scholarly journals COUPLED MODELING OF WAVE AND STORM SURGE FOR EXPLOSIVE CYCLONE 2014 IN THE EAST COAST OF HOKKAIDO

Author(s):  
Kenzo KUMAGAI ◽  
Sooyoul KIM ◽  
Daiki TSUJIO ◽  
Hajime MASE ◽  
Takahito Tsuji
2013 ◽  
Vol 69 (2) ◽  
pp. I_976-I_981
Author(s):  
Yoshitaka MATSUZAKI ◽  
Shigeo TAKAHASHI ◽  
Masayuki BANNO ◽  
Tomotsuka TAKAYAMA ◽  
Kazuhiro GODA

Author(s):  
Aliasghar Golshani ◽  
Will Thurston ◽  
Deborah J. Abbs ◽  
Greg Stuart ◽  
Rodger Tominson

1963 ◽  
Vol 25 (2) ◽  
pp. 12-13
Author(s):  
G COLE ◽  
J R ROSSITER ◽  
G W LENNON ◽  
G E R DEACON ◽  
J PROUDMAN

2009 ◽  
Vol 48 (11) ◽  
pp. 2320-2330 ◽  
Author(s):  
H. Salmun ◽  
A. Molod ◽  
F. S. Buonaiuto ◽  
K. Wisniewska ◽  
K. C. Clarke

Abstract New York coastal regions are frequently exposed to winter extratropical storm systems that exhibit a wide range of local impacts. Studies of these systems either have used localized water-level or beach erosion data to identify and characterize the storms or have used meteorological conditions from reanalysis data to provide a general regional “climatology” of storms. The use of meteorological conditions to identify these storms allows an independent assessment of impacts on the coastal environment and therefore can be used to predict the impacts. However, the intensity of these storms can exhibit substantial spatial variability that may not be captured by the relatively large scales of the studies using reanalysis data, and this fact may affect the localized assessment of storm impact on the coastal communities. A method that uses data from National Data Buoy Center stations in the New York metropolitan area to identify East Coast cool-weather storms (ECCSs) and to describe their climatological characteristics is presented. An assessment of the presence of storm conditions and a three-level intensity scale was developed using surface pressure data as measured at the buoys. This study identified ECCSs during the period from 1977 through 2007 and developed storm climatologies for each level of storm intensity. General agreement with established climatologies demonstrated the robustness of the method. The impact of the storms on the coastal environment was assessed by computing “storm average” values of storm-surge data and by examining beach erosion along the south shore of Long Island, New York. A regression analysis demonstrated that the best storm-surge predictor is based on measurements of significant wave height at a nearby buoy.


Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 756
Author(s):  
Robert Mendelsohn

The National Atmospheric and Oceanic Administration (NOAA) calculates the surge probability distribution along the coast from their long-term tidal stations. This process is sufficient for predicting the surge from common storms but tends to underestimate large surges. Across 23 long-term tidal stations along the East Coast of the United States, 100-year surges were observed 49 times, although they should have occurred only 23 times. We hypothesize that these 100-year surges are not the tail outcome from common storms but are actually caused by major hurricanes. Matching these 100-year surges with major hurricanes revealed that major hurricanes caused 43 of the 49 surges. We consequently suggest a revised approach to estimating the surge probability distribution. We used tidal data to estimate the probability of common surges but analyzed major hurricane surges separately, using the return rate of major hurricanes and the observed surge from each major hurricane to predict hurricane surges. The revision reveals that expected coastal flooding damage is higher than we thought, especially in the southeast United States.


2019 ◽  
Vol 177 (6) ◽  
pp. 2993-3012 ◽  
Author(s):  
P. L. N. Murty ◽  
A. D. Rao ◽  
K. Siva Srinivas ◽  
E. Pattabhi Rama Rao ◽  
Prasad K. Bhaskaran

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