Coastal high water events are increasing in frequency and severity as global ocean levels rise. With higher relative sea levels, minor coastal flooding is occurring more often during periods of higher astronomical tides. If combined with above-normal seasonal sea levels, often associated with climate-driven variability in the ocean, coastal flooding becomes more severe. Such total high water events expose coastlines to potentially damaging storm-related flooding, yet no seasonal prediction of coastal high water exists on a national scale.
Regional sea levels are affected by the winds, as well as ocean circulation changes. In the Pacific, sea level variations (±30 cm) associated with the El Niño-Southern Oscillation (ENSO), as well as more local processes such as eddies and upwelling or downwelling, impact Hawaii, U.S.-affiliated Pacific Islands (USAPI), and the West Coast. In the Atlantic, sea level anomalies also emerge during El Niño from seasonal changes in storm tracks and winds, impacting the East Coast. On more frequent timescales, fluctuations in the Gulf Stream can produce sea level anomalies (±15 cm) along the U.S. mid- and south-Atlantic Coasts. With recent advancements in forecasting seasonal climate variability using state-of-the-art coupled ocean-atmosphere models, which have the ability to assimilate and predict sea level, come the opportunity to predict the potential for future high water events many months in advance for the U.S. Coast.
Our goal is to construct multi-model forecasts based on seasonal prediction systems and evaluate their skill across the NOAA tide gauge network in the continental U.S., as well as the NOAA and University of Hawaii Sea Level Center (UHSLC) network in Hawaii, the USAPI, the Gulf of Mexico, and Caribbean. Preliminary work suggests that forecast skill can also be improved in some regions by incorporating statistical relationships between observed and predicted sea level variability or by connecting it with the modes of atmospheric variability. From the multi-model forecasts we will provide regional seasonal sea level anomaly outlooks nationwide. A geospatial web portal will be developed to deliver the outlooks, such as high-water alert calendars, which can be combined or incorporated into new or existing NOAA coastal-flood products.
Our team will focus on three objectives by performing the following tasks to deliver a prototype seasonal prediction system:
i. We will explore the processes responsible for sea level variability on monthly to interannual timescales in the Pacific, Atlantic, Gulf of Mexico, and Caribbean coastal regions.
ii. We will process sea level forecasts from operational as well as experimental modeling frameworks to develop a prototype ensemble seasonal prediction system for coastal sea level anomalies.
iii. We will use the multi-model prediction system to provide monthly outlooks for seasonal sea level anomalies across the Nation.
We aim to deliver a framework for seasonal sea level forecasting which strengthens the production of climate data and information that informs the management of climate-related risks. Our forecast framework seeks to reduce the residual between predicted tides and observed water levels by predicting relative sea level changes.
Climate Risk Area: Coastal Inundation
Principal Investigator (s): Mark Merrifield (University of Hawai’i at Mānoa (UH)), Arun Kumar (NOAA/CPC), Gary Mitchum (University of South Florida)
Co-PI (s):Matthew Widlansky (UH Sea Level Center), Philip Thompson (UH Sea Level Center), H. Annamalai (International Pacific Research Center), William Sweet (NOAA/NOS/CO-OPS), Eric Leuliette (NOAA/STAR), John Marra (NOAA/NCEI)
Task Force: Marine Prediction
Year Initially Funded:2017
Competition: Research to explore seasonal prediction of coastal high water levels and changing living marine resources