Facing the escalating effects of climate change,it is critical to improve the prediction and understanding of the hurricane evacuation decisions made by households in order to enhance emergency management.Current studies in this area often have relied on psychology-driven linear models,which frequently exhibited limitations in practice.The present study proposed a novel interpretable machine learning approach to predict household-level evacuation decisions by leveraging easily accessible demographic and resource-related predictors,compared to existing models that mainly rely on psychological factors.An enhanced logistic regression model(that is,an interpretable machine learning approach) was developed for accurate predictions by automatically accounting for nonlinearities and interactions(that is,univariate and bivariate threshold effects).Specifically,nonlinearity and interaction detection were enabled by low-depth decision trees,which offer transparent model structure and robustness.A survey dataset collected in the aftermath of Hurricanes Katrina and Rita,two of the most intense tropical storms of the last two decades,was employed to test the new methodology.The findings show that,when predicting the households’ evacuation decisions,the enhanced logistic regression model outperformed previous linear models in terms of both model fit and predictive capability.This outcome suggests that our proposed methodology could provide a new tool and framework for emergency management authorities to improve the prediction of evacuation traffic demands in a timely and accurate manner.
In this paper,we propose a two-stage transmission hardening and planning(TH&P)model that can meet the load growth demand of normal scenarios and the resilience requirements of hurricane-induced damage scenarios.To better measure the resilience requirements,the proposed TH&P model includes two resilience assessment indexes,namely,the load shedding(LS)under the damage scenario and the average connectivity degree(ACD)at different stages.The first-stage model,which aims to meet the load growth demand while minimizing the LS,is formulated as a mixed-integer linear program(MILP)to minimize the total planning and hardening cost of transmission lines,the operating cost of generators,and the penalty cost of wind power and load shedding in both normal and damage scenarios.The second-stage model aims to further improve the ACD when the ACD of the scheme obtained from the first-stage model cannot reach the target.Specifically,the contribution of each transmission line to the ACD is calculated,and the next hardened line is determined to increase the ACD.This process is repeated until the ACD meets the requirements.Case studies of the modified IEEE RTS-24 and two-area IEEE reliability test system-1996 indicate the proposed TH&P model can meet the requirements for both normal and damage scenarios.
Geostationary Operational Environmental Satellite-16(GOES-16) Advanced Baseline Imager(ABI) observations of brightness temperature(TB) are used to examine the temporal evolutions of convection-affected structures of Hurricane Irma(2017) during its rapid intensification(RI) period from 0600 to 1800 UTC 4 September 2017.The ABI observations reveal that both an elliptical eye and a spiral rainband that originated from Irma's eyewall obviously exhibit wavenumber-2 TB asymmetries.The elliptical eye underwent a counterclockwise rotation at a mean speed of a wavenumber-2 vortex Rossby edge wave from 0815 to 1005 UTC 4 September.In the following about 2 hours(1025–1255 UTC 4 September),an inner spiral rainband originated from the eyewall and propagated at a phase speed that approximates the vortex Rossby wave(VRW) phase speed calculated from the aircraft reconnaissance data.During the RI period of Irma,ABI TB observations show an on–off occurrence of low TB intrusions into the eye,accompanying a phase lock of eyewall TB asymmetries of wavenumbers 1 and 2 and an outward propagation of VRW-like inner spiral rainbands from the eyewall.The phase lock leads to an energy growth of Irma's eyewall asymmetries.Although the eye remained clear from 1415 to 1725 UTC 4 September,an inner spiral rainband that originated from a large convective area also had a VRW-like outward propagation,which is probably due to a vertical tilt of Irma.This study suggests a potential link between convection sensitive GOES imager observations and hurricane dynamics.
