Even though the maximum wind radius (
The maximum wind radius (
Numerical simulations have often predicted the extent of inundation due to catastrophic storm surges. For example, in the storm surge model of the Japan Meteorological Agency (JMA), two kinds of meteorological forcing fields are used: a simple parametric model of the tropical cyclone (TC) structure and a prediction of the operational non-hydrostatic mesoscale model (JMA, 2009). Although TC forecasts with a mesoscale model have gradually improved, their mean position error remains around 100 km for 24 h forecasts (JMA, 2009). Furthermore, high spatial resolution is needed to resolve the pressure gradients near the radius of maximum winds; thus, forecasted “low-resolution” storms tend to be weaker than they can be (Persing and Montgomery, 2005). The relationship between TCs and climate can be subtle, while differences in the spatial and temporal scales are large (Elsner and Jagger, 2013). In addition, it was found that the JMA Global Spectral and Typhoon models (GSMs) underestimate the intensity of TCs in their predictions of the central pressure and maximum wind speed (Heming and Goerss, 2010). Therefore, the JMA still uses the parametric TC model to account for the errors in the TC track forecasts and their influence on storm surge prediction (JMA, 2009).
In a parametric model, TCs are defined by a few parameters (e.g., wind speed,
central pressure,
For hurricanes with central pressures of 909–993 hPa in 1893–1979, the
mean
However, the
Quiring et al. (2011) used the maximum wind velocity (
The empirical formula developed by the National Institute for Land and
Infrastructure Management (NILIM) (Kato, 2005) has been often used to
estimate the
The purpose of this paper is to examine the existing models for
In this section, the data for the TC analysis, using only TCs crossing the Japanese archipelago, are elucidated. A brief description of the storm surge model is also presented.
Ten meteorological stations along the Japanese archipelago operated by
the Japan Meteorological Agency (JMA): Minamidaitou-jima
Tracks of the 17 selected tropical cyclones transiting over the ocean.
The color differences represent the changes in central pressure. The crosses
indicate the location of the 10 meteorological stations operated by the Japan
Meteorological Agency (JMA): Minamidaito-jima
The major problems in obtaining TC maximum wind observations result from the sparseness of oceanic stations (Akinson et al., 1977). However, the good density of meteorological stations along the Japanese archipelago has great potential for collecting data during TC passages. Figure 1 indicates the 10 meteorological stations on Japan's southern islands operated by the JMA. Using data from these stations, it was possible to analyze typhoons traveling within about 800 km between Naze and Yonaguni-jima (Fig. 1).
As a TC approaches the Japanese main islands, its track, shape, and intensity are altered due to topographical disturbance (Fujii, 2006). Therefore, the use of data from these remote islands avoids the substantial changes in TC structure induced by land topography.
Data collection from the selected stations was restricted to when the station
experienced low pressures (
Recent major TCs, which caused more than 2000 fatalities, such as the 2004
Hurricane Katrina, the 2007 Cyclone Sidr, the 2008 Cyclone
Nargis, and the 2013 Typhoon Haiyan had very low central
pressures (895–937 hPa) and caused severe storm surge disasters (Table 1).
Of all hurricane damage, 80 % is caused by less than 20 % of
the worst events (Jagger et al., 2007). The aim of the present study is to
develop an
Because the JMA meteorological information contains hourly central pressures and wind speeds only after 1990 (before, data were limited to 3 or 6 h intervals), only data from 1990 to 2013 were used. A TC track analysis was carried out for the WNP, using the best track data from the JMA, which consisted of time, geographical position, sea level pressure at the storm center, maximum sustained wind speed, and auxiliary information for every 3 or 6 h. Only 17 out of the 621 TCs that occurred from 1990 to 2013 met the selection criteria and were used in this study. Their characteristics and tracks are presented in Table 2 and Fig. 2, respectively.
The atmospheric pressure inside a TC is generally expressed by an empirical
formula. For our model, the Myers model was adopted to calculate the
pressure at a distance
Major tropical cyclones in the last 10 years causing extensive storm surges.
Note: central pressure and wind speed shown in the table are from when the
TC made landfall.
Data source: National Hurricane Center (NHC)
Characteristics of the 17 typhoons selected for this study.
For the estimation of
If the exact values for
Although the present study investigated only the station closest to the TC center, ignoring the other stations, including data from additional stations may improve the representation of the TC profile, particularly its tail. For the purpose of improving storm surge forecasting, however, the authors submit that the data closest to the TC center should be most emphasized rather than details of the tail profile, which is less influential for storm surge generations.
It is noted that the representation of
The effectiveness of a new formula mainly aimed to improve the estimation of
storm surges must be addressed through storm surge simulations. Takagi et
al. (2015a, 2016) reproduced the storm surge from the 2013 Typhoon Haiyan for various parts of the Philippines, including Leyte, Samar,
and Cebu. We extended this simulation by incorporating the new
We applied a parametric typhoon model based on the Myers model (Takagi et al., 2012; Takagi et al., 2015a) coupled with the fluid dynamics model Delft3D Flow to estimate the extent of two strong storm surges: one in the Philippines during the 2013 Typhoon Haiyan and the other in the southern islands of Japan during the 2015 Typhoon Goni. This parametric typhoon model calculates both pressure and wind fields using the parameters from the typhoon track data set of the JMA (i.e., central positions and pressures). The Delft3D Flow model was applied to the simulation of a storm surge traveling from the deep sea to shallow waters and eventually running over coastal areas. Although this model is applicable to a 3-D domain, the present study uses a 2-D horizontal grid, making the code equivalent to a non-linear long wave model, which is most commonly used for storm surge simulations.
