Facing the storm:Assessing global storm tide hazards in a changing climate

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

An Assessment of the Impacts of Climate Change on Coastal Inundation on Bonaire

Bonaire is as a small and low-lying island state vulnerable to the impacts of climate change. In the future decades, sea level rise and tropical cyclones are expected to increase coastal flood risk on the island. Yet, it is still unknown to what extent coastal flooding will increase and which areas on Bonaire are expected to flood. Therefore, this study aims to assess the impacts of climate change on coastal inundation on Bonaire. First, a static bathtub model is used to estimate the future coastlines of the island under multiple sea level rise projections. Second, the SFINCS model is applied to incorporate the dynamic storm components of storm tide and waves in addition to sea level rise. The results of the inundation models indicate that coastal inundation becomes critical for large parts of Kralendijk in 2150 under scenarios SSP5-8.5 and SSP5-8.5 LC. Under the more optimistic scenarios SSP1-2.6 and SSP2-4.5 coastal inundation remains limited to the nature reserves of Klein Bonaire, Lac Bay and the saliñas. Therefore, the results of this study indicate the importance for Bonaire of globally limiting climate change to a lower-end future climate scenario

Advancing global storm surge modelling using the new ERA5 climate reanalysis

This study examines the implications of recent advances in global climate modelling for simulating storm surges. Following the ERA-Interim (0.75° × 0.75°) global climate reanalysis, in 2018 the European Centre for Medium-range Weather Forecasts released its successor, the ERA5 (0.25° × 0.25°) reanalysis. Using the Global Tide and Surge Model, we analyse eight historical storm surge events driven by tropical—and extra-tropical cyclones. For these events we extract wind fields from the two reanalysis datasets and compare these against satellite-based wind field observations from the Advanced SCATterometer. The root mean squared errors in tropical cyclone wind speed reduce by 58% in ERA5, compared to ERA-Interim, indicating that the mean sea-level pressure and corresponding strong 10-m winds in tropical cyclones greatly improved from ERA-Interim to ERA5. For four of the eight historical events we validate the modelled storm surge heights with tide gauge observations. For Hurricane Irma, the modelled surge height increases from 0.88 m with ERA-Interim to 2.68 m with ERA5, compared to an observed surge height of 2.64 m. We also examine how future advances in climate modelling can potentially further improve global storm surge modelling by comparing the results for ERA-Interim and ERA5 against the operational Integrated Forecasting System (0.125° × 0.125°). We find that a further increase in model resolution results in a better representation of the wind fields and associated storm surges, especially for small size tropical cyclones. Overall, our results show that recent advances in global climate modelling have the potential to increase the accuracy of early-warning systems and coastal flood hazard assessments at the global scale

Accounting for tropical cyclones more than doubles the global population exposed to low-probability coastal flooding

Storm surges that occur along low-lying, densely populated coastlines can leave devastating societal, economical, and ecological impacts. To protect coastal communities from flooding, return periods of storm tides, defined as the combination of the surge and tide, must be accurately evaluated. Here we present storm tide return periods using a novel integration of two modelling techniques. For surges induced by extratropical cyclones, we use a 38-year time series based on the ERA5 climate reanalysis. For surges induced by tropical cyclones, we use synthetic tropical cyclones from the STORM dataset representing 10,000 years under current climate conditions. Tropical and extratropical cyclone surge levels are probabilistically combined with tidal levels, and return periods are computed empirically. We estimate that 78 million people are exposed to a 1 in 1000-year flood caused by extratropical cyclones, which more than doubles to 192 M people when taking tropical cyclones into account. Our results show that previous studies have underestimated the global exposure to low-probability coastal flooding by 31%

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

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

COAST-RP: A global COastal dAtaset of Storm Tide Return Periods

Storm surges that occur along low-lying, densely populated coastlines can leave devastating societal, economical, and ecological impacts. To protect coastal communities from flooding, return periods of storm tides, defined as the combination of the surge and tide, must be accurately evaluated. Here we present storm tide return periods using a novel integration of two modelling techniques. For surges induced by extratropical cyclones, we use a 38-year time series based on the ERA5 climate reanalysis. For surges induced by tropical cyclones, we use synthetic tropical cyclones from the STORM dataset representing 10,000 years under current climate conditions. Tropical and extratropical cyclone surge levels are probabilistically combined with tidal levels, and return periods are computed empirically. The COAST-RP dataset contains storm tide levels representing the 1, 2, 5, 10, 25, 50, 100, 250, 500, and 1000-year return period.</p

Modeled storm surge changes in a warmer world: the Last Interglacial

The Last Interglacial (LIG; ca. 125 ka) is a period of interest for climate research as it is the most recent period of the Earth's history when the boreal climate was warmer than at present. Previous research, based on models and geological evidence, suggests that the LIG may have featured enhanced patterns of ocean storminess, but this remains hotly debated. Here, we apply state-of-the-art climate and hydrodynamic modeling to simulate changes in sea level extremes caused by storm surges, under LIG and pre-industrial climate forcings. Significantly higher seasonal LIG sea level extremes emerge for coastlines along northern Australia, the Indonesian archipelago, much of northern and eastern Africa, the Mediterranean Sea, the Gulf of Saint Lawrence, the Arabian Sea, the east coast of North America, and islands of the Pacific Ocean and of the Caribbean. Lower seasonal LIG sea level extremes emerge for coastlines along the North Sea, the Bay of Bengal, China, Vietnam, and parts of Central America. Most of these anomalies are associated with anomalies in seasonal sea level pressure minima and in eddy kinetic energy calculated from near-surface wind fields, and therefore seem to originate from anomalies in the meridional position and intensity of the predominant wind bands. In a qualitative comparison, LIG sea level extremes seem generally higher than those projected for future warmer climates. These results help to constrain the interpretation of coastal archives of LIG sea level indicators.</p