Effects of preexisting cyclonic eddies on upper ocean responses to

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115, C09013, doi:10.1029/2009JC005562, 2010
Effects of preexisting cyclonic eddies on upper ocean responses
to Category 5 typhoons in the western North Pacific
Zhe‐Wen Zheng,1 Chung‐Ru Ho,1 Quanan Zheng,2 Yao‐Tsai Lo,1 Nan‐Jung Kuo,1
and Ganesh Gopalakrishnan3
Received 9 June 2009; revised 18 March 2010; accepted 17 May 2010; published 14 September 2010.
[1] This study examines the impacts of preexisting mesoscale cyclonic eddies (PCEs) on
successive enhanced sea surface cooling in response to the passage of Super Typhoon Hai‐
Tang in the western North Pacific in 2005, using numerical simulation methods. We have
done two numerical experiments: one with the presence of these PCEs resolved by the
Hybrid Coordinate Ocean Model/Navy Coupled Ocean Data Assimilation system
(EXPHYC) and another with World Ocean Atlas 2001 climatology as initial conditions
(EXPWOA). The results show that the cooling response simulated by EXPWOA is only half
of that simulated by EXPHYC, which is close to satellite observations. This suggests that an
accurate representation of the upper dynamic conditions is required to estimate the sea
surface cooling to a typhoon accurately. Subsequently, the effects of the PCEs on
successive cooling response to most major typhoons are evaluated by conducting a
systematical analysis with a focus on Category 5 typhoons occurring in the region from
2003 to 2008. Satellite altimeter sea surface height anomaly data and merged Tropical
Rainfall Measuring Mission Microwave Imager/Advanced Microwave Scanning
Radiometer for EOS microwave sea surface temperatures (SST) are used to characterize
PCEs and cooling responses to those typhoons. The results identify the relationship
between PCEs and successive enhanced SST cooling for most strong typhoons in the
western North Pacific.
Citation: Zheng, Z.‐W., C.‐R. Ho, Q. Zheng, Y.‐T. Lo, N.‐J. Kuo, and G. Gopalakrishnan (2010), Effects of preexisting
cyclonic eddies on upper ocean responses to Category 5 typhoons in the western North Pacific, J. Geophys. Res., 115, C09013,
doi:10.1029/2009JC005562.
1. Introduction
[2] Over the last three decades, forecasts of hurricane or
typhoon tracks have been improved, steadily owing to the
combination of better observations and much improved
numerical models. However, predictions of hurricane or
typhoon intensity are advancing slowly [Emanuel, 1999;
Emanuel et al., 2004]. The hurricane or typhoon draws their
energy from the warm ocean waters. In the other words, the
ocean is an energy source for the tropical cyclone (TC)
development [Schade and Emanuel, 1999; Wu et al., 2007;
Lin et al., 2008]. More and more attention has been paid to
the role of the ocean played in TC intensity evolution in
recent years [e.g., Hong et al., 2000; Shay et al., 2000; Goni
and Trinanes, 2003; Emanuel et al., 2004; Lin et al., 2005;
Lin et al., 2008; Lin et al., 2009]. Most of the efforts have
1
Department of Marine Environmental Informatics, National Taiwan
Ocean University, Keelung, Taiwan.
2
Department of Atmospheric and Oceanic Science, University of
Maryland, College Park, Maryland, USA.
3
Climate Atmospheric Science and Physical Oceanography, Scripps
Institution of Oceanography, La Jolla, California, USA.
Copyright 2010 by the American Geophysical Union.
0148‐0227/10/2009JC005562
been focused on rapid TC intensification, while the TCs
pass over the warm ocean features [Shay et al., 2000; Goni
and Trinanes, 2003; Lin et al., 2005, Lin et al., 2008]. On
the other hand, it is worth noting that a TC’s passage has
been shown to markedly lower the sea surface temperature
(SST) under certain circumstances [Price, 1981; Wentz et
al., 2000; Lin et al., 2003; Walker et al., 2005; Zheng et
al., 2008]. This SST decrease determines the energy fed
into the storm from the ocean because evaporation and
conduction are directly dependent upon the air‐sea temperature difference [Leipper and Volgenau, 1972]. Therefore,
the upper layer cooling induced by the TC itself also plays a
key role in TC intensity change [Chang and Anthes, 1979;
Black and Holland, 1995; Schade and Emanuel, 1999].
Moreover, TC‐induced cooling affects not only the strength
of subsequent TCs but also the TC itself [Black and
Holland, 1995; Schade and Emanuel, 1999]. Even a 2°C
sea surface temperature change may cause a significant
impact on the strength of a TC [Anthes and Chang, 1978].
