Observation and modeling of Hurricane Maria for damage assessment

https://doi.org/10.1016/j.wace.2021.100331Get rights and content
Under a Creative Commons license
open access

Abstract

The human loss due to Hurricane Maria (H-Maria) in the month of September of 2017 was quantified to be more than 4500 casualties in the entire island of Puerto Rico, making it the most devastating storm in US history. Besides, H-Maria left a lasting impact on the Island as it brought to full collapse the electrical power grid rendering the Island entirely out of power for more than ten months. The aim of this work is to fill the gap of the hydro-meteorological processes of this relevant storm due to the limited observational data available. The synoptic observational record shows that the monthly average Sea Surface Temperature of 30 °C, with an anomaly of 0.5 °C as well as low vertical wind shear of 4–8 m/s fueled H-Maria. Simulated (WRF) time series of wind speed is in close resemblance compared with the limited data available from ocean buoys with a simulated and observed peak wind speed of 30 m/s on the southern coast of the Island. The total rainfall for the event was simulated to peak at 762 mm (observed 965 mm) at the center of the Island and was validated with post-hurricane National Weather Service (NWS) rainfall with a Normalized Root Mean Square Error (RMSE) of 0.2. The orographic effects are simulated, reflecting enhancement of the rainfall at high altitudes in the central mountains of the Island. As an example of damage assessment, the risk of failure of the electrical power towers as a function of wind speed and soil saturation is simulated using statistical models for the entire Island, which results in higher risks of failure at the Northwest and center of the Island. These validated results of the storm can also be used as an input for other analysis such as hydrological models to geo-locate regions for risks due to flooding.

Keywords

Hurricane Maria
Observation and modelling
WRF
Precipitation
Orographic effect
Damage assessment

Cited by (0)