Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 2.281 IF 2.281
  • IF 5-year value: 2.693 IF 5-year 2.693
  • CiteScore value: 2.43 CiteScore 2.43
  • SNIP value: 1.193 SNIP 1.193
  • SJR value: 0.965 SJR 0.965
  • IPP value: 2.31 IPP 2.31
  • h5-index value: 40 h5-index 40
  • Scimago H index value: 73 Scimago H index 73
Volume 16, issue 3 | Copyright
Nat. Hazards Earth Syst. Sci., 16, 705-717, 2016
https://doi.org/10.5194/nhess-16-705-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 11 Mar 2016

Research article | 11 Mar 2016

Maximum wind radius estimated by the 50 kt radius: improvement of storm surge forecasting over the western North Pacific

Hiroshi Takagi and Wenjie Wu
Related authors
1997 Typhoon Linda Storm Surge and People's Awareness 20 Years Later: Uninvestigated Worst Storm Event in the Mekong Delta
Hiroshi Takagi, Le Tuan Anh, and Nguyen Danh Thao
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2017-365,https://doi.org/10.5194/nhess-2017-365, 2017
Publication in NHESS not foreseen
Design Considerations of Artificial Mangrove Embankments for Mitigating Coastal Floods – Adapting to Sea-level Rise and Long-term Subsidence
Hiroshi Takagi
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2017-61,https://doi.org/10.5194/nhess-2017-61, 2017
Revised manuscript not accepted
Mangrove forest against dyke-break-induced tsunami on rapidly subsiding coasts
Hiroshi Takagi, Takahito Mikami, Daisuke Fujii, Miguel Esteban, and Shota Kurobe
Nat. Hazards Earth Syst. Sci., 16, 1629-1638, https://doi.org/10.5194/nhess-16-1629-2016,https://doi.org/10.5194/nhess-16-1629-2016, 2016
Related subject area
Sea, Ocean and Coastal Hazards
Combining probability distributions of sea level variations and wave run-up to evaluate coastal flooding risks
Ulpu Leijala, Jan-Victor Björkqvist, Milla M. Johansson, Havu Pellikka, Lauri Laakso, and Kimmo K. Kahma
Nat. Hazards Earth Syst. Sci., 18, 2785-2799, https://doi.org/10.5194/nhess-18-2785-2018,https://doi.org/10.5194/nhess-18-2785-2018, 2018
Implementation and validation of a new operational wave forecasting system of the Mediterranean Monitoring and Forecasting Centre in the framework of the Copernicus Marine Environment Monitoring Service
Michalis Ravdas, Anna Zacharioudaki, and Gerasimos Korres
Nat. Hazards Earth Syst. Sci., 18, 2675-2695, https://doi.org/10.5194/nhess-18-2675-2018,https://doi.org/10.5194/nhess-18-2675-2018, 2018
Tree-based mesh-refinement GPU-accelerated tsunami simulator for real-time operation
Marlon Arce Acuña and Takayuki Aoki
Nat. Hazards Earth Syst. Sci., 18, 2561-2602, https://doi.org/10.5194/nhess-18-2561-2018,https://doi.org/10.5194/nhess-18-2561-2018, 2018
Extreme water levels, waves and coastal impacts during a severe tropical cyclone in northeastern Australia: a case study for cross-sector data sharing
Thomas R. Mortlock, Daryl Metters, Joshua Soderholm, John Maher, Serena B. Lee, Geoffrey Boughton, Nigel Stewart, Elisa Zavadil, and Ian D. Goodwin
Nat. Hazards Earth Syst. Sci., 18, 2603-2623, https://doi.org/10.5194/nhess-18-2603-2018,https://doi.org/10.5194/nhess-18-2603-2018, 2018
A comparison of a two-dimensional depth-averaged flow model and a three-dimensional RANS model for predicting tsunami inundation and fluid forces
Xinsheng Qin, Michael Motley, Randall LeVeque, Frank Gonzalez, and Kaspar Mueller
Nat. Hazards Earth Syst. Sci., 18, 2489-2506, https://doi.org/10.5194/nhess-18-2489-2018,https://doi.org/10.5194/nhess-18-2489-2018, 2018
Cited articles
Akinson, G. D. and Holliday C. R.: Tropical cyclone minimum sea level pressure/maximum sustained wind relationship for the Western North Pacific, Mon. Weather Rev., 105, 421–427, 1977.
Bricker, J. D., Takagi, H., Mas, E., Kure, S., Adriano, B., Yi, C., and Roeber, V.: Spatial Variation of Damage due to Storm Surge and Waves during Typhoon Haiyan in the Philippines, J. Jpn. Soc. Civil Eng., 70, 231–235, 2014.
Dvorak, V. F.: Tropical cyclone intensity analysis and forecasting from satellite visible or enhanced infrared imagery, NOAA NESS, Applications Laboratory Training Notes, 42 pp., 1982.
Dvorak, V. F.: Tropical cyclone intensity analysis using satellite data, NOAA Tech. Rep. 11, 45 pp., 1984.
Elsner, J. B. and Jagger, T. H.: Hurricane Climatology: a modern statistical guide using R, Oxford University Press, New York, 373 pp., 2013.
Publications Copernicus
Download
Short summary
We proposed an Rmax estimation method based on the radius of the 50 knot wind (R50). The data obtained during the passage of strong typhoons by a meteorological station network in the Japanese archipelago enabled us to derive the following simple formula, Rmax = 0.23 R50. The proposed method is expected to increase the reliability of storm surge prediction and contribute to disaster risk management, particularly in the western North Pacific.
We proposed an Rmax estimation method based on the radius of the 50 knot wind (R50). The data...
Citation
Share