Schade and Emanuel [1999] further suggested that the SST
feedback is superimposed onto all other processes affecting
hurricane intensity because it directly affects the most fundamental process of a TC and the transfer of heat from the
ocean to the atmosphere. Therefore, with the advance in
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understanding of the positive correlation between warm
ocean features and successive typhoon intensification [Hong
et al., 2000; Shay et al., 2000; Goni and Trinanes, 2003;
Kaplan and DeMaria, 2003; Emanuel et al., 2004; Lin et
al., 2005; Lin et al., 2008; Lin et al., 2009], to gain further understanding about where cooling response to a TC
will take place becomes a key task for further improving
prediction of the change in typhoon intensity.
[3] The strong winds associated with a TC stir the sea
surface water and generate divergent outward flow together
with upwelling processes beneath the sea surface [Price,
1981]. Subsequently, cold subsurface water is entrained
and upwelled into the mixed layer and thus causes the mixed
layer and sea surface cooling [Price, 1981]. On the basis of
observed data, Jacob et al. [2000] concluded that entrainment dominates the cooling (75%–90%) in the upper mixed
layer. Price [1981] indicated that entrainment causes 85% of
the irreversible heat flux into the mixed layer, and upwelling
significantly enhances entrainment only under slowing
moving hurricanes (less than 4 m s−1). Moreover, only
∼10%–15% of the cooling in the upper ocean is due to
surface heat fluxes [Price, 1981]. Using a numerical model,
Prasad and Hogan [2007] concluded that ∼64% of the
cooling was due to vertical mixing (entrainment) caused by
turbulence generated from strong shear stress across the base
of the mixed layer. On the other hand, vertical advection
(upwelling) contributes up to 7%–23.4% of the cooling. The
value varies from 7% to 23.4% depending on the different
model configurations [Prasad and Hogan, 2007]. Overall,
vertical entrainment is considered to be the dominant process in causing the upper ocean cooling [Price, 1981; Jacob
et al., 2000]. Nevertheless, there are some uncertainties
existing in the process of typhoon‐induced ocean cooling,
for example, the upper ocean environment underlying the
typhoon passage.
[4] Recently, from multisensor‐observed data, Zheng et
al. [2008] revealed a tight relationship between the preexisting cyclonic eddies characterized by negative sea surface height anomalies and a series of extreme SST cooling
regions induced by Typhoon Hai‐Tang and concluded that
the intense cooling was caused by the uplifted thermocline
associated with preexisting cyclonic eddies. Using the
Hybrid Coordinate Ocean Model (HYCOM), Prasad and
Hogan [2007] investigated the upper ocean response to
hurricane Ivan and indicated that the regions of extreme
cooling varies depending on the simulated location of the
warm core eddy (WCE). These studies all suggested that the
preexisting mesoscale features play a crucial role to the
successive SST cooling in response to the typhoon passage.
However, some important issues still remain unresolved and
need to be explored. For example, what role do these preexisting mesoscale features play in the surface cooling in
response to most strong typhoons? If there are any other
factors, which of these may also modulate the cooling
process? A comprehensive investigation is needed to elucidate the relationship between the preexisting features and
successive surface cooling to most major TCs.
[5] One of the goals of this work is to identify the relationship between preexisting conditions and successive
surface cooling to a TC as suggested by Zheng et al. [2008].
We also want to provide quantitative values to evaluate the
effect of the preexisting cyclonic eddies (PCEs) on succes-
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sive surface cooling in response to Hai‐Tang’s passage. In
the first part of this study, numerical experiments with different upper ocean conditions are performed to quantify the
effects of the PCEs on those cooling responses to Hai‐Tang.
Meanwhile, satellite altimeter sea surface height anomaly
(SSHA) data are used to synoptically characterize instantaneous upper layer ocean conditions [Lin et al., 2005; Lin et
al., 2008; Zheng et al., 2008], and the microwave radiometer
data, which are insensitive to atmosphere and aerosols, are
used to provide a quantitative estimation of the upper ocean
responses to a TC through substantial clouds during a
typhoon passage [Wentz et al., 2000]. Thus, it is possible to
have a systematic analysis for a series of TC cases based on
satellite observations. In the second part of the study all
Category 5 (in the Saffir‐Simpson tropical cyclone scale)
super typhoons that occurred in the western North Pacific
from 2003 to 2008 are systematically analyzed to assess the
effects of PCEs on the processes in different typhoon cases.
