Date of Award

December 2019

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Civil Engineering

Committee Member

Weichiang Pang

Committee Member

Ashok Mishra

Committee Member

Kalyan Piratla

Committee Member

Shiraj Khan

Abstract

Quantification of hurricane hazard, which includes wind, rainfall and storm surge, is essential for engineering design as well as financial loss assessment. The objective of this study is to develop a stochastic simulation framework which integrates the simulation process of hurricane rainfall and wind hazard. This study is divided into two parts. The main objective of the first part is to develop a method for the estimation of the hurricane wind field parameters radius to maximum wind speeds (R_max) and Holland B parameter (B). The second part develops a stochastic model to simulate hurricane rainfall, which is named the ‘NormRain’ model.

The first part develops a hurricane wind speed computation method, which is validated by comparing with wind speed observations from meteorological stations. Then, a method to estimate R_max and B for historical storms is developed using this wind speed computation algorithm. Finally, based on the analysis of historical storms using the R_max and B estimation method, equations for stochastic simulation of R_max and B time history are developed. These equations can simulate the temporal correlation (i.e. correlation of the simulated value in current time-step with the previous timesteps) of R_max and B, which is an improvement over other commonly used method.

Besides R_max and B estimation, another important application of the wind speed computation framework is to develop a database of hurricane wind speed hazard curves for the 30 Eastern US states, which is expected to aid the research of performance-based wind engineering.

The hurricane rainfall distribution about the storm center can be very asymmetric and irregular, with high rainfall rates far from storm center. The existing statistical models for hurricane rainfall usually estimate the mean rainfall rate profile, and do not explicitly consider the total rainfall volume. However, the mean rainfall rate profiles cannot account for high localized rainfall rates which can be much larger than the mean value and can contribute a significant portion of the total rainfall volume. To overcome this limitation, this study develops a rainfall simulation model which explicitly simulates total rainfall volume using central pressure, relative vorticity and total precipitable water. Since the irregular shape of hurricane rain field is difficult to describe using equations, this study simulates the hurricane rain field using the concept of normalized rain field shape from historical storms. The hurricane simulation model can thus simulate realistic hurricane rain fields.

The hurricane rain simulation model ‘NormRain’ developed in the second part of this study consists of two parts. The first part estimates the total rainfall volume and extent of hurricane rain field at any time-step, and the second part determines how the rainfall rates associated with this rainfall volume are distributed within the rain field extent.

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