In this section, the estimations of
Wind radii and central pressures of 17 tropical cyclones and estimations from the National Institute for Land and Infrastructure Management (NILIM), Port and Airport Research Institute (PARI), Japan Weather Association (JWA), Hsu and Yan (1998) models, and Vickery and Wadhera (2008).
Figure 3 shows a scatter plot for
However, individual radius values show significant scatter around the
regression lines. In fact, the coefficient of determination
Estimated wind radii (
Tropical cyclone information from the Regional Specialized
Meteorological Center (RSMC) Tokyo/Japan Meteorological Agency (JMA)
(
The
The relative inadequacy of
Relationship between the radii of the 50 kt winds around a typhoon
(
The
Although this new method was expected to improve the estimation of
Comparison of observed and simulated storm surges during the passage
of Typhoon Goni in 2015. The water level was observed at the tide station of
Ishigaki-jima, which is located at 24
Distribution of storm surge heights at the time of Typhoon Goni passed
over Ishigaki-jima, estimated with
Figure 6 also indicates the estimated
Maximum storm surge heights in San Pedro Bay due to the passage of Typhoon Haiyan (after Takagi et al., 2015a).
Two major typhoons, Goni and Haiyan, both of which were not
included in the data used for the development of the present
Figure 7 presents an application of the proposed method to a recent strong
typhoon, Typhoon Goni, which traveled over the southern oceanic
basin of Japan in August 2015. This severe typhoon brought about very strong
winds, reaching up to 71.0 m s
The present analysis indicates that the larger the typhoon radius, the
greater the storm surge height is at a tide station. Figure 8 also
demonstrates how changes in
Typhoon Haiyan caused the worst storm surge disaster in the recorded history of the Philippines, striking Leyte Island in November 2013 and causing inundations of up to 6–7 m in Tacloban City, where most casualties occurred (Nakamura et al., 2015; Mikami et al., 2016; Esteban et al., 2015, 2016). High inundation heights were observed even outside the Leyte Gulf along the eastern coast of Eastern Samar, which faces the Pacific Ocean in the deep Philippine Trench. Haiyan generated the strongest winds among over 400 past storms, being 16 % stronger than the second strongest recorded typhoon. Haiyan's forward speed was nearly twice the average speed of these weather systems, potentially making it the fastest recorded typhoon (Takagi et al., 2015b). A numerical simulation indicated inundation above 3 m along the entire bay and up to 6 m in the inner bay (Fig. 9; Takagi et al., 2015a). The maximum hindcast significant wave heights caused by the extremely strong winds reached 19 m off Eastern Samar (Bricker et al., 2014; Roeber et al., 2015).
To assess which areas of the Philippines were affected by Typhoon Haiyan, a simulation was initially carried out for a wide area encompassing most of the Philippines. Then, a more detailed simulation was performed for San Pedro Bay in the Leyte Gulf, an area where the massive storm surge engulfed and claimed thousands of lives. The numerical simulation for these two domains had already been implemented in a previous study by the authors (Takagi et al., 2015a).
Figure 10 presents the estimated maximum storm surge heights for six
locations around San Pedro Bay. The simulation was implemented for two
different radii covering the 95 % prediction interval, namely
Simulated storm surge heights (black and blue) derived from different
maximum wind radii (
Although previous research (e.g., Jelesnianski, 1972, Loder et al., 2009)
suggested that peak surge elevation would increase for a large
The
Rainfall intensity detected by the Doppler radar system on Cebu Island when Typhoon Haiyan passed the Leyte Gulf.
As the
However, some estimation errors (Fig. 6) were unavoidable because of
fundamental uncertainties in the TC structure and insufficient number of
available TCs to derive the relationship from Eq. (3). For example, a
challenge for the
Estimated maximum wind radius and central pressures of the 2015
Typhoon Goni during its transit near Ishigaki-jima,
Some TC parameters such as center positions,
Therefore, the estimation of
It should also be noted that various
With regard to Typhoon Goni, the progress of
This example implies that the new estimation is expected to provide a
reliable
The consideration of these uncertainties in storm surge simulation is also
relevant with regard to the uncertainty in the TC information issued by the
agencies. An examination of our 17 selected TCs indicates that temporal
changes in
Therefore, the variability of
Using observations from a number of Japanese islands and best track data, 17
typhoons with central pressures below 935 hPa that passed near
meteorological stations were selected to examine existing methods and a new
method is presented to calculate
The present research was funded by the JSPS KAKENHI grant number 26702009 and
the Environment Research and Technology Development Fund (S-14) of the
Ministry of the Environment, Japan. The JMA typhoon best track data are
available at