Today, the Department of Commerce and NOAA announced $3.8 million in funding for six new innovative projects that will work to enhance coastal flooding and inundation information and services, through an investment from the Bipartisan Infrastructure Law.
The initiative, Earth System Science and Modeling Research for Coastal Inundation, will be managed by the NOAA Climate Program Office’s Climate Variability & Predictability and Modeling, Analysis, Predictions and Projections programs. The six projects will be funded for three years, working to empower communities with the knowledge and tools needed to better navigate and respond to coastal challenges.
Funded projects:
- Identifying and leveraging large-scale sources of seasonal to sub-seasonal (S2S) predictability of regional sea-level extremes with explainable machine learning
- This project aims to improve our ability to predict regional sea level changes over periods ranging from a few weeks to several months. By analyzing tide data and using advanced artificial intelligence techniques, these scientists hope to better understand and forecast sea level fluctuations. The research will investigate how large climate patterns influence sea levels and compare predictions from different models. The project will ultimately improve early warning systems, inform adaptation strategies, and enhance resilience to coastal flooding and sea level rise.
- Project PI: Elizabeth A. Barnes (Colorado State University)
- Co-PI: CoPI: Marybeth C. Arcodia (Colorado State University)
- Award amount: $675,453
- Investigating the Seasonal Total Water Level Projections Informed by a Coupled Coastal Modeling System and Bias-Corrected S2S Precipitation Forecasts
- This project focuses on predicting flooding in coastal areas by combining models that account for various types of water movement, such as inland and coastal flooding. This group will provide more accurate and reliable forecasts of compound flooding and total water levels by analyzing the effects of climate change and seasonal variations. This research fills a gap in current NOAA services by addressing the combined impact of sea level rise, increased rainfall, and storm intensity over weeks to months, boosting preparedness and response efforts for climate-related flooding hazards.
- Project PI: Kendra Dresback (University of Oklahoma)
- Co-PIs: Tiantian Yang, Randall Kolar (University of Oklahoma). Collaborators: Edward Myers, Saeed Moghimi (NOAA/NOS)
- Award amount: $600,000
- Understanding the influence of ocean model resolution on seasonal to annual United States coastal sea level forecasts
- Accurate sea level forecasts are crucial for helping coastal residents and decision-makers manage flood risks. This project will analyze advanced global ocean models to improve predictions of sea level changes over seasonal to annual timescales. By studying how well these models capture both atmospheric and natural sea level variability, researchers aim to enhance NOAA’s forecasting tools. The project benefits coastal residents, decision-makers, and the broader scientific community by providing a better understanding of small-scale ocean processes influencing coastal sea level variability and predictability.
- Project PIs: Christopher Little (AER), Stephen Yeager (UCAR)
- Award amount: $487,987
- Predictability of Seasonal to Interannual Coastal Flood Risk
- Sea level rise is an on-going risk to the US coasts with many communities already being impacted. This project aims to deliver a prototype real-time seasonal-to-seasonal coastal flood risk prediction system for the US coastline, incorporating sources of predictability from natural climate patterns such as ENSO, NAO, and MJO, and leveraging NMME prediction systems. The project enhances the accuracy and timeliness of flood risk predictions, ultimately improving resilience and adaptation measures.
- Project PI: Benjamin Kirtman (University of Miami)
- Co-PIs: Brian Soden, Emiliy Becker, Brian McNoldy (University of Miami)
- Award amount: $750,000
- The impact of local-scale variability on regional patterns of total water levels
- The project aims to produce total water level datasets, including the contributions of various components such as tides, storm surges, mean sea level, seasonality, sea level anomalies, and wave runup, over a 40-year period with high temporal and spatial resolution along the U.S. Gulf and East coasts. The research will inform future efforts to improve coastal inundation forecasts, ultimately enhancing coastal resilience and reducing economic losses due to flooding.
- Project PI: Katherine Serafin (University of Florida)
- Co-PIs: Gregory Dusek (NOAA/NOS), Margaret Palmsten (USGS/St. Petersburg Coastal and Marine Science Center)
- Award amount: $544,667
- Assessing opportunities for improved coastal data assimilation in ocean model analyses and seasonal forecasting systems
- This project will improve global model analyses and seasonal forecasting systems related to sea levels for the U.S. East Coast and Gulf of Mexico regions, as well as sea level monthly anomaly outlooks to complement NOAA reporting efforts. The project contributes to better preparedness and adaptation strategies for coastal regions facing increasing threats from sea level rise.
- Project PI: Matthew Widlansky (University of Hawaiʻi at Mānoa)
- Co-PIs: Malte F. Stuecker (University of Hawaiʻi at Mānoa), William Sweet (NOAA/NOS)
- Collaborators: Philip Thompson, Xue Feng, Linta Rose (University of Hawaiʻi at Mānoa), Arun Kumar (NOAA/CPC), Gregory Dusek (NOAA/NOS), John Marra (NOAA/NCEI)
- Award amount: $741,513
These projects are part of a coordinated announcement of $22.78 million in funding to NOAA labs, programs, cooperative institutes and other research partners to advance research on a wide range of water-driven climate impacts.