Antarctic Ice Sheet and emission scenario controls on 21st-century extreme sea-level changes

Frederikse, Thomas; Buchanan, Maya K.; Lambert, Erwin; Kopp, Robert; Oppenheimer, Michael; Rasmussen, D. J.; Wal, R. S. W. van de

doi:10.1038/s41467-019-14049-6

Cited by 45 publications

(32 citation statements)

References 48 publications

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“…Decomposing the total water level to tides and storm surges would allow further investigation of the mechanisms driving the sea-level changes, and whether the interaction effects are important to include in large-scale assessments. Moreover, future research could quantify how the sea-level changes affect return periods (Vitousek et al, 2017;Frederikse et al, 2020). This could include an estimation of the uncertainty in the return periods due to fitting the extreme value distribution.…”

Section: Future Research Directionsmentioning

confidence: 99%

A High-Resolution Global Dataset of Extreme Sea Levels, Tides, and Storm Surges, Including Future Projections

et al. 2020

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The world's coastal areas are increasingly at risk of coastal flooding due to sea-level rise (SLR). We present a novel global dataset of extreme sea levels, the Coastal Dataset for the Evaluation of Climate Impact (CoDEC), which can be used to accurately map the impact of climate change on coastal regions around the world. The third generation Global Tide and Surge Model (GTSM), with a coastal resolution of 2.5 km (1.25 km in Europe), was used to simulate extreme sea levels for the ERA5 climate reanalysis from 1979 to 2017, as well as for future climate scenarios from 2040 to 2100. The validation against observed sea levels demonstrated a good performance, and the annual maxima had a mean bias (MB) of-0.04 m, which is 50% lower than the MB of the previous GTSR dataset. By the end of the century (2071-2100), it is projected that the 1 in 10-year water levels will have increased 0.34 m on average for RCP4.5, while some locations may experience increases of up to 0.5 m. The change in return levels is largely driven by SLR, although at some locations changes in storms surges and interaction with tides amplify the impact of SLR with changes up to 0.2 m. By presenting an application of the CoDEC dataset to the city of Copenhagen, we demonstrate how climate impact indicators derived from simulation can contribute to an understanding of climate impact on a local scale. Moreover, the CoDEC output locations are designed to be used as boundary conditions for regional models, and we envisage that they will be used for dynamic downscaling.

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Section: Future Research Directionsmentioning

confidence: 99%

A High-Resolution Global Dataset of Extreme Sea Levels, Tides, and Storm Surges, Including Future Projections

et al. 2020

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“…Subsequently, a Spearman correlation analysis between the GEE Bruun rule results and the previous study [57] was performed. After the validation process, was tested for the area a scenario of sea-level rise of 1.21 m, considering the contribution of the Antarctic Ice Sheet (AIS) melting process (AIS = 60 cm) [60].…”

Section: R = S(w/h + B)mentioning

confidence: 99%

Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule

et al. 2021

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Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence of free and open-source models to estimate the sea-level impact can contribute to improve coastal management. This study aims to develop and validate two different models to predict the sea-level rise impact supported by Google Earth Engine (GEE)—a cloud-based platform for planetary-scale environmental data analysis. The first model is a Bathtub Model based on the uncertainty of projections of the sea-level rise impact module of TerrSet—Geospatial Monitoring and Modeling System software. The validation process performed in the Rio Grande do Sul coastal plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses the Bruun rule formula implemented in GEE and can determine the coastline retreat of a profile by creatting a simple vector line from topo-bathymetric data. The model shows a very high correlation (0.97) with a classical Bruun rule study performed in the Aveiro coast (NW Portugal). Therefore, the achieved results disclose that the GEE platform is suitable to perform these analysis. The models developed have been openly shared, enabling the continuous improvement of the code by the scientific community.

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“…In the context of climate change problems, such as those mentioned in the previous section, techniques for estimating exceedance probabilities and return periods for extreme events are a matter of first priority. To that end, good, high-resolution paleoclimatic files can be quite useful in this context, as they provide opportunities for evaluating more extreme events over longer periods [32][33][34].…”

Section: Gutenberg-richter Law On Wtd and Peat Humificationmentioning

confidence: 99%

A New Climate Nowcasting Tool Based on Paleoclimatic Data

et al. 2020

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Atmospheric pollutants and environmental indicators are often used to reconstruct historic atmospheric pollution from peat, as it accumulates over time by decomposing plant material, thus recording a history of air pollution. In the present study, three key parameters related to the peat bogs’ surface wetness dynamics in European Russia during the Holocene were investigated using modern statistical analysis. These parameters are: (i) the water table depth (WTD) in relation to the surface, which is reconstructed based on the community structure of the subfossil testate amoeba assemblages; (ii) the peat humification estimated as absorption of alkaline extract that directly reflects moisture at which the peat was formed; (iii) the Climate Moisture Index (CMI) and the Aridity Index derived from pollen-based reconstructions of the mean annual temperature and precipitation and classifying moisture conditions as the ratio between available annual precipitation and potential land surface evapotranspiration. All these parameters provide useful information about the paleoclimate (atmospheric moisture component) dynamics. High values of WTD and peat humification appear to comply with Gutenberg–Richter law. It is noteworthy that this law also seems to reproduce the high values of the modeled climate moisture and aridity indices. The validity of this new result is checked by replacing “conventional time” with “natural time”. On this basis, a new nowcasting tool is developed to more accurately estimate the average waiting time for the extreme values of these climate parameters. This will help to understand climate variability better to address emerging development needs and priorities by implementing empirical studies of the interactions between climatic effects, mitigation, adaptation, and sustainable growth.

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Antarctic Ice Sheet and emission scenario controls on 21st-century extreme sea-level changes

Cited by 45 publications

References 48 publications

A High-Resolution Global Dataset of Extreme Sea Levels, Tides, and Storm Surges, Including Future Projections

A High-Resolution Global Dataset of Extreme Sea Levels, Tides, and Storm Surges, Including Future Projections

Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule

A New Climate Nowcasting Tool Based on Paleoclimatic Data

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