26. INFLUENCES OF NATURAL VARIABILITY AND
ANTHROPOGENIC FORCING ON THE EXTREME 2015
ACCUMULATED CYCLONE ENERGY IN THE
WESTERN NORTH PACIFIC
Wei Zhang, Gabriel A. Vecchi, Hiroyuki Murakami, Gabriele Villarini, Thomas L. Delworth,
K aren Paffendorf, Rich Gudgel, Liwei Jia , Fanrong Zeng, and Xiaosong Yang
The extreme value of the 2015 western North Pacific (WNP) accumulated cyclone energy (ACE) was
mainly caused by the sea surface warming in the eastern and central Pacific, with the anthropogenic
forcing largely increasing the odds of the occurrence of this event.
Introduction. The 2015 tropical cyclone (TC) activity
measured by the ACE [computed as the sum of thesquare of the maximum surface wind speed (MSW)
over the TC duration when MSW is greater than 34
knots; e.g., Bell et al. 2000] was extremely high in thewestern North Pacific Ocean (Figs. 26.1a,b and 26.2a).
The 2015 WNP ACE is the second highest since 1970
(with the highest being 1997) based on the Joint Typhoon Warning Center best track data for 1970–2014
and Unisys data for 2015 (http://weather.unisys.com/hurricane/), the highest since 1977 based on theJapan Meteorological Agency (JMA), and the highest since 1970 based on Shanghai Typhoon Institute(STI) data. Higher (lower) WNP ACE is generally
observed during El Niño (La Niña) years, because
TCs are formed more southeastward (northwestward) and stay longer (shorter) over the warm ocean
surface (e.g., Camargo and Sobel 2005; Chan 2007).
This shift in genesis and difference in tracks leads toa higher occurrence of the most intense typhoons,
which is the main cause of a high ACE during El Niño
years. An extremely strong El Niño event developedin 2015. While there has been major progress in theunderstanding of the El Niño–Southern Oscillation(ENSO)–WNP ACE association, the modulation of
AFFILIATIONS: Zhang , Veechi , Murakami , Delworth ,Paffendorf, Jia , and Yang —NOAA/Geophysical Fluid Dynamics
Laboratory, Princeton, New Jersey; Zhang , Veechi , Murakami ,Delworth , Paffendorf, Gudgel , Jia , and Zeng —Atmospheric andOceanic Sciences Program, Princeton University, Princeton, New
Jersey; Zhang and Villarini —IIHR–Hydroscience & Engineering,
The University of Iowa, Iowa City, Iowa; Yang—University
Corporation for Atmospheric Research, Boulder, Colorado
DOI:10.1175/BAMS-D-16-0146.1
A supplement to this article is available online (10.1175/BAMS-D-16-0146.2)

AMERICAN METEOROLOGICAL SOCIETY

WNP ACE by anthropogenic forcing is still a challenging scientific question (e.g., Emanuel 2013; Lin
and Chan 2015). Using observations and a suite of climate model experiments, this study attempts to assess
whether and to what extent internal climate modes(e.g., ENSO) and anthropogenic forcing contributed
to the extreme 2015 WNP ACE event.
Methodology. We use two coupled general circulation
models (CGCMs): the Geophysical Fluid Dynamics Laboratory (GFDL) forecast-oriented low ocean
resolution model (FLOR; Vecchi et al. 2014) and highresolution FLOR (HiFLOR; Murakami et al. 2015a;
Zhang et al. 2016b). TCs are identified and tracked
using a tracking algorithm based on various model
variables (Zhang et al. 2016a,b; see online Supplemental Material). The climatological values of WNP ACE
in the observations, FLOR, and HiFLOR are different
partly because of different spatial resolutions and climate mean states; we therefore analyze the WNP ACE
values in terms of exceedance probabilities (e.g., 0.95,
0.99) of all the sampled ACE values in observations
and simulations. Following Murakami et al. (2015b)
and Yang et al. (2015), we use a probabilistic approach
to examine the probability of a WNP ACE event as:

