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Frontiers of Earth Science

Front. Earth Sci.
RESEARCH ARTICLE
Typhoon parameter sensitivity of storm surge in the semi-enclosed Tokyo Bay
Md. Rezuanul ISLAM(), Hiroshi TAKAGI
School of Environment and Society, Tokyo Institute of Technology, Tokyo 152-8550, Japan
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Abstract

In this study, a storm surge model of the semi-enclosed Tokyo Bay was constructed to investigate its hydrodynamic response to major typhoon parameters, such as the point of landfall, approach angle, forward speed, size, and intensity. The typhoon simulation was validated for Typhoon Lan in 2017, and 31 hypothetical storm surge scenarios were generated to establish the sensitivity of peak surge height to the variation in typhoon parameters. The maximum storm surge height in the upper bay adjacent to the Tokyo Metropolitan Area was found to be highly sensitive to the forward speed and size of the passing typhoon. However, the importance of these parameters in disaster risk reduction has been largely overlooked by researchers and disaster managers. It was also determined that of the many hypothetical typhoon tracks evaluated, the slow passage of a large and intense typhoon transiting parallel to the longitudinal axis of Tokyo Bay, making landfall 25 km southwest, is most likely to cause a hazardous storm surge scenario in the upper-bay area. The results of this study are expected to be useful to disaster managers for advanced preparation against destructive storm surges.

Keywords storm surge      risk      semi-enclosed bay      typhoon parameters      parametric study      Typhoon Lan     
Corresponding Author(s): Md. Rezuanul ISLAM   
Just Accepted Date: 07 May 2020   Online First Date: 04 June 2020   
 Cite this article:   
Md. Rezuanul ISLAM,Hiroshi TAKAGI. Typhoon parameter sensitivity of storm surge in the semi-enclosed Tokyo Bay[J]. Front. Earth Sci., 04 June 2020. [Epub ahead of print] doi: 10.1007/s11707-020-0817-1.
 URL:  
http://journal.hep.com.cn/fesci/EN/10.1007/s11707-020-0817-1
http://journal.hep.com.cn/fesci/EN/Y/V/I/0
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Md. Rezuanul ISLAM
Hiroshi TAKAGI
Fig.1  Track of Typhoon Lan (2017) as it approached the shallow coastal areas of Tokyo Bay. The black place markers indicate measurement stations used in this study (Tide: Harumi, Yokohama, Chiba, and Kanaya; Wind: Haneda). The hypothetical typhoon track is described in Section 3.5 (Japan Oceanographic Data Center, 2000; Japan Aerospace Exploration Agency, 2015; Geospatial Information Authority of Japan, 2016; JMA, 2019b).
Typhoon parameters Typhoon Lan (JMA, 2019b): approach angle 140°, forward speed 65 km/h (very fast), Rmax of 89 km (very large)
Typhoon model Pressure: empirical estimation by Myers formula;
Wind: gradient winds considering super-gradient wind effect (Fujii and Mitsuta, 1986)
Fluid dynamics model Delft3D-FLOW ver. 6.02
Domain Spherical coordinate system, grid size: 50-m mesh
Bathymetry 50-m grid spacing
Tab.1  Numerical model settings for typhoon and storm surge simulation
Group Experiment Remarks
A Sensitivity to typhoon track
(21 cases)
Original Lan track, varied approach angle from 0° (A-1) to 180° (A-7) in 30° increments.
Shifted original Lan track 100 km eastward, varied approach angle from 0° (A-8) to 180° (A-14) in 30° increments.
Shifted original Lan track 150 km eastward, varied approach angle from 0° (A-15) to 180° (A-21) in 30° increments.
B Sensitivity to typhoon forward speed
(two cases)
Reduced forward speed to 36 km/h (by 45%, intermediate) (B-1) and 18 km/h (by 72%, very slow) (B-2).
C Sensitivity to typhoon size
(four cases)
Reduced Rmax to 55 (C-1), 43 (C-2), 26 (C-3), and 13 km (very small; C-4).
D Sensitivity to typhoon intensity
(two cases)
Decreased (D-1) and increased (D-2) original Lan intensity by 50%.
E Estimating possible maximum storm surge height (two cases) Landfall location: 25 km southwest of Tokyo Bay, q = 100°, forward speed of 18 km/h, Rmax = 89 km, Lan intensity increased by 50% at rising (E-1) and at falling tide periods (E-2).
Tab.2  Experimental conditions, hypothesized based on Typhoon Lan (2017) as the reference typhoon
Fig.2  (a) Simulated vs. observed wind speed at Haneda, Tokyo, and (b) estimated wind speed error ((simulated - observed)/observed wind speed × 100)). The red vertical line indicates the time of landfall of Typhoon Lan (2017).
