Understanding hydro-meteorology of an extreme hurricane event

Hurricane Maria was the strongest hurricane to hit the island of Puerto Rico since 1928, with an estimated damage cost of ninety billion dollars between the island of Puerto Rico and the U.S. Virgin Islands. Hurricane Maria recorded unprecedented total rainfall resulting in flooding, mudslides, and high-speed winds that led to the destruction of most electrical power and communication transmission systems on the island. The meteorological data recorded during extreme events are of paramount importance in predicting future events and preparing for damage control. Unfortunately, limited data was recorded for Hurricane Maria due to the collapse of the recording station during the first few hours of the storm.  

A team of researchers from the City College of New York led by Professor Jorge González along with his colleagues Dr. Rabindra Pokhrel, Salvador del Cos, Juan Pablo Montoya Rincon, and Equisha Glenn simulated Hurricane Maria in weather research and forecast (WRF) modeling tool, a numerical weather prediction system developed by the National Center for Atmospheric Research (NCAR), compared and validated the results of the model with limited observational records during Hurricane Maria . The original article was published in the research journal Weather and Climate Extremes.

Professor Gonzalez said that: “Hurricane Maria was an exceptional storm with record-high mortality. The study’s motivation is to provide insights before and during the event for impact analysis, especially on critical power infrastructure.”

Professor Gonzalez and colleagues have identified the hydro-meteorological processes that occurred before and during this exceptional event. WRF model outcomes were used for geospatial risk assessment of the failure of electrical power poles on the island.

With regard to the synoptic analysis of conditions that led to the storm indicate, recorded 2017 as the hottest year for sea surface temperatures globally. The higher sea surface temperature was accompanied by low vertical wind shear that helps hurricane formation and intensification.

The research team predicted comparable landfall location and magnitude of Hurricane Maria by using WRF. The maximum wind speed simulated by the model was similar to the wind speed recorded by ocean buoys during the hurricane. The simulation also predicted comparable total rainfall peaks at the center of the island by utilizing precipitation records and the orographic effect of the high altitudes in the island’s central mountains. In addition, it is simulated that the orographic variation increased the rainfall by more than four times. A risk assessment for the failure of electrical power towers on the island was conducted using the wind speed and maximum rainfall data, which concluded a higher risk of failure at the north and center of the island.

This study has successfully provided critical insight into the events that preceded Hurricane Maria. Record high sea surface temperatures and low vertical wind shear were responsible for unparalleled precipitation and flooding caused by the Hurricane. The led author Dr. Rabindra Pokhrel said to Science Featured:  “The validated meteorological variables can be further utilized for further impact assessments such as hydrological modeling (for flood risk) and resiliency model (for impact on critical infrastructures). Future works will be focused on generating reliable data sources for other hurricanes in the Island and utilizing the data for impacts on critical infrastructures.”