2. Data and Methodology
2.1. Observations
[6] In this work, merged SST products retrieved from
Tropical Rainfall Measuring Mission (TRMM) Microwave
Imager (TMI) and Advanced Microwave Scanning Radiometer for EOS (AMSR‐E) are used to characterize the
upper ocean responses [Wentz et al., 2000] to all Category 5
typhoons from 2003 to 2008. The SSHA data derived from
TOPEX/Poseidon, Jason‐1, ERS‐1/2, and ENVISAT are
used to synoptically characterize upper ocean conditions
[Lin et al., 2008; Zheng et al., 2008]. The SSHA data with a
0.25 degree spatial resolution and a 7 day temporal interval
are provided by Archiving Validation and Interpretation of
Satellite Data in Oceanography (AVISO). The Joint
Typhoon Warning Center best track data are obtained from
Unisys Weather (http://weather.unisys.com/hurricane/).
2.2. Model Description and Experiment Design
[7] To elucidate the role PCEs played in the processes of
typhoon‐induced upper ocean response, a three‐dimensional, realistic bathymetry model based on the Regional
Ocean Model System (ROMS) is used in this study. ROMS
is a free surface, primitive equation, curvilinear coordinate
oceanic model, in which barotropic and baroclinic
momentum equations are resolved separately. Higher‐order
numerical schemes for space and time differencing (third‐
order, upstream‐biased advection scheme) allow the generation of steep gradients and a significant increase in the
permissible time step [Penven et al., 2006]. In addition, a
nonlocal, K profile planetary boundary layer scheme [Large
et al., 1994] parameterizes the subgrid‐scale vertical mixing
processes. Detailed description and validation of the model
can be found in Shchepetkin and McWilliams [2003, 2005].
[8] The model domain covers most of the western North
Pacific (15°N–35°N, 115°E–155°E) with a horizontal resolution of 0.25°. Vertically, 20 s coordinate levels are distributed unevenly for a good resolution of the upper ocean.
Model bathymetry is derived from ETOPO2 bottom
topography [Smith and Sandwell, 1997]. To evaluate the
contribution of PCEs to the process of typhoon‐induced
upper ocean response, the initial fields derived from HYCOM/Navy Coupled Ocean Data Assimilation (NCODA)
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Figure 1. (top) Sea surface height anomalies (estimated from sea surface height minus model domain
spatial average (m)), and (bottom) sea surface temperature (°C) prior to Hai‐Tang’s passage (1200 10 July
2005) simulated by HYCOM/NCODA system. The two fields are used as initial conditions for the model
integration. Typhoon tracks and intensities are depicted with color points.
system [Cummings, 2005] and World Ocean Atlas 2001
climatology (WOA01) [Stephens et al., 2002] are used to
resolve both the upper layer ocean conditions prior to the
arrival of Hai‐Tang and regular climatological conditions.
[9] The HYCOM/NCODA system is configured for the
global ocean with HYCOM as the dynamical model from
November 2003 to March 2009 with 1/12° equatorial resolution. Through the Navy Coupled Ocean Data Assimilation system, available satellite altimeter observations,
satellite and in situ SST as well as in situ vertical temperature and salinity profiles are assimilated. Because of the
lack of sufficient in situ observed data over the vast western
North Pacific, initial fields obtained from the system are the
preferred choice for providing the initial ocean conditions
before the passage of Typhoon Hai‐Tang for our experiments. The initial fields include three‐dimensional (3‐D)
zonal and meridional velocities, temperature, salinity, and
two‐dimensional (2‐D) sea surface height. The sea surface
height anomaly and SST fields prior to Hai‐Tang’s passage
(1200 10 July 2005) as shown in Figure 1 are used as the
initial ocean conditions for ROMS (all times are in UT).
[10] As for the surface forcing, surface heat and mass
fluxes are generated from atmospheric parameters (e.g.,
wind speed, air temperature, relative humidity, precipitation
rate, shortwave radiation, and outgoing longwave radiation),
which are obtained from Global Forecast System (GFS)
(available at http://nomads.ncdc.noaa.gov/) with a bulk
formula during the model run, instead of directly prescribing
the fluxes. The drag coefficients used for turbulent heat
fluxes and momentum flux are calculated from Kondo
[1975] and Large and Pond [1981]. Recent studies suggested that the wind drag coefficient would level off for
wind speeds exceeding 30 m s−1 [Powell et al., 2003], as
opposed to one that increases with wind speed for hurricane
force winds. However, the specific goal of this study is to
evaluate the influence of preexisting upper ocean environment to the cooling process. This might not adversely affect
the results of the numerical experiments. For the two experiments, surface winds at 10 m height are derived from
QuikSCAT/National Centers for Environmental Prediction
(QSCAT/NCEP) six‐hourly wind data (0.5° × 0.5°), which
are retrieved from a temporal and spatial blend of QuikSCAT satellite scatterometer observations and NCEP analysis
[Milliff et al., 1999].
