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Little is known about the effect of tidal changes on minor flooding in most lagoonal estuaries, often due to a paucity of historical records that predate landscape changes. In this contribution, we recover and apply archival tidal range data to show that the mean tidal range in Miami, Florida, has almost doubled since 1900, from 0.32 to 0.61 m today. A likely cause is the dredging of a ∼15 m deep, 150 m wide harbor entrance channel beginning in the early 20th century, which changed northern Biscayne Bay from a choked inlet system to one with a tidal range close to coastal conditions. To investigate the implications for high‐tide flooding, we develop and validate a tidal‐inference based methodology that leverages estimates of pre‐1900 tidal range to obtain historical tidal predictions and constituents. Next, water level predictions that represent historical and modern water level variations are projected forward in time using different sea level rise scenarios. Results show that the historical increase in tidal range hastened the occurrence of present‐day flooding, and that the total integrated number of days with high‐tide floods in the 2020–2100 period will be approximately O(10³) more under present day tides compared to pre‐development conditions. These results suggest that tidal change may be a previously under‐appreciated factor in the increasing prevalence of high‐tide flooding in lagoonal estuaries, and our methods open the door to improving our understanding of other heavily‐altered systems.

 

We demonstrate that long‐term tidally induced changes in extreme sea levels affect estimates of major flood hazard in a predictable way. Long‐term variations in tides due to the 4.4 and 18.6‐year cycles influence extreme sea levels at 380 global tide gauges out of a total of 581 analyzed. Results show coherent regions where the amplitudes of the modulations are particularly relevant in the 100‐year return sea level, reaching more than 20 cm in some regions (western Europe, north Australia, and Singapore). We identify locations that are currently in a positive phase of the modulation and therefore at a higher risk of flooding, as well as when (year) the next peak of the long‐term tidal modulations is expected to occur. The timing of the peak of the modulation is spatially coherent and influenced by the relative importance of each cycle (4.4 or 18.6‐year) over the total amplitude. An evaluation of four locations suggests that the potentially flooded area in a 100‐year event can vary up to ∼45% (in Boston) as a result of the long‐term tidal cycles; however, the flooded area varies due to local topography and tidal characteristics (6%–13%). We conclude that tidally modulated changes in extreme sea levels can alter the potentially inundated area in a 100‐year event and that the traditional, fixed 100‐year floodplain is inadequate for describing coastal flood risk, even without considering sea‐level rise.

 

We perform the first global analysis of the spatial footprints of storm surges, using observed and simulated storm surge data. Three different techniques are applied to quantify the spatial footprints: clustering analysis, percentage of co‐occurrence, and joint probability analysis. The capability of the simulated data to represent the observed storm surge footprints is demonstrated. Results lead to the identification of coastline stretches prone to be impacted simultaneously by the same storm surge events. The spatial footprint sizes differ around the globe, partially conditioned by the geography of the coastline, that is, more irregular coastlines consist of a larger number of different storm surge clusters with varying footprint sizes. For the northwestern Atlantic, spatial footprints of storm surges vary when specifically accounting for tropical cyclones, using storm track information in the storm surge simulations. Our results provide important new insights into the spatial footprints of storm surges at the global scale and will help to facilitate improvements in how coastal flood risk is identified, assessed, and managed, by taking these spatial features into account.

 

The release of new and updated sea‐level rise (SLR) information, such as from the Intergovernmental Panel on Climate Change (IPCC) Assessment Reports, needs to be better anticipated in coastal risk and adaptation assessments. This requires risk and adaptation assessments to be regularly reviewed and updated as needed, reflecting the new information but retaining useful information from earlier assessments. In this paper, updated guidance on the types of SLR information available is presented, including for sea‐level extremes. An intercomparison of the evolution of the headline projected ranges across all the IPCC reports show an increase from the fourth and fifth assessments to the most recent “Special Report on the Ocean and Cryosphere in a Changing Climate” assessment. IPCC reports have begun to highlight the importance of potential high‐end sea‐level response, mainly reflecting uncertainties in the Greenland/Antarctic ice sheet components, and how this might be considered in scenarios. The methods that are developed here are practical and consider coastal risk assessment, adaptation planning, and long‐term decision‐making to be an ongoing process and ensure that despite the large uncertainties, pragmatic adaptation decisions can be made. It is concluded that new sea‐level information should not be seen as an automatic reason for abandoning existing assessments, but as an opportunity to review (i) the assessment's robustness in the light of new science and (ii) the utility of proactive adaptation and planning strategies, especially over the more uncertain longer term.