Fig.3  Comparison of observed and simulated storm tide at (a) Harumi, (b) Chiba, and (c) Yokohama. The red vertical lines indicate the time of landfall of Typhoon Lan (2017).
Fig.4  Comparison of storm tide level for selected sets of landfall locations and approach angles: (a) original landfall (OL; 140° approach angle), (b) 100 km east of OL and 90° approach angle (Case A-11), and (c) 150 km east of OL and 90° approach angle (Case A-18). The red vertical lines indicate time of typhoon landfall.
Fig.5  Simulated wind diagram at landfall for the Harumi observation station during passage of typhoon (a) Case A-11 (landfall location 25 km southwest of Tokyo Bay, q = 90°); (b) Case A-13 (landfall location 25 km southwest of Tokyo Bay, q = 150°).
Fig.6  Comparison of (a) peak storm surge, (b) peak surge arrival time, and (c) duration of storm surge over 1 m for typhoons with different forward speeds. Note, the arriving times in (b) and higher surge durations in (c) are relative to those observed during the actual passage of Typhoon Lan.
Fig.7  Wind speed and direction during peak surge at Harumi for typhoon forward speed of 18 km/h
Fig.8  (a) Comparison of peak storm surge height (in m) for typhoons of different size (in terms of Rmax) and (b) observed peak storm surge (JMA, 2019c) vs. typhoon size (Rmax) at typhoon landfall at the Harumi observation station during 1979–2018. The dashed line shows the correlation gradient between the observed storm surge and Rmax.
Fig.9  Distribution of simulated water level during the passage of Typhoon Lan over Tokyo Bay varying with Rmax.
Fig.10  Storm surge hydrographs generated for (a) original Typhoon Lan, (b) 50% increase in Typhoon Lan wind speed, and (c) 50% decrease in Typhoon Lan wind speed. The red vertical lines indicate time of landfall.
Fig.11  Comparison of storm surge heights due to (a) Typhoon Lan; (b) a hypothetical typhoon (landfall location 25 km southwest of Tokyo Bay, q = 100°, forward speed of 18 km/h, Rmax = 89 km, Lan intensity increased by 50%); and (c) the hypothetical typhoon assumed by Ministry of Land, Infrastructure, Transport and Tourism (MLIT) (landfall location 25 km southwest of Tokyo Bay, q = 100°, forward speed of 50 km/h, intensity of 915 hPa at landfall time, sea level rise of 0.6 m due to global warming). The red vertical lines indicate time of landfall.
Fig.12  Tracks and 50 kt (26 m/s) wind radii (R50) of Typhoon Tip (1979), Typhoon Lan (2017), Typhoon Faxai (2019), and Typhoon Hagibis (2019) during their approach to Japan (JMA, 2019b).
Typhoon name (Year) Peak storm surge /m Landfall location from central bay axis in km (direction) Approach angle relative to coastline (degree in clockwise direction) Forward speed at landfall /(km·h-1) Radius of R50 at landfall /km Max. 10-min sustained wind speed at landfall
/(m·s-1)
Hagibis (2019) 1.38 50 (south-west) 130 37 333 41
Tip (1979) 1.25 430 (south-west) 135 75 370 36
Irma (1985) 1.20 80 (south-west) 130 69 232 33
Lan (2017) 1.20 125 (south-west) 140 65 389 41
Danas (2001) 1.12 over Tokyo Bay 120 24 56 28
Roke (2011) 1.14 190 (south-west) 140 46 222 41
Fitow (2007) 1.04 50 (south-west) 110 23 167 33
Faxai (2019) 1.01 over Tokyo Bay 135 24 93 41
Melor (2009) 0.87 250 (south-west) 145 58 222 36
Jelawat (2012) 0.86 230 (south-west) 130 50 222 36
Tab.3  Top ten typhoons (1979–2009) impacting upper Tokyo Bay (i.e., Harumi) according to resultant maximum storm surge (JMA, 2019b, 2019c)
1 J D Bricker, V Roeber, H Tanaka (2016). Storm surge protection by tsunami seawalls in Sendai, Japan. In: Proceedings of 35th International Conference on Coastal Engineering, Antalya, Turkey
2 Deltares (2011). Delft3D-FLOW – Simulation of Multi- Dimensional Hydrodynamic Flows and Transport Phenomena, Including Sediments. User Manual Delft3DFLOW, The Netherlands, 690
3 Digital Typhoon (2019). Typhoon Damage List (Available at )
4 G D Egbert, S Y Erofeeva (2002). Efficient inverse modeling of barotropic ocean tides. J Atmos Ocean Technol, 19(2): 183–204
https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2
5 T Fujii, Y Mitsuta (1986). Synthesis of a stochastic typhoon model and simulation of typhoon winds. In: Disaster Prevention Research Institute Annuals, 29, B-1, 229–239 (in Japanese)
6 Geospatial Information Authority of Japan (2016). GSI Japan Global Map Site. (Available at )
7 M Higaki, H Hironori, F Nozaki, (2009) Outline of the storm surge prediction model at the Japan Meteorological Agency. In: The Technical Review- RSMC Tokyo-Typhoon Center, 25–38
8 K Hirano, S Bunya, T Murakami, S Iizuka, T Nakatani, S Shimokawa, K Kawasaki (2014). Prediction of typhoon storm surge flood in Tokyo Bay using unstructured model ADCIRC under global warming scenario. In: Proceedings of 4th Joint US-European Fluids Engineering Division Summer Meeting and 12th International Conference on Nanochannels, Microchannels, and Minichannels. Chicago, Illinois, USA: ASME.