3. Numerical Experiments
[11] Zheng et al. [2008] suggested that Super Typhoon
Hai‐Tang‐induced upper ocean cooling responses are
closely correlated to preexisting oceanic conditions, which
can be characterized by negative SSHA features. In order to
examine the dynamic therein and the role of PCEs in the
cooling process, the processes of Hai‐Tang‐induced upper
ocean responses are reproduced by ROMS with HYCOM/
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Figure 2. Model simulated SST fields on (a) 15 July, (b) 16 July, (c) 17 July, (d) 18 July, and (e) 19 July
2005. TMI/AMSR‐E SST images on (f) 15 July, (g) 16 July, (h) 17 July, (i) 18 July, and (j) 19 July 2005.
Contours, which denote PCEs characterized by negative sea surface features, are superimposed on the
SST fields. Green points denote the positions of Hai‐Tang corresponding to the date of SST fields.
NCODA outputs and WOA01 climatology used as initial
conditions in this section.
3.1. EXPHYC: Reproduction of Hai‐Tang‐Induced
Cooling Responses
[12] The initial fields from HYCOM/NCODA are used to
reconstruct the initial ocean state prior to the passage of Hai‐
Tang in July 2005. A numerical experiment (EXPHYC)
based on ROMS with these initial conditions is conducted to
reproduce the process of Hai‐Tang‐induced separate upper
ocean cooling responses along its track in the western North
Pacific. Figures 2a, 2b, 2c, 2d, and 2e show a series of
model‐simulated SST fields from 15 July to 19 July. One
can see that in contrast to the initial SST field (10 July 2005)
shown in Figure 1 (bottom), Hai‐Tang caused a series of
upper ocean cooling responses along its track. Furthermore,
the cooling responses took place separately in particular
areas rather than all the way along the track as observed by
microwave radiometers [Zheng et al., 2008]. Compared to
SST variability derived from TMI/AMSR‐E from 15 to 19
July (Figures 2f, 2g, 2h, 2i, and 2j), the magnitudes and
locations of four separately extreme cooling responses reproduced by model simulations generally show a good
agreement with the cooling responses derived from satellite
observations. Nevertheless, there is a minor difference existing between the locations of cooling responses C3 (as
marked in Figure 2) because the initial oceanic conditions in
the vicinity of C3 in our model are slightly different from
the real ocean conditions (as shown by contours in Figure 2).
Moreover, one can see that the maximum cooling responses
derived from the model and observed SST fields all occurred
at around 22°N, 126°E. The simulated cooling responses
also support a scenario that coexistence of maximum
typhoon intensity and PCEs causes the strongest cooling
responses.
[13] Figure 3 shows the time series of the SST drop at the
locations of the four distinct cooling areas in EXPHYC
(dashed lines). The SST drop derived from TMI/AMSR‐E
satellite measurement is also plotted in Figure 3 (solid lines)
for comparison. Overall, the evolutions of these cooling
responses produced by the model are comparable with the
observed SST drops during the typhoon’s passage. A relatively significant difference is found in the time series of
SST drops at around ∼19.5°N, 132.5°E (Figure 3c). This
difference is attributed to the fact that the initial condition
used by our model simulations did not resolve the location
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Figure 3. Time series of SST drop derived from EXPWOA (dotted lines), EXPHYC (dashed lines), TMI/
AMSR‐E (solid lines) at (a) 21°N, 142.5°E; (b) 22.5°N, 137°E; (c) 19.5°N, 132.5°E; and (d) 22°N, 126°E
from 15 to 22 July 2005.
of PCEs around 19.5°N, 132.5°E accurately (see contours in
Figure 2). Comparing the results shown in Figure 3 to PCEs
reflected by altimeter data and HYCOM/NCODA data prior
to Hai‐Tang passage (contours in Figure 2), one can see that
an accurate representation of the upper ocean dynamical
conditions is needed to estimate the successive surface
cooling accurately. In summary, with coexistence of accurate initial ocean conditions and adequate surface forcing,
the physical process of Hai‐Tang induced a series of separate cooling responses in the western North Pacific that can
be substantially reproduced by ROMS.
3.2. The Impact of PCEs on the Upper Ocean Cooling
Process
[14] Contours, which are superimposed on Figures 2a, 2b,
2c, 2d, and 2e, represent negative SSHA features derived
from the HYCOM/NCODA system (1200 10 July 2005),
showing PCEs prior to the passage of Hai‐Tang. One can
see that the locations of these PCEs show a good agreement
with the locations of large surface cooling regions simulated
by our model. This implies that PCEs make more significant
SST cooling after typhoon passage, and modeled PCEs are
able to act as good predictors for forecasting where extreme
cooling will subsequently take place. Moreover, with these
model outputs, the relationship between these PCEs and
subsequent upper ocean cooling beneath the sea surface can
be examined.