This article is categorized under:

Assessing Impacts of Climate Change > Scenario Development and Application

 

Abstract. Rising seas are a threat to human and natural systems along coastlines. The relation between global warming and sea level rise is established, but the quantification of impacts of historical sea level rise on a global scale is largely absent. To foster such quantification, here we present a reconstruction of historical hourly (1979–2015) and monthly (1900–2015) coastal water levels and a corresponding counterfactual without long-term trends in sea level. The dataset pair allows for impact attribution studies that quantify the contribution of sea level rise to observed changes in coastal systems following the definition of the Intergovernmental Panel on Climate Change (IPCC). Impacts are ultimately caused by water levels that are relative to the local land height, which makes the inclusion of vertical land motion a necessary step. Also, many impacts are driven by sub-daily extreme water levels. To capture these aspects, the factual data combine reconstructed geocentric sea level on a monthly timescale since 1900, vertical land motion since 1900 and hourly storm-tide variations since 1979. The inclusion of observation-based vertical land motion brings the trends of the combined dataset closer to tide gauge records in most cases, but outliers remain. Daily maximum water levels get in closer agreement with tide gauges through the inclusion of intra-annual ocean density variations. The counterfactual data are derived from the factual data through subtraction of the quadratic trend. The dataset is made available openly through the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) at https://doi.org/10.48364/ISIMIP.749905 (Treu et al., 2023a).

 

Abstract We address the challenge, due to sparse observational records, of investigating long-term changes in the storm surge climate globally. We use two centennial and three satellite-era daily storm surge time series from the Global Storm Surge Reconstructions (GSSR) database and assess trends in the magnitude and frequency of extreme storm surge events at 320 tide gauges across the globe from 1930, 1950, and 1980 to present. Before calculating trends, we perform change point analysis to identify and remove data where inhomogeneities in atmospheric reanalysis products could lead to spurious trends in the storm surge data. Even after removing unreliable data, the database still extends existing storm surge records by several decades for most of the tide gauges. Storm surges derived from the centennial 20CR and ERA-20C atmospheric reanalyses show consistently significant positive trends along the southern North Sea and the Kattegat Bay regions during the periods from 1930 and 1950 onwards and negative trends since 1980 period. When comparing all five storm surge reconstructions and observations for the overlapping 1980–2010 period we find overall good agreement, but distinct differences along some coastlines, such as the Bay of Biscay and Australia. We also assess changes in the frequency of extreme surges and find that the number of annual exceedances above the 95th percentile has increased since 1930 and 1950 in several regions such as Western Europe, Kattegat Bay, and the US East Coast. 

Abstract. To improve our understanding of the influence of tropicalcyclones (TCs) on coastal flooding, the relationships between storm surgeand TC characteristics are analyzed for 12 sites along the east coast of theUnited States. This analysis offers a unique perspective by first examiningthe relationship between the characteristics of TCs and their resultingstorm surge and then determining the probabilities of storm surge associatedwith TCs based on exceeding certain TC characteristic thresholds. Usingobservational data, the statistical dependencies of storm surge on TCs areexamined for these characteristics: TC proximity, intensity, path angle, andpropagation speed, by applying both exponential and linear fits to the data.At each tide gauge along the east coast of the United States, storm surge isinfluenced differently by these TC characteristics, with some locations morestrongly influenced by TC intensity and others by TC proximity. Thecorrelation for individual and combined TC characteristics increases whenconditional sorting is applied to isolate strong TCs close to a location.The probabilities of TCs generating surge exceeding specific return levels(RLs) are then analyzed for TCs passing within 500 km of a tide gauge, wherebetween 6 % and 28 % of TCs were found to cause surge exceeding the1-year RL. If only the closest and strongest TCs are considered, thepercentage of TCs that generate surge exceeding the 1-year RL is between 30 % and 70 % at sites north of Sewell's Point, VA, and over 65 % atalmost all sites south of Charleston, SC. When examining storm surgeproduced by TCs, single-variable regression provides a good fit, whilemulti-variable regression improves the fit, particularly when focusing on TCproximity and intensity, which are, probabilistically, the two mostinfluential TC characteristics on storm surge.