11069-010-9508-7.
Ying, M., T. R. Knutson, H. Kamahori, and T. C. Lee, 2012:
Impacts of climate change on tropical cyclones in the
western North Pacific basin. Part II: Late 21st century pro-
jections. Trop. Cyclone Res. Rev., 1, 231–241, doi:10.6057/
2012TCRR02.09.
Zhang, Q., L. Wu, and Q. Liu, 2009: Tropical cyclone damages in
China 1983–2006. Bull. Amer. Meteor. Soc., 90, 489–495,
doi:10.1175/2008BAMS2631.1.
Zhao, H., and L. Wu, 2014: Inter-decadal shift of the prevailing
tropical cyclone tracks over the western North Pacific and its
mechanism study.Meteor.Atmos. Phys., 125, 89–101, doi:10.1007/
s00703-014-0322-8.
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