[15] Figure 4 shows model‐simulated vertical temperature
profiles extracted from two locations; one is a PCE area P1,
and another is a positive SSHA (warm feature) area P2 (P1
and P2 as marked in Figure 1 (top)). The two points are
closely located to and within a region affected by the same
TC intensity (Category 2). The profiles demonstrate the
processes of TC‐induced upper layer ocean responses
Figure 4. Vertical temperature profiles extracted from a
PCE area P1 at (a) 1500 15 July, (b) 0300 16 July, and
(c) 1500 16 July, and vertical temperature profiles extracted
from a positive SSHA area P2 at (d) 0900 15 July, (e) 2100
15 July, and (f) 0900 16 July. Black lines represent initial
temperature profiles prior to the passage of Hai‐Tang.
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Figure 5. Model simulated serial images of the SST drops by (left) EXPHYC and (right) EXPWOA on
(a) 15 July, (b) 16 July, (c) 17 July, (d) 18 July, and (e) 19 July 2005. Green points denote the positions of Hai‐Tang corresponding to the date of SST drops.
beneath the sea surface under different upper ocean conditions. The blue line in Figure 4c shows the upper layer
temperature profile of P1 at 1500 16 July, when the maximum SST cooling (∼2.4°C) took place. The blue lines in
Figures 4a and 4b show the cases at the same location but 1
day and a half day before 1500 16 July. The black lines
represent the initial conditions before Hai‐Tang’s arrival.
Figures 4a, 4b, and 4c show the process of Hai‐Tang’s
gradually induced upper layer ocean response at P1. The
processes of upper layer ocean cooling in our case agree
well with those suggested by Price [1981, Figure 21b]. At
depths within the initial mixed layer, water is cooled primarily by entrainment. At depths between bottoms of initial
mixed layer and new mixed layer, water is warmed up by
entrainment [Price, 1981].
[16] On the other hand, the blue line in Figure 4f shows
the temperature profile while the maximum cooling
response took place after Hai‐Tang’s passage but at P2
(0900 16 July). Again, blue lines in Figures 4d and 4e show
the profiles 1 day and a half day before maximum cooling
occurrence. The profiles in black represent the initial temperature structure. One can see that thermocline at P2 is
much deeper than that at P1. Because TCs thrive on warm
waters that are at least 26°C [Shay et al., 2000; Lin et al.,
2005; Lin et al., 2008], waters with a temperature less
than 26°C are considered cold water in this study. According to this definition, the depths of the cold water at P1 and
P2 are at ∼22 m and ∼81 m, respectively. Figures 4d, 4e, and
4f show the evolution of upper ocean responses to Hai‐
Tang’s passage at P2. In contrast to profiles extracted from
P1, one can see that cooling responses induced by Hai‐Tang
in the region within the positive SSHA area are much
weaker than that in the PCE area. The maximum temperature drop is only 0.5°C.
[17] The cooling processes reproduced by model simulations under different upper layer ocean conditions provide
dynamic evidence to support a scenario that the situation of
cold water closer to the sea surface accompanying PCEs
would favor entrainment and upwelling more efficiently and
thus enhance the cooling response eventually. Moreover, a
shallower mixed layer accompanying PCEs also contributes
to the cooling process. The reasons include that for the same
surface wind stress, the velocity shear between the base of
the mixed layer and upper thermocline is higher when the
mixed layer is shallower [Wu et al., 2007], and it has relatively small thermal inertia because of the relatively small
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Figure 6. TMI/AMSR‐E‐observed maximum cooling responses along typhoon tracks for (a) Maemi
(2003), (b) Lupit (2003), (c) Nida (2004), (d) Dianmu (2004), (e) Hai‐Tang (2005), (f) Nabi (2005),
and (g) Sepat (2007). Contours of PCEs are superimposed on the images. Typhoon tracks and intensities
are marked by color points.
volume of fluid that needs to be cooled; therefore, the
identical heat flux at the mixed layer base will cool a thin
mixed layer faster. Therefore, once a typhoon approaches to
the candidate areas with the PCEs distributed, the extreme
cooling responses will be triggered more easily. That is why
Hai‐Tang induced distinct surface cooling responses in
certain areas rather than all the way along its track.
