scholarly journals Integrating storm surge modeling with traffic data analysis to evaluate the effectiveness of hurricane evacuation

2021 ◽  
Author(s):  
Wenrui Huang ◽  
Kai Yin ◽  
Mahyar Ghorbanzadeh ◽  
Eren Ozguven ◽  
Sudong Xu ◽  
...  
Keyword(s):  
Wind Speed ◽  
Storm Surge ◽  
South Florida ◽  
Traffic Data ◽  
Maximum Wind ◽  
South West ◽  
Storm Surge Modeling ◽  
Hurricane Forecasting ◽  
Evacuation Traffic ◽  
Hurricane Irma

AbstractAn integrated storm surge modeling and traffic analysis were conducted in this study to assess the effectiveness of hurricane evacuations through a case study of Hurricane Irma. The Category 5 hurricane in 2017 caused a record evacuation with an estimated 6.8 million people relocating statewide in Florida. The Advanced Circulation (ADCIRC) model was applied to simulate storm tides during the hurricane event. Model validations indicated that simulated pressures, winds, and storm surge compared well with observations. Model simulated storm tides and winds were used to estimate the area affected by Hurricane Irma. Results showed that the storm surge and strong wind mainly affected coastal counties in south-west Florida. Only moderate storm tides (maximum about 2.5 m) and maximum wind speed about 115 mph were shown in both model simulations and Federal Emergency Management Agency (FEMA) post-hurricane assessment near the area of hurricane landfall. Storm surges did not rise to the 100-year flood elevation level. The maximum wind was much below the design wind speed of 150–170 mph (Category 5) as defined in Florida Building Code (FBC) for south Florida coastal areas. Compared with the total population of about 2.25 million in the six coastal counties affected by storm surge and Category 1–3 wind, the statewide evacuation of approximately 6.8 million people was found to be an over-evacuation due mainly to the uncertainty of hurricane path, which shifted from south-east to south-west Florida. The uncertainty of hurricane tracks made it difficult to predict the appropriate storm surge inundation zone for evacuation. Traffic data were used to analyze the evacuation traffic patterns. In south-east Florida, evacuation traffic started 4 days before the hurricane’s arrival. However, the hurricane path shifted and eventually landed in south-west Florida, which caused a high level of evacuation traffic in south-west Florida. Over-evacuation caused Evacuation Traffic Index (ETI) to increase to 200% above normal conditions in some sections of highways, which reduced the effectiveness of evacuation. Results from this study show that evacuation efficiency can be improved in the future by more accurate hurricane forecasting, better public awareness of real-time storm surge and wind as well as integrated storm surge and evacuation modeling for quick response to the uncertainty of hurricane forecasting.

scholarly journals Integrating Evacuation and Storm Surge Modeling Considering Potential Hurricane Tracks: The Case of Hurricane Irma in Southeast Florida

2021 ◽  
Vol 10 (10) ◽  
pp. 661
Author(s):  
Mahyar Ghorbanzadeh ◽  
Linoj Vijayan ◽  
Jieya Yang ◽  
Eren Erman Ozguven ◽  
Wenrui Huang ◽  
...  
Keyword(s):  
Storm Surge ◽  
Element Model ◽  
South Florida ◽  
Individual Decision ◽  
Evacuation Modeling ◽  
Case Study Analysis ◽  
Storm Surge Modeling ◽  
Shelter Availability ◽  
Hurricane Irma

Hurricane Irma, in 2017, made an unusual landfall in South Florida and the unpredictability of the hurricane’s path challenged the evacuation process seriously and left many evacuees clueless. It was likely to hit Southeast Florida but suddenly shifted its path to the west coast of the peninsula, where the evacuation process had to change immediately without any time for individual decision-making. As such, this study aimed to develop a methodology to integrate evacuation and storm surge modeling with a case study analysis of Irma hitting Southeast Florida. For this purpose, a coupled storm surge and wave finite element model (ADCIRC+SWAN) was used to determine the inundation zones and roadways with higher inundation risk in Broward, Miami-Dade, and Palm Beach counties in Southeast Florida. This was fed into the evacuation modeling to estimate the regional clearance times and shelter availability in the selected counties. Findings show that it takes approximately three days to safely evacuate the populations in the study area. Modeling such integrated simulations before the hurricane hit the state could provide the information people in hurricane-prone areas need to decide to evacuate or not before the mandatory evacuation order is given.

