Attributing decadal climate variability in coastal sea-level trends

Royston, Sam; Bingham, Rory J.; Bamber, Jonathan

doi:10.5194/os-18-1093-2022

Cited by 5 publications

(2 citation statements)

References 52 publications

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“…Haq et al (2014) documented ~ 40 cycles in the Cretaceous of 1-2 My duration, that likely correspond to these 3rd order cycles (Fig. 16) and may be related to relative sea level changes caused by variations in mid-ocean ridge spreading rates or orbital forcing (Berger et al, 1990.;Royston et al, 2022;Wright et al, 2020) Figure 16. Integrated chronostratigraphic events chart of the Guinea Plateau since the Mid Jurassic.…”

Section: Controls On Transgressive-regressive Cycles On the Guinea Ma...mentioning

confidence: 95%

Seismic stratigraphy of the Guinea Plateau before, during and after the opening of the Equatorial Atlantic Gateway

Aduomahor,

Duarte,

Wagner

et al. 2024

Preprint

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The Guinea Plateau contains a ~200-million-year stratigraphic record, encompassing the mid-Cretaceous opening of the Equatorial Atlantic Gateway (EAG). Here we present new 2D seismic data to constrain the structural and stratigraphic evolution of the plateau. Seismic stratigraphic analysis reveals five megasequences of ~25-65 My duration: M1, a Jurassic syn-rift sequence with prominent seaward-dipping reflections; M2, a late Jurassic- Early Cretaceous post-rift carbonate platform; M3, a late Early Cretaceous syn-transform clastic-dominated sequence; M4, an Albian-Maastrichtian post-transform sequence; and M5, a Maastrichtian-Recent passive margin sequence with low sedimentation rates. These megasequences also contain prominent transgressive-regressive cycles of 5-10 My duration, interpreted to be the result of dynamic topography.The boundary between M3 and M4 is a major erosional unconformity documenting final continental breakup during the opening of the EAG. Above this, a pronounced Albian to Cenomanian/Turonian marine transgression resulted in marine inundation of the plateau. Structural deformation continued into the early Cenomanian along the Guinea Marginal Ridge, a potential structural barrier that restricted marine connection across the EAG. Bulk geochemical data from the shallow Guinea Plateau indicate that enhanced carbon burial in this setting was primarily driven by the deposition of reworked, oxidised organic matter during OAE, independent of gateway opening.

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Section: Controls On Transgressive-regressive Cycles On the Guinea Ma...mentioning

confidence: 95%

Seismic stratigraphy of the Guinea Plateau before, during and after the opening of the Equatorial Atlantic Gateway

Aduomahor,

Duarte,

Wagner

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…However, these studies applied climate model data from CMIP5 with a temporal length of several decades (Taylor et al 2012). This is too short to properly account for decadal climate variability (Royston et al 2022) and low-probability TCs (Bloemendaal et al 2020b). In addition, the climate model's resolution is too low to adequately capture TC characteristics (Murakami and Sugi 2010;Murakami 2014), further limiting the certainty of the projections.…”

Section: Future Climate Tc and Etc Storm Tide Levelsmentioning

confidence: 99%

Facing the storm

Dullaart

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Coastal flooding is one of the most frequent natural hazards around the globe and can have devastating societal impacts. It is caused by extreme storm tides, which are composed of storm surges and tides, on top of mean sea levels. Due to socio-economic developments in the world’s coastal zones, the impacts of coastal floods have increased in recent decades. In addition, projected changes in the frequency and intensity of storms, as well as sea level rise due to climate change are expected to increase the coastal flood hazard. These trends show that it is crucial to further improve coastal flood hazard assessments to support coastal flood management. A lack of understanding of the influence of tropical cyclones (TCs) on storm tide level return periods (RPs) currently prevails. Available meteorological data does not adequately capture the structure of TCs, and the temporal length of this data is too short to accurately compute RPs because TCs are low-probability events. Existing large scale coastal flood hazard assessments assume an infinite flood duration and do not capture the physical hydrodynamic processes that drive coastal flooding. Furthermore, future changes in the frequency and intensity of TCs and extratropical cyclones (ETCs) are often neglected in coastal flood hazard assessments. As such, the goal of this thesis is to improve global storm tide modelling through the better representation of TC-related extremes and enable dynamic flood mapping in both current and future climates. The research in this thesis contributes to ongoing efforts in the coastal risk community to better understand coastal flood hazards and risks on a global scale. The COAST-RP dataset can help identify hotspot regions most prone to coastal flooding. Such information can then be used to determine where more detailed local-scale coastal flood hazard assessments are most needed. Combining data from COAST-RP with the HGRAPHER method allows us to move away from planar towards more advanced dynamic inundation methods. This will improve the accuracy of the coastal flood hazard maps. Lastly, the developed TC intensity Δ method that is applicable to different kinds of future climate TC datasets opens the door to studying the future intensity of TCs and corresponding storm surges by placing them in a future climate.

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Unveiling Regional Climate Patterns Through Global Subsurface Ocean Temperature Data: An AI Multi-Layer Analysis Framework

Radin,

Nieves

2024

Earth Syst Environ

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Regional-scale climate variability has far-reaching implications for both local and global climate systems, impacting factors like temperature, precipitation patterns, oceanic circulation, and the occurrence of extreme weather events. However, despite these influences, there is currently no universal methodology for the automated identification of regional-scale variability modes, including those less dominant globally, and for simultaneously exploring the influence of various ocean depth layers in characterizing these modes and diagnosing regional sea level variations. The presented innovative approach addresses these critical region-specific needs by assisting in the extraction of novel regional depth-layered variability modes and establishing their correlation with regional sea level fluctuations, employing tailored machine-learning techniques. This dual-purpose is achieved through the utilization of an optimized k-means clustering method for the automatic identification of regions with shared variability patterns across all global oceans, revealing previously unexplored regional variability modes. Additionally, guided by an EOF/PC analysis, the approach facilitates an automatic exploration of depth layers that significantly contribute to explaining sea level variability, providing insights into diverse climatic regions. Furthermore, the methodology is specifically designed for a multi-scale analysis, enabling the examination of climate variability spanning from months to several years. The results obtained through this approach have the potential to support informed decision-making regarding local climate-related changes.

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Attributing decadal climate variability in coastal sea-level trends

Cited by 5 publications

References 52 publications

Seismic stratigraphy of the Guinea Plateau before, during and after the opening of the Equatorial Atlantic Gateway

Seismic stratigraphy of the Guinea Plateau before, during and after the opening of the Equatorial Atlantic Gateway

Facing the storm

Unveiling Regional Climate Patterns Through Global Subsurface Ocean Temperature Data: An AI Multi-Layer Analysis Framework

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