3.3. EXPWOA: Upper Ocean Responses to Hai‐Tang
Without the PCEs
[18] To quantify the impact of PCEs on the processes of
Hai‐Tang‐induced upper ocean responses, we further conduct a non‐PCE experiment (EXPWOA) with the same
dynamic model (ROMS), surface forcing, and surface heat
flux but without the PCEs (using WOA01 July climatology
as initial ocean conditions). Subsequently, through comparison with cooling responses simulated by EXPHYC, we
can evaluate the impact of the PCEs on upper ocean responses to Hai‐Tang. Figure 5 shows the serial images of
the SST drops (DSST, sea surface temperature differences
from modeled initial conditions) obtained by the two experiments: with EXPHYC and without EXPWOA PCEs. One
can see that much stronger SST drops are induced in the
EXPHYC than EXPWOA. A maximum cooling simulated by
EXPWOA is less than −3.0°C, while a maximum cooling by
EXPHYC is −6.2°C.
[19] Figure 3 shows the time series of the SST drop at the
locations of the four distinct cooling areas derived from
EXPHYC (dashed lines), EXPWOA (dotted lines), and TMI/
AMSR‐E satellite observations (solid lines) for quantitative
comparison. One can see that the cooling responses simulated
by EXPHYC fit the satellite observations much better than that
simulated by EXPWOA, though the maximum SST cooling in
EXPHYC is generally less than the satellite measurement.
Because the model settings of EXPHYC and EXPWOA are
identical except the initial conditions, the improvement of
cooling response simulations in EXPHYC can be attributed to
the presence of PCEs resolved by the HYCOM/NCODA
system. These results imply that an accurate representation of
the upper ocean dynamical conditions is needed to estimate
the sea surface cooling accurately.
[20] Moreover, to quantify the effect of the PCEs, here we
define a factor to evaluate the effect of PCEs on the cooling
response; that is, FPCE = (DSSTPCE − DSSTnon‐PCE)/D
SSTPCE, where DSSTPCE (DSSTnon‐PCE) is the maximum
temperature drops between the maximum cooling that took
place in EXPHYC (EXPWOA) and initial oceanic state during
Hai‐Tang’s passage. From 15 July to 19 July, FPCE is 0.58,
0.42, 0.45, 0.52, and 0.50, respectively. This implies that if
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Figure 7. Category 5 typhoons in the western North
Pacific and a time series of monthly Nino3.4 El Niño–
Southern Oscillation (ENSO) index from 2003 to 2008.
Red and green patches represent the El Niño and La Niña
events, respectively, according to the definition by
Trenberth [1997]. Gray arrows denote the dates of Category 5 typhoons which occur in the western North Pacific
from 2003 to 2008.
Super Typhoon Hai‐Tang passed the same area, but without
encountering PCEs, surface cooling induced by its passage
will approximately be reduced by one half.
4. Observations of PCE Impacts on Ocean
Responses to Super Typhoons in the Western North
Pacific
[21] In the preceding experiments, the crucial role of
PCEs on the SST cooling forced by Hai‐Tang has been
clarified by a series of dynamic evidences provided by the
numerical model. However, Hai‐Tang was a special case
only; the impacts of initial upper ocean conditions on other
typhoons still remain unclear. In this section, we examine
PCE impacts on ocean responses to all Category 5 typhoons
that occurred in the western North Pacific from 2003 to
2008, using the TMI/AMSR‐E‐merged microwave SST
products. During this period, a total of 11 Category 5
typhoons are taken into account in the systematic analysis.
According to their cooling behavior, these typhoons are
divided into two groups for systematic interpretation.
[22] Figure 6 shows the maximum cooling responses to
typhoon cases Maemi (2003), Lupit (2003), Nida (2004),
Dianmu (2004), Hai‐Tang (2005), Nabi (2005), and Sepat
(2007), which occurred during the normal and La Niña
periods (as marked in Figure 7). The maximum cooling
responses are estimated by TMI/AMSR‐E satellite‐observed
maximum SST drops (relative to SST prior to typhoon
passage) caused by these TCs along their tracks. The parameters used to characterize the ocean responses are listed in
Table 1. One can see that the cooling responses to a majority
of these typhoons (6/7, except Maemi) show a regular rule,
i.e., all the cooling responses occurred under the following
two conditions: (1) there are PCEs existing, and (2) the
typhoon is intensifying to Category 4 and higher. Moreover,
synergy of both effects usually causes very large cooling for
some of the typhoons (e.g., Typhoon Dianmu in 2004,
Typhoons Hai‐Tang and Nabi in 2005, and Typhoon Sepat
in 2007, as shown in Table 1). On the other hand, Typhoon
Maemi (2003) was an exception. Along its track, there were
no PCEs observed, thus no extreme cooling responses
occurred. This case provides additional evidence for the
crucial role of PCEs played in the process of typhoon‐
induced upper ocean cooling response. Without the PCEs,
the extreme cooling response would not be trigged although
the intensity of Maemi reached to Category 4 (Figure 6a).
