Skillful multiyear prediction of flood frequency along the US Northeast Coast using a high-resolution modeling system

Zhang, Liping; Delworth, Thomas L.; Koul, Vimal; Ross, Andrew; Stock, Charles; Yang, Xiaosong; Zeng, Fanrong; Wittenberg, Andrew; Zhao, Jian; Gu, Qinxue; Li, Shouwei

doi:10.1126/sciadv.ads4419

i

Skillful multiyear prediction of flood frequency along the US Northeast Coast using a high-resolution modeling system

2025
By Zhang, Liping ; Delworth, Thomas L. ; Koul, Vimal ; ...

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Journal Title:

Science Advances
Personal Author:

Zhang, Liping ; Delworth, Thomas L. ; Koul, Vimal ; Ross, Andrew ; Stock, Charles ; Yang, Xiaosong ; Zeng, Fanrong ; Wittenberg, Andrew ; Zhao, Jian ; Gu, Qinxue ; Li, Shouwei
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; GFDL (Geophysical Fluid Dynamics Laboratory)
Description:

Using tide gauge (TG) observations, we identify pronounced multidecadal fluctuations in sea level along the US Northeast Coast (USNEC) superimposed on a long-term increasing trend. This multidecadal sea level variability, largely arising from fluctuations in the buoyancy-driven Atlantic meridional overturning circulation (AMOC), substantially modulates the frequency of flood occurrences along the USNEC and serves as a source of multiyear predictability. Using an initialized dynamical downscaling decadal prediction system with a 1/12° ocean resolution, we demonstrate that flood frequency along the USNEC can be predicted on multiyear to decadal timescales. The long-term increasing trend in flood frequency, mainly driven by increasing greenhouse gases and associated radiative forcing changes, can be predicted a decade ahead. Furthermore, detrended flood frequency along the USNEC exhibits prediction skill for up to 3 years, as verified by TG observation. This multiyear prediction skill is achieved using prediction models that are initialized from our best estimate of observed AMOC.
Source:

Science Advances, 11(20)
DOI:

https://doi.org/10.1126/sciadv.ads4419
ISSN:

2375-2548
Format:

PDF
Publisher:

American Association for the Advancement of Science (AAAS)
Document Type:

Journal Article
License:

https://creativecommons.org/licenses/by-nc/4.0/
Rights Information:

CC BY-NC
Compliance:

Submitted
Main Document Checksum:

urn:sha-512:8d02dacdebba1e55a335c1b041ecf51cf8aeba5053469e43f58fea788c2bd83f5c942b5a0c1e626d95bc6c3ad4fc471e7a8ec2d406dcf394329a81c138acbcb3
Download URL:

https://repository.library.noaa.gov/view/noaa/71095/noaa_71095_DS1.pdf
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[PDF - 4.42 MB ]

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