scholarly journals A new tropical cyclone surge index incorporating the effects of coastal geometry, bathymetry and storm information

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Md. Rezuanul Islam ◽  
Chia-Ying Lee ◽  
Kyle T. Mandli ◽  
Hiroshi Takagi
Keyword(s):  
Wind Speed ◽  
Tropical Cyclone ◽  
Retrospective Analysis ◽  
Real Time ◽  
Numerical Computation ◽  
Storm Surge ◽  
Public Awareness ◽  
Translation Speed ◽  
Potential Index ◽  
Using Data

AbstractThis study presents a new storm surge hazard potential index (SSHPI) for estimating tropical cyclone (TC) induced peak surge levels at a coast. The SSHPI incorporates parameters that are often readily available at real-time: intensity in 10-min maximum wind speed, radius of 50-kt wind, translation speed, coastal geometry, and bathymetry information. The inclusion of translation speed and coastal geometry information lead to improvements of the SSHPI to other existing surge indices. A retrospective analysis of SSHPI using data from 1978–2019 in Japan suggests that this index captures historical events reasonably well. In particular, it explains ~ 66% of the observed variance and ~ 74% for those induced by TCs whose landfall intensity was larger than 79-kt. The performance of SSHPI is not sensitive to the type of coastal geometry (open coasts or semi-enclosed bays). Such a prediction methodology can decrease numerical computation requirements, improve public awareness of surge hazards, and may also be useful for communicating surge risk.

scholarly journals A new tropical cyclone surge index incorporating the effects of coastal geometry, bathymetry and storm information

2021 ◽  
Author(s):  
Md. Islam ◽  
Chia-Ying Lee ◽  
Kyle T. Mandli ◽  
Hiroshi Takagi
Keyword(s):  
Wind Speed ◽  
Tropical Cyclone ◽  
Retrospective Analysis ◽  
Real Time ◽  
Numerical Computation ◽  
Storm Surge ◽  
Public Awareness ◽  
Translation Speed ◽  
Potential Index ◽  
Using Data

This study presents a new storm surge hazard potential index (SSHPI) for estimating tropical cyclone (TC) induced maximum surge levels at a coast. The SSHPI incorporates parameters that are often readily available at real-time: intensity in 10-minute maximum wind speed, radius of 50-kt wind, translation speed, coastal geometry, and bathymetry information. The inclusion of translation speed and coastal geometry information lead to improvements of the SSHPI to other existing surge indices. A retrospective analysis of SSHPI using data from 1978–2019 in Japan suggests that this index captures historical events reasonably well. In particular, it explains ~66% of the observed variance and ~74% for those induced by TCs whose landfall intensity was larger than 79-kt. The performance of SSHPI is not sensitive to the type of coastal geometry (open coasts or semi-enclosed bays). Such a prediction methodology can decrease numerical computation requirements, improve public awareness of surge hazards, and may also be useful for communicating surge risk.

EFFECTS OF MAXIMUM WIND SPEED RADIUS AND TRANSLATION SPEED OF SCENARIO TYPHOON ON STORM SURGE AND WAVE

2018 ◽  
Vol 74 (2) ◽  
pp. I_583-I_588
Author(s):  
Masafumi KIMIZUKA ◽  
Tomotsuka TAKAYAMA ◽  
Hiroyasu KAWAI ◽  
Masafumi MIYATA ◽  
Katsuya HIRAYAMA ◽  
...  
Keyword(s):  
Wind Speed ◽  
Storm Surge ◽  
Maximum Wind Speed ◽  
Translation Speed ◽  
Maximum Wind

scholarly journals Tropical cyclone wind speed constraints from resultant storm surge deposition: A 2500 year reconstruction of hurricane activity from St. Marks, FL

2013 ◽  
Vol 14 (8) ◽  
pp. 2993-3008 ◽  
Author(s):  
Christine M. Brandon ◽  
Jonathan D. Woodruff ◽  
D. Phil Lane ◽  
Jeffrey P. Donnelly
Keyword(s):  
Wind Speed ◽  
Tropical Cyclone ◽  
Storm Surge ◽  
Hurricane Activity

scholarly journals Effect of Translation Speed and Scale of Tropical Cyclone on Storm Surge in Yatsushiro Bay

2014 ◽  
Vol 70 (2) ◽  
pp. I_256-I_260
Author(s):  
Sota NAKAJO ◽  
Soo Youl KIM ◽  
Nobuhito MORI ◽  
Tomohiro YASUDA ◽  
Hajime MASE ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Storm Surge ◽  
Translation Speed ◽  
Yatsushiro Bay

scholarly journals Quantifying Interagency Differences in Tropical Cyclone Best-Track Wind Speed Estimates