where x is a selected WNP ACE value and P(x) represents the probability with WNP ACE larger thanor equal to x. We use the fraction of attributable risk
(FAR; e.g., Allen 2003; Stott et al. 2004) to quantify
the FAR to human influence or anthropogenic forcing. FAR is defined as FAR = 1 − (P0/P1), where P0(P1) is the probability of exceeding the observed TC
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trend in the experiments
without (with) anthropogenic
forcing. We compute FAR
using P0 from a 1990 control
experiment of FLOR and P1
from a 2 × CO2 experimentwith the same model (vander Wiel et al. 2016). We also
compute P0 (P1) from the two
experiments of HiFLOR withradiative forcing representative of 1940 (2015; 1940 is also
a strong El Niño year).
Natural Variability. The extremely high 2015 WNP ACE
is mostly due to a large number of category 4 and 5 (C45;wind speed exceeding 58.1
m s−1) TCs (Fig. 26.1a). There
were 13 C45 TCs in the WNP
during 2015, more than twice
the climatological value of
6.3. The 2015 C45 proportion, defined by the numberof C45 TCs divided by thebasin-total TCs, is 0.48 while
the climatology (1970–2015)
is 0.25. The 2015 basin-total
TC frequency (27) is slightly
higher than climatology (25).
−1
The ENSO–WNP ACE as- Fig. 26.1. (a) TC tracks in 2015 and C45 TCs (wind speed exceeding 58.1 m s )are shown in red. The C45 proportion in 2015 is 0.48 while the climatology
sociation is supported by the (1970–2015) is 0.26, with 13 (6.3) C45 TCs in 2015 (climatology; see Supplemenhigh Niño-3.4 index in 2015, tal Material for data sources). (b) Time series of different annually averaged
similar to those in 1987 and normalized climate indices (see legend) and ACE (black); Cor (Niño-3.4, ACE)
1997 (Figs. 26.1b,c). The SST denotes the correlation coefficient between Niño-3.4 index and WNP ACE forwarming in 2015 extends 1970–2015, while the others are defined likewise. (c) Sea surface temperature
westward to 160°E, and this anomalies (°C) in 2015 computed with respect to the 1970–2000 base period.
provides favorable conditions
for TC intensification because WNP TC intensifica- ACE and the AMM is negative but not statisticallytion is influenced both by TC genesis location and significant (Fig. 26.1b, see Supplemental Material for
ocean temperature (Wada and Chan 2008; Mei et more details of the indices). The Niño-3.4 and PMM
al. 2015; Zhang et al. 2015). Previous studies sug- indices in 2015 are strongly positive, contributing togested that factors such as the Pacific meridional the extreme 2015 WNP ACE. Therefore, internal climode (PMM), the Pacific decadal oscillation (PDO), mate modes, especially the strong El Niño, may haveand the Atlantic meridional mode (AMM) (see substantially contributed to the extreme 2015 WNP
Supplemental Material) may also modulate WNP ACE by leading to an extremely high frequency ofACE (e.g., Chan 2008; Zhang et al. 2016a,c). The C45 TCs (Camargo and Sobel 2005).
correlations between WNP ACE and the Niño-3.4(significant at 0.01 level), PMM (significant at 0.01 Effect of Anthropogenic Forcing. We analyze two sets oflevel), and PDO (not significant at the 0.01 level) in- experiments (i.e., 1990 control and 2 × CO2 experidices are positive, while the correlation between WNP ments) with FLOR. The probability density functions
S132 |DECEMBER 2016

Fig. 26.2. (a) Annual WNP ACE based on observations. (b) PDFs of WNP ACE in 1990 (blue) and 2 × CO2 (red)experiments with FLOR. (c) PDFs of WNP ACE in the experiments with radiative forcing representative of 1940
(blue) and 2015 (red) in HiFLOR. The magenta bars represent the 99th percentile of the ACE values (similar
to observations) in FLOR/HiFLOR. (d) P(x = 95th percentile) in FLOR-FA all_forcing/nat_forcing multidecadal
experiments with upper/lower limits of error bars represent ENSO+/− (red), PMM+/− (blue), PDO+/− (green),and AMO−/+ (magenta). The brown bars represent P(x = 95th percentile) in two control experiments with thewidths representing the 0.95 confidence intervals. The black and gray curves represent P(x = 95th percentile)in samples of all_forcing and nat_forcing experiments, respectively.