9 S Hoshino, M Esteban, T Mikami, H Takagi, T Shibayama (2016). Estimation of increase in storm surge damage due to climate change and sea level rise in the Greater Tokyo area. Nat Hazards, 80(1): 539–565
https://doi.org/10.1007/s11069-015-1983-4
10 J L Irish, D T Resio, J J Ratcliff (2008). The influence of storm size on hurricane surge. J Phys Oceanogr, 38(9): 2003–2013
https://doi.org/10.1175/2008JPO3727.1
11 M R Islam, H Takagi, L T Anh, A Takahashi, K Bowei (2018). 2017 Typhoon Lan reconnaissance field survey in coasts of Kanto Region, Japan. Journal of Japan Society of Civil Engineers,Ser. B3. Ocean Eng, 74(2) doi:10.2208/jscejoe.74.I_593
12 M R Islam, H Takagi (2020). Statistical significance of tropical cyclone forward speed on storm surge generation: retrospective analysis of best track and tidal data in Japan. Georisk. Assessment and Management of Risk for Engineered Systems and Geohazards, doi:10.1080/17499518.2020.1756345
13 Japan Aerospace Exploration Agency (2015). 30 m World Elevation Data Site. (Available at )
14 Japan Meteorological Agency (2019a). Typhoon statistics (in Japanese). (Available at )
15 Japan Meteorological Agency (2019b). Typhoon Best Track Data Site. (Available at)
16 Japan Meteorological Agency (2019c). Tidal Observation Data Site (in Japanese). (Available at )
17 Japan Meteorological Agency (2019d). Past weather data (in Japanese). (Available at )
18 Japan Oceanographic Data Center (2000). 500 m Gridded Bathymetric Feature Data around Japan. (Available at)
19 C P Jelesnianski (1972). SPLASH (Special Program to List Amplitudes of Surges from Hurricanes): 1. Landfall storms. In NOAA Technical Memorandum NWS TDL-46. Silver Spring.
20 T A Le, H Takagi, M Heidarzadeh, Y Takata, A Takahashi (2019). Field surveys and numerical simulation of the 2018 Typhoon Jebi: impact of high waves and storm surge in semi-enclosed Osaka Bay, Japan. Pure Appl Geophys, 176(10): 4139–4160
https://doi.org/10.1007/s00024-019-02295-0
21 R Marsooli, N Lin (2018). Numerical modeling of historical storm tides and waves and their interactions along the U.S. East and Gulf coasts. J Geophys Res Oceans, 123(5): 3844–3874
https://doi.org/10.1029/2017JC013434
22 Ministry of Health Labour and Welfare (Japan) (2018). Statistics and other data. (Available at)
23 Ministry of Land Infrastructure and Transport (Japan) (2009). Estimation of large scale inundation scenario by storm surge at Tokyo Bay (in Japanese). (Available at )
24 S Nakajo, H Fujiki, S Kim, N Mori (2018).Sensitivity of tropical cyclone track to assessment of severe storm surge event at tokyo bay. In: Proceedings of 36th International Conference on Coastal Engineering, Baltimore, Maryland, USA
25 H F Needham, B D Keim (2011). Storm surge: Physical processes and an impact scale. In: Lupo E, ed. Recent Hurricane Research—Climate, Dynamics, and Societal Impacts. Croatia: Intech Open Access, 386 –394
26 H F Needham, B D Keim (2013). Correlating storm surge heights with tropical cyclone winds at and before landfall. Earth Interact, 18: 1–26 doi:10.1175/2013EI000527.1
