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Within the last century, the global sea level has risen between 16 and 21 cm and will likely accelerate into the future. Projections from the Intergovernmental Panel on Climate Change (IPCC) show the global mean sea level (GMSL) rise may increase to up to 1 m (1000 mm) by 2100. The primary cause of the sea level rise can be attributed to climate change through the thermal expansion of seawater and the recession of glaciers from melting. Because of the complexity of the climate and environmental systems, it is very difficult to accurately predict the increase in sea level. The latest estimate of GMSL rise is about 3 mm/year, but as GMSL is a global measure, it may not represent local sea level changes. It is essential to obtain tailored estimates of sea level rise in coastline Florida, as the state is strongly impacted by the global sea level rise. The goal of this study is to model the sea level in coastal Florida using climate factors. Hence, water temperature, water salinity, sea surface height anomalies (SSHA), and El Niño southern oscillation (ENSO) 3.4 index were considered to predict coastal Florida sea level. The sea level changes across coastal Florida were modeled using both multiple regression as a broadly used parametric model and the generalized additive model (GAM), which is a nonparametric method. The local rates and variances of sea surface height anomalies (SSHA) were analyzed and compared to regional and global measurements. The identified optimal model to explain and predict sea level was a GAM with the year, global and regional (adjacent basins) SSHA, local water temperature and salinity, and ENSO as predictors. All predictors including global SSHA, regional SSHA, water temperature, water salinity, ENSO, and the year were identified to have a positive impact on the sea level and can help to explain the variations in the sea level in coastal Florida. Particularly, the global and regional SSHA and the year are important factors to predict sea level changes.
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This content will become publicly available on January 31, 2026
Variable vertical land motion and its impacts on sea level rise projections
Coastal vertical land motion (VLM), including uplift and subsidence, can greatly alter relative sea level projections and flood mitigations plans. Yet, current projection frameworks, such as the IPCC Sixth Assessment Report, often underestimate VLM by relying on regional linear estimates. Using high-resolution (90-meter) satellite data from 2015 to 2023, we provide local VLM estimates for California and assess their contribution to sea level rise both now and in future. Our findings reveal that regional estimates substantially understate sea level rise in parts of San Francisco and Los Angeles, projecting more than double the expected rise by 2050. Additionally, temporally variable (nonlinear) VLM, driven by factors such as hydrocarbon and groundwater extraction, can increase uncertainties in 2050 projections by up to 0.4 meters in certain areas of Los Angeles and San Diego. This study highlights the critical need to include local VLM and its uncertainties in sea level rise assessments to improve coastal management and ensure effective adaptation efforts.
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- Award ID(s):
- 2225216
- PAR ID:
- 10610312
- Publisher / Repository:
- Science Advances
- Date Published:
- Journal Name:
- Science Advances
- Volume:
- 11
- Issue:
- 5
- ISSN:
- 2375-2548
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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