Suchergebnisse

Abstract. Coastal flooding is a major global hazard, yet few
studies have examined the spatial and temporal characteristics of extreme
sea level and associated coastal flooding. Here we analyse sea-level records
around the coast of New Zealand (NZ) to quantify extreme storm-tide and
skew-surge frequency and magnitude. We identify the relative magnitude of
sea-level components contributing to 85 extreme sea level and 135 extreme
skew-surge events recorded in NZ since 1900. We then examine the spatial and
temporal clustering of these extreme storm-tide and skew-surge events and
identify typical storm tracks and weather types associated with the spatial
clusters of extreme events. We find that most extreme storm tides were
driven by moderate skew surges combined with high perigean spring tides. The
spring–neap tidal cycle, coupled with a moderate surge climatology,
prevents successive extreme storm-tide events from happening within 4–10 d of each other, and generally there are at least 10 d between extreme
storm-tide events. This is similar to findings from the UK (Haigh et al.,
2016), despite NZ having smaller tides. Extreme events more commonly
impacted the east coast of the North Island of NZ during blocking weather
types, and the South Island and west coast of the North Island during trough
weather types. The seasonal distribution of both extreme storm-tide and
skew-surge events closely follows the seasonal pattern of mean sea-level
anomaly (MSLA) – MSLA was positive in 92 % of all extreme storm-tide events and
in 88 % of all extreme skew-surge events. The strong influence of
low-amplitude (−0.06 to 0.28 m) MSLA on the timing of extreme events shows
that mean sea-level rise (SLR) of similarly small height will drive rapid
increases in the frequency of presently rare extreme sea levels. These
findings have important implications for flood management, emergency
response and the insurance sector, because impacts and losses may be
correlated in space and time.

Abstract. The interaction between waves, surges, and astronomical tides can lead to high coastal total water level (TWL), which can in turn trigger coastal flooding. Here, a high-resolution (1.5 km) simulation from a UK-focused regional coupled environmental prediction system is used to investigate the extreme events of winter 2013/4 around the UK and Irish coasts. The aim is to analyse the spatial distribution of coastal TWL and its components during this period by assessing (1) the relative contribution of different TWL components around the coast; (2) how extreme waves, surges, and tide interacted and if they occurred simultaneously; and (3) if this has implications in defining the severity of coastal hazard conditions. The TWL components' coastal distribution in winter 2013/4 was not constant in space, impacting differently over different regions. High (>90th percentile) waves and high surges occurred simultaneously at any tidal stage, including high tide (7.7 % of cases), but more often over the flood tide. During periods of high flood risk, a hazard proxy, defined as the sum of the sea surface height and half the significant wave height, at least doubled from average over three-quarters of the coast. These results have important implications for the risk management sector.

Abstract. In coastal regions, floods can arise through a combination of multiple
drivers, including direct surface run-off, river discharge, storm surge, and
waves. In this study, we analyse compound flood potential in Europe and
environs caused by these four main flooding sources using state-of-the-art
databases with coherent forcing (i.e. ERA5). First, we analyse the
sensitivity of the compound flooding potential to several factors: (1)
sampling method, (2) time window to select the concurrent event of the
conditioned driver, (3) dependence metrics, and (4) wave-driven sea level
definition. We observe higher correlation coefficients using annual maxima
than peaks over threshold. Regarding the other factors, our results show
similar spatial distributions of the compound flooding potential. Second, the
dependence between the pairs of drivers using the Kendall rank correlation
coefficient and the joint occurrence are synthesized for coherent patterns of
compound flooding potential using a clustering technique. This quantitative
multi-driver assessment not only distinguishes where overall compound flooding
potential is the highest, but also discriminates which driver combinations are
more likely to contribute to compound flooding. We identify that hotspots of
compound flooding potential are located along the southern coast of the North
Atlantic Ocean and the northern coast of the Mediterranean Sea.

Abstract. The interaction between physical drivers from oceanographic, hydrological, and meteorological processes in coastal areas can result in compound flooding. Compound flood events, like Cyclone Idai and Hurricane Harvey, have revealed the devastating consequences of the co-occurrence of coastal and river floods. A number of studies have recently investigated the likelihood of compound flooding at the continental scale based on simulated variables of flood drivers, such as storm surge, precipitation, and river discharges. At the global scale, this has only been performed based on observations, thereby excluding a large extent of the global coastline. The purpose of this study is to fill this gap and identify regions with a high compound flooding potential from river discharge and storm surge extremes in river mouths globally. To do so, we use daily time series of river discharge and storm surge from state-of-the-art global models driven with consistent meteorological forcing from reanalysis datasets. We measure the compound flood potential by analysing both variables with respect to their timing, joint statistical dependence, and joint return period. Our analysis indicates many regions that deviate from statistical independence and could not be identified in previous global studies based on observations alone, such as Madagascar, northern Morocco, Vietnam, and Taiwan. We report possible causal mechanisms for the observed spatial patterns based on existing literature. Finally, we provide preliminary insights on the implications of the bivariate dependence behaviour on the flood hazard characterisation using Madagascar as a case study. Our global and local analyses show that the dependence structure between flood drivers can be complex and can significantly impact the joint probability of discharge and storm surge extremes. These emphasise the need to refine global flood risk assessments and emergency planning to account for these potential interactions.

