Title

Correlation Analysis between Sea Surface Temperature & Storm Intensity of Hurricanes in Southern Florida between 2003 and 2023

Presenter Information

Devin RichardsFollow

Academic Level at Time of Presentation

Senior

Major

Geology

List all Project Mentors & Advisor(s)

Dr. Haluk Cetin

Presentation Format

Poster Presentation

Abstract/Description

The objective of this study is to map historic hurricane tracks through south Florida over the past two decades to determine if there is a correlation between storm intensity and sea surface temperature (SST). This project was conducted using Google Earth Engine (GEE) mapping software and graphing of Excel datasets. Hurricane track coordinates were sourced from the National Oceanic and Atmospheric Administration public storm database, which included record of storm intensity, wind speed, and air pressure. Hurricane GPS coordinates were plotted atop global SST data sourced from NASA’s MODIS Global Water Reservoir algorithm. A regression model was then created for multiple points along various hurricane tracks mapping storm intensity and SST. The initial results of this correlation analysis were that there was a positive relationship between storm intensity and higher SST at the time of the events. This concise analysis would not be possible without the use of GEE’s availability of datasets and stored tools, such as NASA’s MODIS algorithm.

Fall Scholars Week 2023 Event

Earth and Environment Sciences Poster Session

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Correlation Analysis between Sea Surface Temperature & Storm Intensity of Hurricanes in Southern Florida between 2003 and 2023

The objective of this study is to map historic hurricane tracks through south Florida over the past two decades to determine if there is a correlation between storm intensity and sea surface temperature (SST). This project was conducted using Google Earth Engine (GEE) mapping software and graphing of Excel datasets. Hurricane track coordinates were sourced from the National Oceanic and Atmospheric Administration public storm database, which included record of storm intensity, wind speed, and air pressure. Hurricane GPS coordinates were plotted atop global SST data sourced from NASA’s MODIS Global Water Reservoir algorithm. A regression model was then created for multiple points along various hurricane tracks mapping storm intensity and SST. The initial results of this correlation analysis were that there was a positive relationship between storm intensity and higher SST at the time of the events. This concise analysis would not be possible without the use of GEE’s availability of datasets and stored tools, such as NASA’s MODIS algorithm.