[23] There are a few exceptional TC cases that did not
follow the rule mentioned above to induce cooling responses. These exceptions are Typhoons Chaba and Ma‐On
in 2004, as well as Typhoons Saomai and Yagi in 2006.
More interesting is that all the four exceptional cases coincidentally occurred during El Niño periods, as shown in
Figure 7. Their maximum cooling responses along their
tracks are shown in Figure 8. Furthermore, their ocean
response parameters are listed in Table 2. One can see that
Typhoons Chaba and Yagi appeared to induce cooling responses all the way along the right hand sides of their tracks
rather than related to the PCEs. Typhoons Ma‐On and
Saomai did not induce distinct surface cooling after their
passage even when they encountered PCEs close to their
tracks. The maximum SST drop for Chaba (2004) and Yagi
(2006) reaches 5.1°C and 5.6°C, respectively, which is close
Table 1. Parameters of Seven Category 5 Typhoons Occurring During Normal and La Niña Years
Month and Year
Typhoon Life
Period
Maemi
Lupit
Sep 2003
Nov 2003
05 Sep to 16 Sep
20 Nov to 05 Dec
Nida
May 2004
15 May to 24 May
Dianmu
Jun 2004
13 Jun to 24 Jun
Hai‐Tang
Jul 2005
10 Jul to 23 Jul
Nabi
Sep 2005
29 Aug to 10 Sep
Sepat
Aug 2007
12 Aug to 22 Aug
Typhoon
Extreme
Cooling
Response(s)a
Encountering
PCEs
Typhoon
Intensityb
Maximum
DSST (°C)
−c
+1
+2
+1
+2
+1
+2
+1
+2
+3
+1
+2
+1
+2
−
−
+
+
−
−
+
+
+
+
+
+
−
+
‐
5
3
1
5
4–5
4
1
2
5
3–4
3
4
4–5
‐
−6.3
−6.0
−4.2
−4.5
−4.7
−5.1
−3.8
−3.6
−5.9
−6.6
−4.8
−3.8
−4.5
a
Superscript number denotes the number of extreme cooling response induced by individual typhoon.
Intensity while typhoon passed over cooling area.
c
Maemi did not induce extreme cooling response until it passed over the East China Sea continental shelf (as shown in Figure 6).
b
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Figure 8. TMI/AMSR‐E‐observed maximum cooling responses along typhoon tracks for (a) Chaba
(2004), (b) Ma‐On (2004), (c) Saomai (2006), and (d) Yagi (2006). Contours of PCEs are superimposed
on the images. Typhoon tracks and intensity changes are marked by color points.
to that in the cases of normal and La Niña periods. However,
the maximum SST drop induced by Saomai (2006) is only
2.3°C, which is much smaller than that in other cases. These
results suggest an interesting scenario that the long‐term
climate change may impact the process of typhoon‐induced
upper ocean responses. Nevertheless, because of the highly
complex environment changes (including both the atmospheric and oceanic parts) caused by the El Niño event,
further investigations are needed to clarify how the climate
events affect the ocean cooling process to a typhoon.
5. Summary
[24] In this study, we reproduce the physical processes of
Hai‐Tang‐induced series of separate upper ocean responses
in the western North Pacific in 2005, using a dynamic model
(ROMS), surfacing forcing, air‐sea flux given by GFS, and
initial ocean conditions derived from HYCOM/NCODA
system. A good agreement between the locations of PCEs
given by model initial field and subsequent surface cooling
responses implies that existing of PCEs makes more significant SST cooling after typhoon passage, and modeled
PCEs are able to act as good predictors for forecasting
where extreme cooling will subsequently take place.
[25] Model‐simulated vertical temperature profiles extracted from two locations within PCEs and also within a
positive SSHA area demonstrate the processes of how Hai‐
Tang induced upper ocean cooling beneath the sea surface
under different upper ocean conditions. In comparison with
vertical temperature profiles changes extracted from a positive SSHA area, cooling responses occurring within a PCEs
area with cold water closer to the sea surface (∼22 m) show
much more distinct temperature drops. The mechanisms
producing enhanced cooling in thin‐mixed layers are the
proximity of cold water to the sea surface that can be easily
entrained, stronger mixed layer currents associated with
larger shear at the mixed layer base, and the smaller thermal
Table 2. Parameters of Four Category 5 Typhoons Occurring During El Niño Years
Typhoon
Month and Year
Typhoon Life
Period
Chaba
Ma‐On
Saomai
Yagi
Aug 2004
Oct 2004
Aug 2006
Sep 2006
19 Aug to 03 Sep
04 Oct to 12 Oct
05 Aug to 14 Aug
17 Sep to 28 Sep
Extreme
Cooling
Response (s)
Encountering
PCEs
Typhoon
Intensitya
Maximum
DSST (°C)
+
+
−
+
−/+b
−
−
−/+b
4–5
2–4
‐
5
−5.1
−4.7
‐
−5.6
a
Intensity while typhoon passed over cooling area.