scholarly journals CONSIDERATION OF STORM SURGE CAUSED BY HURRICANE IRMA BASED ON STOC-WRF COUPLING MODEL

2018 ◽  
pp. 55
Author(s):  
Taro Arikawa ◽  
Katsumi Seki ◽  
Takuto Haga ◽  
Kazuhiro Fujiwara
Keyword(s):  
Global Warming ◽  
Wind Speed ◽  
Atlantic Ocean ◽  
Storm Surge ◽  
Coupling Model ◽  
Local Area ◽  
Maximum Wind Speed ◽  
Maximum Wind ◽  
Set Up ◽  
Hurricane Irma

Hurricane Irma occurred in the Atlantic Ocean in 2017. It has developed to Category 5, the maximum wind speed is about 82.7 [m/s], minimum central pressure is about 914 [hPa]. Because there is concern that the risk of storm surge due to global warming is increasing, it is important to predict storm surge for prevention of the disasters. For that purpose, it is important to construct a method that can predict local area phenomena. Therefore, in this study, to achieve that purpose, a methodology of downscaling the mesoscale data is developed by using the STOC-ML and WRF, and the applicability is verified to the storm surge due to Irma. In addition, wave set up is also estimated using SWAN and the characteristics of Irma is considered.

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 Evacuee Perception of Geophysical Hazards for Hurricane Irma

2019 ◽  
Vol 11 (1) ◽  
pp. 217-227 ◽  
Author(s):  
Jason Senkbeil ◽  
Jennifer Collins ◽  
Jacob Reed
Keyword(s):  
Wind Speed ◽  
Storm Surge ◽  
Wind Speeds ◽  
Wind Gusts ◽  
Different Types ◽  
High Concern ◽  
Rest Areas ◽  
The Mean ◽  
Atlantic Hurricanes ◽  
Hurricane Irma

Abstract Hurricane Irma was one of the strongest Atlantic hurricanes in history before landfall and caused a large evacuation. A total of 155 evacuees at interstate rest areas were asked to rank their concern about damage at their residence for six different geophysical hurricane hazards. Additionally, they were asked about their perceived maximum wind speeds (PMWS) and the wind speeds at which they thought damage would occur (DW) at their residence. These wind speeds were then compared to the actual peak wind gusts (APG) nearest to each resident’s location. Results show a significantly greater concern for wind and storm size, compared to other hazards (tornadoes, rainfall/flooding, storm surge, falling trees). The mean PMWS of evacuees was greater than the mean APG, suggesting widespread misperception of wind speeds. Furthermore, the mean APG was less than the mean DW, and the mean PMWS was also higher than the DW. Additional tests found no significant differences in wind perception between residents with previous storm experiences and no experience, and no significant differences between those who resided in mandatory evacuation zip codes and those who did not. These results suggest that wind speed risk is poorly understood, even though it is a high concern for evacuees from hurricanes. The communication of wind speed risk in forecasts should possibly be modified by placing greater emphasis on postlandfall impacts, wind speed decay after landfall, and wind speeds that cause damage to different types of residences.

scholarly journals Hurricane Irma Simulation at South Florida Using the Parallel CEST Model

2021 ◽  
Vol 3 ◽  
Author(s):  
Yuepeng Li ◽  
Qiang Chen ◽  
Dave M. Kelly ◽  
Keqi Zhang
Keyword(s):  
Storm Surge ◽  
Message Passing ◽  
High Performance ◽  
Message Passing Interface ◽  
Field Measurements ◽  
South Florida ◽  
Computational Time ◽  
Linear Speedup ◽  
Lagrangian Advection ◽  
Hurricane Irma

