North American East Coast Sea Level Exhibits High Power and Spatiotemporal Complexity on Decadal Timescales

Little, Christopher M.; Piecuch, C. G.; Ponte, Rui M.

doi:10.1029/2021gl093675

Cited by 14 publications

(15 citation statements)

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“…On monthly to interannual time scales, Charleston sea level is coherent with much of the US East Coast south of Cape Hatteras (Calafat et al., 2018; Little et al., 2021; Woodworth et al., 2014). Many densely‐populated cities prone to coastal flooding events over the last few decades (Moftakhari et al., 2015) are located along this coast.…”

Section: Introductionmentioning

confidence: 99%

“…This location is one of the pilot study locations agreed upon by a collaborative project called RISE involving researchers from NOAA, NASA, and academia to compare seasonal SLA prediction skill from different methods. Charleston has been selected as pilot location for four reasons: On monthly to interannual time scales, Charleston sea level is coherent with much of the US East Coast south of Cape Hatteras (Calafat et al., 2018; Little et al., 2021; Woodworth et al., 2014). Many densely‐populated cities prone to coastal flooding events over the last few decades (Moftakhari et al., 2015) are located along this coast. For Charleston, a “minor flood” threshold of 38 cm above mean high‐high water (MHHW) has been estimated by NOAA.…”

Section: Introductionmentioning

confidence: 99%

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A Hybrid Dynamical Approach for Seasonal Prediction of Sea‐Level Anomalies: A Pilot Study for Charleston, South Carolina

et al. 2022

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With global-mean sea level (SL) rising at an accelerating pace (Frederikse et al., 2020;Nerem et al., 2018), many coastal cities around the globe face an increase in extreme SL and coastal flooding events (Moftakhari et al., 2015;Thompson et al., 2021;Wahl et al., 2014). For example, over the last several years, many coastal cities around the United States have started experiencing high-tide flooding (HTF) events. HTF events are floods not primarily caused by large storm systems, but due to high tides and regular variations in atmospheric and oceanic conditions (Sweet et al., 2020). Accurate predictions of such flooding events, or even assessments of coastal flooding probabilities could possibly be a valuable tool for coastal communities to prepare for these events. However, it is challenging to accurately predict such events up to a few months ahead in part because we

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Hybrid Dynamical Approach for Seasonal Prediction of Sea‐Level Anomalies: A Pilot Study for Charleston, South Carolina

et al. 2022

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“…Hatteras to Nova Scotia (Figure S1; Andres et al, 2013;Thompson, 1986;McCarthy et al, 2015;Thompson & Mitchum, 2014;Woodworth et al, 2014;Piecuch et al, 2016;Little et al, 2021).…”

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confidence: 99%

Local and Remote Forcing of Interannual Sea‐Level Variability at Nantucket Island

et al. 2022

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The northeast coast of the United States (US) is a densely-populated region with enhanced sea level rise (SLR) relative to the global mean (Sallenger et al., 2012). Many processes contribute to sea-level change in this region (Little et al., 2019; Woodworth et al., 2019 and references therein). Quantifying the relative contributions of these different processes to past sea-level change can improve the reliability of future SLR predictions.The magnitude of interannual sea-level variations in the northeast US is large compared to the long-term secular trend over the last few decades (Andres et al., 2013). For example, Goddard et al. (2015) reported an extreme seal-level variation during 2009-2010 that was equivalent to approximately 30 years of global-mean SLR. In addition to having large magnitudes, interannual sea-level variations in the region are also coherent from Cape

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“…Previous studies primarily focused on the driving mechanism of the Pacific, Atlantic, Indian Ocean, Mediterranean, and global sea levels (Kirikkaleli and Sowah, 2021;Deepa and Gnanaseelan, 2021;Little et al, 2021). In contrast, we include the Black Sea, the southern hemisphere, and the northern hemisphere in addition to the above areas.…”

Section: Wavelet Coherence Analysis Resultsmentioning

confidence: 99%

“…Although WC is suitable for studying the relationship between sea level and its influencing factors, most studies have focused on single sea areas, including the east coast of North America (Little et al, 2021), European sea areas (Jevrejeva et al, 2006;Jevrejeva et al, 2010), Indian Ocean (Tiwari et al, 2004;Deepa and Gnanaseelan, 2021), East China Sea (Liu et al, 2010), South China Sea (Xi et al, 2020), Bohai Bay (Lü et al, 2019), Mediterranean Sea (Dogan et al, 2015;Volkov et al, 2019), New England coastal areas (Piecuch et al, 2019), Persian Gulf (Afshar et al, 2020), Baltic sea (Medvedev and Kulikov, 2019;Armin et al, 2021), the west coast of South America (Camayo and Campos, 2006), and global studies (Kirikkaleli and Sowah, 2021;Haddad et al, 2013) However, due to the interaction between climate indices (ENSO is highly correlated with PDO, AMO, SOI, and AMO), the relationship between climate indices and MMSL may not be independent. Therefore, using WC may be misleading to analyze the binary relationship between climate indices and sea level.…”

Section: Introductionmentioning

confidence: 99%

Improving the understanding of the influencing factors on sea level on various time scales based on wavelet coherence and partial wavelet coherence

Song

Chen

Xia

2021

Preprint

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The relationship between sea level change and a single climate indicator has been widely discussed. Despite this, few studies focused on the relationship between monthly mean sea level (MMSL) and several key impact factors, including CO2 concentration, sea ice area, and sunspots, on various time scales. In addition, research on the independent relationship between climate factors and sea level on various time scales is lacking, especially when the dependence of climate factors on Niño 3.4 is excluded. Based on this, we use wavelet coherence (WC) and partial wavelet coherence (PWC) to establish a relationship between MMSL and its influencing factors. The WC results show that the influence of climate indices on MMSL has strong regional characteristics. Sunspots affect MMSL on a scale of more than 64 months. The influence of the sea ice area on MMSL in the northern hemisphere is opposite to that in the southern hemisphere. The PWC results show that after removing the influence of Niño 3.4, the significant coherent regions of the Pacific Decadal Oscillation (PDO), Dipole Mode Index (DMI), Atlantic Multidecadal Oscillation (AMO), and Southern Oscillation Index (SOI) decrease to varying degrees on different time scales in different regions, demonstrating the influence of Niño 3.4. Our work emphasizes the independent relationship between MMSL and its influencing factors on various time scales and the use of PWC and WC to describe this relationship. The study has important reference significance for selecting the best predictors of sea level change or climate systems.

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North American East Coast Sea Level Exhibits High Power and Spatiotemporal Complexity on Decadal Timescales

Abstract: Interannual to multidecadal fluctuations in sea level often overwhelm long-term secular trends, driving changes in the frequency and severity of coastal flooding, salt water intrusion, and coastal erosion events, with important consequences for coastal communities (e.g.

Cited by 14 publications

References 50 publications

A Hybrid Dynamical Approach for Seasonal Prediction of Sea‐Level Anomalies: A Pilot Study for Charleston, South Carolina

A Hybrid Dynamical Approach for Seasonal Prediction of Sea‐Level Anomalies: A Pilot Study for Charleston, South Carolina

Local and Remote Forcing of Interannual Sea‐Level Variability at Nantucket Island

Improving the understanding of the influencing factors on sea level on various time scales based on wavelet coherence and partial wavelet coherence

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