Discipline: Ecology Environmental and Earth Sciences
Subcategory: Climate Change
Robert Breininger - Florida Institute of Technology
Co-Author(s): Hanna Vaidya, Wake Forest University, NC. Marisela Madrid, Turtle Mountain Tribal College, ND. Steven Lazarus, Florida Institute of Technology, FL. Nezamoddin N. Kachouie, Florida Institute of Technology, FL.
One of the major consequences of the global climate change is sea level rise. The change in the sea level at a global scale can be attributed to the increased rate of glacial recession and thermal expansion of the oceans . However, many estimates for sea level have been made at the global scale. In Florida, the most recent study regarding the local climate was over a decade ago . Identifying and confirming potential differences between estimates of local sea level rise along Florida coasts and estimates of sea level rise at larger scales (basin and global) would provide essential insights. It is hypothesized that the global rate of sea level change may underestimate the local rate for coastal Florida. The data used to find the local sea level rise estimates for Florida were satellite altimetry at the local, regional, and global level, water temperature and salinity, and El Niño southern oscillation (ENSO) 3.4. The data was found for 15 coastal Florida locations that corresponded to cities. The trends and variances of sea surface height anomalies (SSHA) were found from altimetry data. In this study, the regional, and global sea level rise were compared with the local measurements. The hypothesis was confirmed, as local sea level rise in Florida exceeds the global estimate (about 3mm/year) at 14 out of 15 of the selected locations. The local trends range from about 2.5 mm/year to about 5 mm/year. The local variability ranges from about 2000 mm2 to about 6200 mm2. To model sea level rise in coastal Florida, multiple regression was implemented. However, multiple regression turned out not to be sufficient to model the sea level changes. In turn a more advanced nonlinear model so called generalized additive model (GAM) was implemented. The identified optimal GAM (using Akaike Information Criterion) for each of the 15 coastal Florida locations included year, global SSHA, regional SSHA, water temperature, water salinity, and ENSO as predictors. Since year is proxy variable for many other climate and environmental factors, “Year” was removed in the final model. In both models with and without “Year” as a predictor, all other factors were found to impact the rate of sea level rise. The future work will be focused on extending and refining the GAM by including other environmental and climate factors such as average monthly winds, atmospheric pressures, and coastal currents (Prandi et al. 2009). The tide gauge data will be also used to improve the current model. The coastal Florida locations were selected specifically to have available tide gauge data.References: . Mengel, M., Levermann, A., Frieler, K., Robinson, A., Marzeion, B., and Winkelmann, R. “Future sea level rise constrained by observations and long-term commitment.” Proceedings of the National Academy of Sciences, Vol. 113(10), 2597-2602 (2016). Mitchum, G.T. “Sea level changes in the Southeastern United States.” Florida Climate Institute. (2011).
Funder Acknowledgement(s): Funding was provided by an NSF REU Grant to Dr. Nezamoddin N. Kachouie, Florida Institute of Technology.
Faculty Advisor: Dr. Nezamoddin N. Kachouie and Dr. Steven Lazarus, firstname.lastname@example.org
Role: This project was one of the projects in the REU Summer 2021 Program of Statistical Modeling with Applications to Geoscience (SMAG ) at Florida Institute of Technology under direct supervision of Dr. Nezamoddin N. Kachouie and Dr. Lazarus. As a graduate student participant, I was involved in all aspects of this project working with a team of two undergrad students.