In this study, a parallel extension of the Coastal and Estuarine Storm Tide (CEST) model is developed and applied to simulate the storm surge tide at South Florida induced by hurricane Irma occurred in 2017. An improvement is also made to the existing advection algorithm in CEST. This is achieved through the introduction of high-order, monotone Semi-Lagrangian advection. Distributed memory parallelization is developed via the Message Passing Interface (MPI) library. The parallel CEST model can therefore be run efficiently on machines ranging from multicore laptops to massively High Performance Computing (HPC) system. The principle advantage of being able to run the CEST model on multiple cores is that relatively low run-time is possible for real world storm surge simulations on grids with high resolution, especially in the locality where the hurricane makes landfall. The computational time is critical for storm surge model forecast to finish simulations in 30 min, and results are available to users before the arrival of the next advisory. In this study, simulation of hurricane Irma induced storm surge was approximately 22 min for 4 day simulation, with the results validated by field measurements. Further efficiency analysis reveals that the parallel CEST model can achieve linear speedup when the number of processors is not very large.

scholarly journals The Effect of the Surface Wind Field Representation in the Operational Storm Surge Model of the National Hurricane Center

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 193 ◽  
Author(s):  
Talea Mayo ◽  
Ning Lin
Keyword(s):  
Wind Speed ◽  
Storm Surge ◽  
Wind Field ◽  
Wind Profile ◽  
Storm Surges ◽  
Maximum Wind Speed ◽  
Field Representation ◽  
Maximum Wind ◽  
National Hurricane Center ◽  
Surface Background

The Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model is the operational storm surge model of the National Hurricane Center (NHC). Previous studies have found that the SLOSH model estimates storm surges with an accuracy of ±20%. In this study, through hindcasts of historical storms, we assess the accuracy of the SLOSH model for four coastal regions in the Northeastern United States. We investigate the potential to improve this accuracy through modification of the wind field representation. We modify the surface background wind field, the parametric wind profile, and the maximum wind speed based on empirical, physical, and observational data. We find that on average the SLOSH model underestimates maximum storm surge heights by 22%. The modifications to the surface background wind field and the parametric wind profile have minor impacts; however, the effect of the modification to maximum wind speed is significant—it increases the variance in the SLOSH model estimates of maximum storm surges, but improves its accuracy overall. We recommend that observed values of maximum wind speed be used in SLOSH model simulations when possible.

Potential Tropical Cyclone Disaster Loss Assessment based on Multiple Hazard Indicators

2020 ◽  
Author(s):  
Jian Li
Keyword(s):  
Wind Speed ◽  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Storm Surge ◽  
Maximum Wind Speed ◽  
Central Pressure ◽  
Loss Assessment ◽  
Maximum Wind ◽  
Disaster Loss ◽  
Potential Loss

<p><span>Tropical cyclones could cause large casualties and economic loss in coastal area of China. It is of great importance to develop a method that can provide pre-event rapid loss assessment in a timely manner prior to the landing of a tropical cyclone. In this study, a pre-event tropical cyclone disaster loss assessment method based on similar tropical cyclone retrieval with multiple hazard indicators is proposed. Multiple indicators include tropical cyclone location, maximum wind speed, central pressure, radius of maximum wind, forward speed, Integrated Kinetic Energy (IKE), maximum storm surge, and maximum significant wave height. Firstly, the track similarity is measured by similarity deviation considering only the locations of tropical cyclone tracks. Secondly, the intensity similarity is measured by best similarity coefficient using central pressure, radius of maximum wind, maximum wind speed, moving speed, wind, storm surge, and wave intensity indices. Then, the potential loss of current tropical cyclone is assessed based on the retrieved similar tropical cyclones loss. Taking tropical cyclone Utor (2013) that affected China as an example, the potential loss is predicted according to the five most similar historical tropical cyclones which are retrieved from all the historical tropical cyclones. The method is flexible for rapid disaster loss assessment since it provides a relatively satisfactory result based on two scenarios of input dataset availability.</span></p>

A COMPREHENSIVE STUDY ON RADIUS TO TYPHOON-GENERATED MAXIMUM WIND SPEED BASED ON DATA ANALYSES

2020 ◽  
Vol 76 (2) ◽  
pp. I_223-I_228
Author(s):  
Masataka YAMAGUCHI ◽  
Kunimitsu INOUCHI ◽  
Yoshihiro UTSUNOMIYA ◽  
Hirokazu NONAKA ◽  
Yoshio HATADA ◽  
...  
Keyword(s):  
Wind Speed ◽  
Maximum Wind Speed ◽  
Maximum Wind ◽  
Data Analyses ◽  
Comprehensive Study
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