27 F Omori (1918). Tsunami in Tokyo Bay. In: Earthquake Investigation Committee Report, 89, 19–48 (in Japanese).
28 J L Rego, C Li (2009). On the importance of the forward speed of hurricanes in storm surge forecasting: a numerical study. Geophys Res Lett, 36(7): L07609
https://doi.org/10.1029/2008GL036953
29 J L Rego, C Li (2010). Nonlinear terms in storm surge predictions: Effects of tide and shelf geometry with case study from Hurricane Rita. J Geophys Res, 115(C6): 1–19
https://doi.org/10.1029/2009JC005285
30 A G Sebastian, J M Proft, J C Dietrich, W Du, P B Bedient, C N Dawson (2014). Characterizing hurricane storm surge behavior in Galveston Bay using the SWAN+ ADCIRC model. Coast Eng, 88: 171–181
https://doi.org/10.1016/j.coastaleng.2014.03.002
31 H Song, C Kuang, J Gu, Q Zou, H Liang, X Sun, Z Ma (2020). Nonlinear tide-surge-wave interaction at a shallow coast with large scale sequential harbor constructions. Estuar Coast Shelf Sci, 233: 1–15
https://doi.org/10.1016/j.ecss.2019.106543
32 J L A Soria, A D Switzer, C L Villanoy, H M Fritz, P H T Bilgera, O C Cabrera, F P Siringan, Y Y S Maria, R D Ramos, I Q Fernandez (2016). Repeat storm surge disasters of Typhoon Haiyan and its 1897 predecessor in the Philippines. Bull Am Meteorol Soc, 97(1): 31–48
https://doi.org/10.1175/BAMS-D-14-00245.1
33 H Takagi, N D Thao, M Esteban, T T Tam, H L Knaepen, T Mikami (2012). Assessment of the coastal disaster risks in Southern Vietnam. Journal of Japan Society of Civil Engineering, B3. Ocean Eng, 68(2): 888–893 doi:10.2208/jscejoe.68.I_888
34 H Takagi, N D Thao, M Esteban (2014). Tropical cyclones and storm surges in Southern Vietnam. In: Thao N D, Takagi H, Esteban M, eds. Coastal Disasters and Climate Change in Vietnam. Elsevier. 3 –16
35 H Takagi, S Li, M de Leon, M Esteban, T Mikami, R Matsumaru, T Shibayama, R Nakamura (2016a). Storm surge and evacuation in urban areas during the peak of a storm. Coast Eng, 108: 1–9
https://doi.org/10.1016/j.coastaleng.2015.11.002
36 H Takagi, W Wu (2016b). Maximum wind radius estimated by the 50 kt radius: improvement of storm surge forecasting over the Western North Pacific. Nat Hazards Earth Syst Sci, 16(3): 705–717
https://doi.org/10.5194/nhess-16-705-2016
37 H Takagi, M Esteban, T Shibayama, T Mikami, R Matsumaru, M De Leon, N D Thao, T Oyama, R Nakamura (2017). Track analysis, simulation and field survey of the 2013 Typhoon Haiyan storm surge. J Flood Risk Manag, 10(1): 42–52
https://doi.org/10.1111/jfr3.12136
38 H Takagi, Y Xiong, F Furukawa (2018). Track analysis and storm surge investigation of 2017 Typhoon Hato: were the warning signals issued in Macau and Hong Kong timed appropriately? Georisk. Assessment and Management of Risk for Engineered Systems and Geohazards, 12(4): 297–307
39 H Takagi, Y Xiong, J Fan (2019). Public perception of typhoon signals and response in Macau: did disaster response improve between the 2017 Hato and 2018 Mangkhut. Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards.
40 H Takagi, M R Islam, L T Anh, A Takahashi, T Sugiu, F Furukawa (2020). Investigation of high wave damage caused by 2019 Typhoon Faxai in Kanto region and wave hindcast in Tokyo Bay. Journal of Japan Society of Civil Engineers, Ser. B3. Ocean Eng, 76(1) doi:10.2208/jscejoe.76.1_12
41 A Thomas, J C Dietrich, T G Asher, M Bell, B O Blanton, J H Copeland, A T Cox, C N Dawson, J G Fleming, R A Luettich (2019). Influence of storm timing and forward speed on tides and storm surge during Hurricane Matthew. Ocean Model, 137: 1–19
https://doi.org/10.1016/j.ocemod.2019.03.004
42 R H Weisberg, L Zheng (2006). Hurricane storm surge simulations for Tampa Bay. Estuaries Coasts, 29(6): 899–913
https://doi.org/10.1007/BF02798649
43 C Zhang, C Li (2019). Effects of hurricane forward speed and approach angle on storm surges: an idealized numerical experiment. Acta Oceanol Sin, 38(7): 48–56
https://doi.org/10.1007/s13131-018-1081-z
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