−/+ denotes that a part of the cooling response encountered PCEs, but a part did not.
b
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inertia. Moreover, the process of upper layer ocean cooling
within a PCEs area simulated by our model shows a good
agreement with the results of Price [1981].
[26] Subsequently, a control experiment (EXPWOA) without the contribution of PCEs (using WOA01 climatology as
initial ocean conditions) is conducted to evaluate the impact
of the PCEs on upper ocean responses to a typhoon. The
results show that cooling responses simulated by EXPHYC fit
the satellite observations much better than those simulated by
EXPWOA. This implies that an accurate representation of the
upper ocean dynamic conditions is needed to estimate the sea
surface cooling accurately. In addition, the PCE factor FPCE =
0.5 implies that cooling responses to Super Typhoon Hai‐
Tang will be reduced by about a factor of two without PCEs
being present. These results provide dynamical evidence to
elucidate the crucial role of PCEs play in the process of
typhoon‐induced upper ocean cooling response.
[27] A systematical analysis, focused on all Category 5
super typhoons that occurred in the western North Pacific
from 2003 to 2008 (in total 11 cases), is carried out to
evaluate the role PCEs played in the cooling responses to
other major typhoons. The results reveal that extreme surface cooling in response to most typhoons occurred under
the following two conditions: (1) there are PCEs present and
(2) the typhoon reaches Category 4 or higher although there
are four exceptions to these conditions. However, more
interesting is that these four exceptional cases all occurred
during El Niño periods, while the upper ocean was underlying the drastic changes caused by El Niño. This sheds light
on an important possibility that the long‐term climate
change may impact the process of typhoon‐induced upper
ocean responses. However, we have analyzed only four
cases that occurred over a limited time span from 2003 to
2008; it is still far to reach a definite conclusion. This is
because the El Niño events largely alter environment factors
of both ocean and atmosphere; further studies, statistical and
numerical, are needed for understanding the cooling responses during El Niño periods.
[28] Numerical experiments conducted in this study not
only provide a dynamic evidence to identify the crucial role
of PCEs played in the process of typhoon‐induced upper
ocean responses but also point out the importance of an
accurate representation of upper‐ocean dynamical conditions, which are required to accurately reproduce the sea
surface cooling by a typhoon. Since the surface cooling in
response to a typhoon plays a key role in the typhoon
intensity change [Black and Holland, 1995; Monaldo et al.,
1997; Schade and Emanuel, 1999], further understanding of
the generation mechanism of extreme cooling responses and
more accurate PCEs information prior to typhoon passage,
either from satellite observations or a nowcast/forecast
model system, can be expected to substantially improve the
prediction of typhoon intensity.
[ 29 ] Acknowledgments. The authors deeply appreciate the two
anonymous reviewers. Their valuable comments greatly improved the earlier manuscript. We thank B. Cornuelle, J. F. Price, D.‐S. Ko, Y. Chao, and
P. Penven for valuable discussions. Thanks also go to J. Alpert, S.‐F. Lin,
and C.‐Y. Lee for assistance in data provision. HYCOM/NCODA and GFS
data were provided by HYCOM Consortium and NCDC. The altimeter products were provided by AVISO with support from CNES. QSCAT/NCEP
blended ocean winds were from the Research Data Archive (available at
NCAR). The TMI/AMSR‐E sea surface temperatures were provided by
C09013
Remote Sensing Systems. The Niño3.4 SST anomaly data were obtained
from NOAA Climate Prediction Center (CPC), and JTWC best track
typhoon data were provided by Unisys Weather. This work was supported
by the National Science Council of Taiwan through grant NSC 98‐2611‐
M‐019‐017‐MY3 and partly supported by US NOAA NESDIS ORS Program 05‐01‐11‐000 (for Zheng).
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G. Gopalakrishnan, Climate Atmospheric Science and Physical
Oceanography, Scripps Institution of Oceanography, La Jolla, CA 92093,
USA.
C.‐R. Ho, N.‐J. Kuo, Y.‐T. Lo, and Z.‐W. Zheng, Department of Marine
Environmental Informatics, National Taiwan Ocean University, Keelung,
202, Taiwan. ([email protected])
Q. Zheng, Department of Atmospheric and Oceanic Science, University
of Maryland, College Park, MD 20742, USA.
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