(PDFs) of WNP ACE in FLOR 1990 control and 2 ×
CO2 experiments have similar mean values while
their variances are different, with a fatter tail in the
2 × CO2 experiment (Fig. 26.2b). We select the ACE
values in the 99th percentile of FLOR 1990 to calculate
FAR, consistent with the percentile of the observed
2015 WNP ACE (Figs. 26.2a,b). The FAR in the 1990
control and 2 × CO2 experiments of FLOR are 0.81,
indicating that anthropogenic forcing can substantially increase the risk of having extreme WNP ACE
events higher than or equal to the 2015 event. To further substantiate this finding, we also analyze P0 and
P1 in the two experiments of HiFLOR with radiative
forcing representative of 1940 and 2015. The PDFs of
WNP ACE in HiFLOR also have a fatter tail in theexperiment with radiative forcing representative of2015 compared with that of 1940 (Fig. 26.2c). The FARAMERICAN METEOROLOGICAL SOCIETY

in HiFLOR is 0.80, close to 0.81 in the experimentswith FLOR (Figs. 26.2b,c).
We ran 35-member simulations with all forcing(natural and anthropogenic under RCP 4.5 scenario)
and 30-member multidecadal simulations withnatural forcing from 1961 to 2040 (see Supplemental
Material). For each 20-year period from 1961, 1300
(20 × 35 + 20 × 30) samples (years) were available
to calculate P(x). We define a simulated positive (ornegative) phase of ENSO, PDO, PMM, and AMO asthese indices exceeding (falling below) one (minusone) standard deviation and estimate the amplitudeof P(x) between the two phases. Figure 26.2d illustrates the results for P(x = 95th percentile). P(x = 95th
percentile) in all_forcing experiments increases from1960 to 2040, suggesting that the external forcing
tends to increase the odds of occurrence of extreme
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WNP ACE. There is a sharp increase in P(x = 95th
percentile) during 2020–40 (Fig. 26.2d). In addition,
the P(x = 95th percentile) in nat_forcing experiments
also largely increases in 1960–2060, except for a slightdecrease from 1960–80 to 1980–2000. The P(x = 95th
percentile) in all_forcing experiments are higher
than those in nat_forcing experiments, indicatingthat anthropogenic forcing increases the risk of having extreme WNP ACE events. The results based on
FLOR-FA 1860 and 1990 control experiments arealso shown in the left of Fig. 26.2d, providing additional support to these conclusions. For each 20-year
subperiod in 1980–2040, ENSO produces the largest
variability of WNP ACE (Fig. 26.2d). The variability
associated with ENSO is larger than that associatedwith radiative forcing (Fig. 26.2d). Therefore, theextreme 2015 WNP ACE may be mainly modulated
by natural climate modes, especially by the strong
El Niño, with the anthropogenic forcing increasing
the risk of 2015 having a season with an extremely
high WNP ACE. This risk is predicted to continue
to increase in the next few decades, increasing theprobability of having seasons with a WNP ACE equal
to or higher than 2015 in the future.
Discussions and Conclusions. We have observed an extremely active TC season in the WNP in 2015, with anextremely high ACE and frequency of C45 TCs. The
2015 season may be caused mainly by warm ocean
surface temperatures in the tropical Pacific, characterized by a strong El Niño event, with other climate
modes (e.g., PMM) potentially playing a role. We havefound that anthropogenic forcing has substantially
increased the risk of having WNP ACE higher than orequal to such an extreme event. Although the changes
in WNP ACE under anthropogenic forcing are still
unclear (e.g., Emanuel 2013; Lin and Chan 2015), both
GFDL FLOR and HiFLOR do suggest that the annual
WNP ACE tends to become more extreme because ofanthropogenic forcing. The two models also suggestthat the variability of WNP ACE attributable to climate modes will increase at a much higher rate thanas a result of anthropogenic forcing. The frequency ofstrong El Niño events is projected to increase due togreenhouse warming (Cai et al. 2014), which in turn
could potentially lead to a higher frequency of WNP
seasons with high values of ACE.
ACKNOWLEDGEMENT. This material is basedin part upon work supported by the National Science
Foundation under Grants AGS-1262091 and AGS1262099.
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