NCAR「JointWRF/MPAS Users
Workshop 2024」（当社社員発表風景）

P4

Using WRF and SWAN models in calculating
wind and wave conditions for Typhoon Jebi (2018)

Haruka MIURA (miura.haruka@meci.jp)
Meteorological Engineering Center, Inc, Japan

1. Introduction
Japan experiences weather disasters all year long. We experience extreme heatwaves and heavy rainfall in summer,
typhoons in autumns, heavy snowfall in winter, and avalanche caused by snowmelt in spring. These weather events
bring harmful impact to the society, highlighting the importance of accurate weather forecasting. However, it isparticularly challenging in Japan due to its highly complex geographical structures. Therefore, extensive effort has been
invested into improving the skill of the forecast models. In order to test the accuracy of the WRF and SWAN (SimulatingWaves Nearshore) models, wind speed, direction and wave conditions were calculated using the models for Typhoon
Jebi (2018).

2. Typhoon Jebi (2018)
In 2018, Typhoon Jebi brought significant damages around
Osaka Bay, located in the western areas of Japan. It madelandfall as a Category 3 typhoon for the first time in 25 years, andbrought extremely strong winds and high waves.

Fig.1 Track chart of Typhoon Jebi.
〇 is 9:00 JST. ● is 21:00 JST.

At Sumoto, where the typhoon
passed, the observed windspeed decreased with change
in wind direction. This is inaccordance with the model
predictions.

GoddardFig.5 Observed and predicted
wind conditions around Osaka
Bay.
ANAL(5km)
14:00

GSM (20km)
14:00

Thompson
14:30

WSM6
14:10

Kessler
14:50

Lin et al.
14:10

WSM3
14:20

WSM5
14:10

Ferrier
14:30

Goddard
14:10

Milbrandt-Yau
14:20

Morrison
14:10

CAM5.1
14:20

SBU_YLIN
14:30

WDM514:10

WDM614:10

Fig.3 The location of Osaka Bay.

Fig.2 ↑ A tanker crashes intoKansai International Airport’sbridge due to strong winds.
→Fallen utility poles blocking aroad in Osaka.

3. WRF

ANAL is hourly atmospheric analysis data provided
by the JMA.

Table.1 WRF model settings.

Table.1 shows the WRF model settings used for thisexperiment. The initial and boundary conditions were derived Modelfrom GSM (Japan Meteorological Agency’s Global Spectral Horizontal resolution [km]Model). It is a global numerical forecast model produced by the Mesh
JMA, which produces separate datasets for both the entire Number of vertical layers
globe and Japan. The current study utilized the regional dataset.
Cumulus convection
In order to perform a sensitivity analysis, the simulations wereMicrophysics
done with 14 different microphysics schemes (Table.2).

Area1

Area2

Area3

186

2

94

112

133

27
Kain-Fritsch-listed in Table.2

Long wave radiation

RRTM

Sort wave radiation

DudhiaSurface layer

Revised MM5 Monin-Obukhov

Land surface

Noah land-surface
YSU

Planetary

gtopo_30s

Geog_data_res

Table.2 Microphysics schemes.

casecase
Fig.4 WRF domain configuration.

1Thompson

6Fig.6 Distribution of wind speed at the time when thehighest wind speed was predicted at KIX for eachmicrophysics scheme.

WRF V4.2

4. SWAN
Wave conditions were calculated using SWAN with winddata from ANAL, GSM, and WRF (WSM3, WSM5, Goddard,Morrison, WDM6).
The results from prediction based on ANAL and WRF
showed overestimation compared to the observed data(Fig.8). Wave directions predicted from the models
showed discrepancy from the observed data until 12:00
JST September 4. This is thought to be due to the settingsof the SWAN model, which remains to be improved in thefuture studies.
Table.3 SWAN model settings.

case
WSM5

11

CAM5.1

Area1
Model

Area2
SWAN V41.31

Area3

Fig.7 Bathymetry.
ANAL

Fig.8 Observed and predicted wave conditions.
GSM

Goddard7Ferrier
12
SBU_YLIN
WSM6
By looking at the results of observed and predicted wind 20.1
0.05
0.005
Horizontal resolution [°]Kessler
8Goddard
13
WDM5speeds, simulations with most physical schemes showed a 3
10Time interval [minutes]
reduction in wind speed at Kansai International Airport (KIX) 49Milbrandt-Yau 14
WDM6Lin at al.
GEN3 JANSsen AGROW, BRE,Physics
and Kobe Airport at 14:00 JST September 4 (Fig.5). However, 5
WSM310Morrison
FRICTION, TRI, OFF FSHIFT
Goddard was able to calculate an increase in wind speed
1km
Bathymetry
Fig.9 Distribution of significant wave height at 12:20 JST September 4.
without such reduction at KIX. Overall, the maximum wind speeds were accurately calculated, despite the variations intimes at which the peaks occurred. Fig.6 shows the distribution of wind speed at which the maximum wind speed was
5. Conclusions
predicted at KIX. As a result, ANAL showed the strong wind exceeding 35m/s in Osaka Bay at 14:00 JST September 4.
Similarly, the schemes such as WSM3, WSM5, Goddard, Morrison, and WDM6 were able to predict strong winds in the We believe the advancement in the predictive ability of wind in Japan with such a highly complex coastal structures will
location, of which WSM3 and Goddard in particular were able to simulate the wind condition in the inner part of the bay. be of great use in the future wave protection and the development of offshore wind power generation.