2010 ◽  
Vol 138 (4) ◽  
pp. 1459-1473 ◽  
Author(s):  
Kenneth R. Knapp ◽  
Michael C. Kruk
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Tropical Cyclone ◽  
Temporal Changes ◽  
Data Availability ◽  
Spatially Inhomogeneous ◽  
The World ◽  
Using Data ◽  
Over Time

Abstract Numerous agencies around the world perform postseason analysis of tropical cyclone position and intensity, a process described as “best tracking.” However, this process is temporally and spatially inhomogeneous because data availability, operational techniques, and knowledge have changed over time and differ among agencies. The net result is that positions and intensities often vary for any given storm for different agencies. In light of these differences, it is imperative to analyze and document the interagency differences in tropical cyclone intensities. To that end, maximum sustained winds from different agencies were compared using data from the International Best Track Archive for Climate Stewardship (IBTrACS) global tropical cyclone dataset. Comparisons were made for a recent 5-yr period to investigate the current differences, where linear systematic differences were evident. Time series of the comparisons also showed temporal changes in the systematic differences, which suggest changes in operational procedures. Initial attempts were made to normalize maximum sustained winds by correcting for known changes in operational procedures. The result was mixed, in that the adjustments removed some but not all of the systematic differences. This suggests that more details on operational procedures are needed and that a complete reanalysis of tropical cyclone intensities should be performed.

scholarly journals Spatial Relation between Wind Stress and Storm Surge during Hurricanes Laura and Delta in 2020

2021 ◽  
Vol 02 (03) ◽  
pp. 1-1
Author(s):  
Shih-Ang Hsu ◽  
Keyword(s):  
Wind Speed ◽  
Tropical Cyclone ◽  
Water Level ◽  
Storm Surge ◽  
Surface Analysis ◽  
Wind Stress ◽  
Spatial Relation ◽  
High Water ◽  
Mesoscale Meteorology ◽  
First Approximation

Spatial relation between wind stress and storm surge during two hurricanes in 2020 is investigated. It is found that, during Laura’s landfall, the area inside of 65 knots (34 m s -1) isotach or line of equal wind speed can produce up to 18 ft (5.5 m) inundation and during Delta, the area inside of 50 knots (26 m s -1) up to 11 ft (3.3 m) high water level above the ground. The tropical cyclone (TC) surface analysis near landfall by the Regional and Mesoscale Meteorology Branch (RAMMB) is recommended as a first approximation for coastal environmental and engineering applications during a TC.

scholarly journals A Tropical Cyclone Rapid Intensification Prediction Aid for the Joint Typhoon Warning Center’s Areas of Responsibility

2020 ◽  
Vol 35 (3) ◽  
pp. 1173-1185 ◽  
Author(s):  
John A. Knaff ◽  
Charles R. Sampson ◽  
Brian R. Strahl
Keyword(s):  
Tropical Cyclone ◽  
Real Time ◽  
North Pacific ◽  
Input Data ◽  
Western North Pacific ◽  
Rapid Intensification ◽  
Probabilistic Forecasts ◽  
Time Periods ◽  
Using Data ◽  
Joint Typhoon Warning Center

Abstract In late 2017, the Rapid Intensification Prediction Aid (RIPA) was transitioned to operations at the Joint Typhoon Warning Center (JTWC). RIPA probabilistically predicts seven rapid intensification (RI) thresholds over three separate time periods: 25-, 30-, 35-, and 40-kt (1 kt ≈ 0.51 m s−1) increases in 24 h (RI25, RI30, RI35, RI40); 45- and 55-kt increases in 36 h (RI45 and RI55); and 70-kt increases in 48 h (RI70). RIPA’s probabilistic forecasts are also used to produce deterministic forecasts when probabilities exceed 40%, and the latter are included as members of the operational intensity consensus forecast aid. RIPA, initially designed for the western North Pacific, performed remarkably well in all JTWC areas of responsibility (AOR) and is now incorporated into JTWC’s ever improving suite of intensity forecast guidance. Even so, making real-time operational RIPA forecasts exposed some methodological weaknesses such as overprediction of RI for weak/disorganized systems (i.e., systems with maximum winds less than 35 kt), prediction of RI during landfall, input data reliability, and statistical inconsistencies. Modifications to the deterministic forecasts that address these issues are presented, and newly derived and more statistically consistent models are developed using data from all of JTWC’s AORs. The updated RIPA is tested as it would be run in operations and verified using a 2-yr (2018–19) independent sample. The performance from this test indicates the new RIPA—when compared to its predecessor—has improved probabilistic verification statistics, and similar deterministic skill while using fewer predictors to make forecasts.

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