Abstract. Coastal regions face increasing threats from rising sea levels and extreme weather events, highlighting the urgent need for accurate assessments of coastal flood risk. This study presents a novel approach to estimating global extreme sea level (ESL) exceedance probabilities using a regional frequency analysis (RFA) approach. The research combines observed and modelled hindcast data to produce a high-resolution (∼1 km) dataset of ESL exceedance probabilities, including wave setup, along the entire global coastline (excluding Antarctica). The methodology presented in this paper is an extension of the regional framework of Sweet et al. (2022), with innovations introduced to incorporate wave setup and apply the method globally. Water level records from tide gauges and a global reanalysis of tide and surge levels are integrated with a global ocean wave reanalysis. Subsequently, these data are regionalised, normalised, and aggregated and then fit with a generalised Pareto distribution. The regional distributions are downscaled to the local scale using the tidal range at every location along the global coastline obtained from a global tide model. The results show 8 cm of positive bias at the 1-in-10-year return level when compared to individual tide gauges. The RFA approach offers several advantages over traditional methods, particularly in regions with limited observational data. It overcomes the challenge of short and incomplete observational records by substituting long historical records with a collection of shorter but spatially distributed records. These spatially distributed data not only retain the volume of information but also address the issue of sparse tide gauge coverage in less populated areas and developing nations. The RFA process is illustrated using Cyclone Yasi (2011) as a case study, demonstrating how the approach can improve the characterisation of ESLs in regions prone to tropical cyclone activity. In conclusion, this study provides a valuable resource for quantifying the global coastal flood risk, offering an innovative global methodology that can contribute to preparing for – and mitigating against – coastal flooding.

Abstract. Coastal floods, driven by extreme sea levels, are one of the most dangerous
natural hazards. The people at highest risk are those living in low-lying
coastal areas exposed to tropical-cyclone-forced storm surges. Here we
apply a novel modelling framework to estimate past and/or present and future storm-surge-level and extreme-sea-level probabilities along the coastlines of southern
China, Vietnam, Cambodia, Thailand, and Malaysia. A regional hydrodynamic
model is configured to simulate 10 000 years of synthetic tropical cyclone
activity, representative of a past/present (1980–2017) and high-emission-scenario future (2015–2050) period. Results show that extreme storm surges, and therefore total water levels, will increase substantially in the coming decades, driven by an increase in the frequency of intense tropical
cyclones. Storm surges along the southern Chinese and northern and southern Vietnamese
coastlines increase by up to 1 m, significantly larger than expected changes in mean sea-level rise over the same period. The length of coastline that is presently exposed to storm surge levels of 2.5 m or greater will more than double by 2050. Sections of Cambodian, Thai, and Malaysian coastlines are projected to experience storm surges (at higher return periods) in the
future, not previously seen, due to a southward shift in tropical cyclone
tracks. Given these findings, coastal flood management and adaptation in
these areas should be reviewed for their resilience against future extreme
sea levels.

Abstract. Billions of historical climatological observations remain
unavailable to science as they exist only on paper, stored in numerous
archives around the world. The conversion of these data from paper to
digital could transform our understanding of historical climate variations,
including extreme weather events. Here we demonstrate how the rescue of such
paper observations has improved our understanding of a severe windstorm that
occurred in February 1903 and its significant impacts. By assimilating newly
rescued atmospheric pressure observations, the storm is now credibly
represented in an improved reanalysis of the event. In some locations this
storm produced stronger winds than any event during the modern period
(1950–2015) and it is in the top-4 storms for strongest winds anywhere over
land in England and Wales. As a result, estimates of risk from severe
storms, based on modern period data, may need to be revised. Examining the
atmospheric structure of the storm suggests that it is a classic
Shapiro–Keyser-type cyclone with "sting-jet" precursors and associated
extreme winds at locations and times of known significant damage. Comparison
with both independent observations and qualitative information, such as
photographs and written accounts, provides additional evidence of the
credibility of the atmospheric reconstruction, including sub-daily
rainfall variations. Simulations of the storm surge resulting from this
storm show a large coastal surge of around 2.5 m, comparing favourably with
newly rescued tide gauge observations and adding to our confidence in the
reconstruction. Combining historical rescued weather observations with
modern reanalysis techniques has allowed us to plausibly reconstruct a
severe windstorm and associated storm surge from more than 100 years ago,
establishing an invaluable end-to-end tool to improve assessments of risks
from extreme weather.

Abstract. This paper reviews the state of the art in storm surge forecasting and its particular application in the northern Adriatic Sea. The city of Venice already depends on operational storm surge forecasting systems to warn the population and economy of imminent flood threats, as well as help to protect the extensive cultural heritage. This will be more important in the future, with the new mobile barriers called MOSE (MOdulo Sperimentale Elettromeccanico, Experimental Electromechanical Module) that will be completed by 2021. The barriers will depend on accurate storm surge forecasting to control their operation. In this paper, the physics behind the flooding of Venice is discussed, and the state of the art of storm surge forecasting in Europe is reviewed. The challenges for the surge forecasting systems are analyzed, especially in view of uncertainty. This includes consideration of selected historic extreme events that were particularly difficult to forecast. Four potential improvements are identified: (1) improve meteorological forecasts, (2) develop ensemble forecasting, (3) assimilation of water level measurements and (4) develop a multimodel approach.