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. Flooding is of particular concern in low-lying coastal zones that are prone to flooding impacts from multiple drivers, such as oceanographic (storm surge and wave), fluvial (excessive river discharge), and/or pluvial (surface runoff). In this study, we analyse, for the first time, the compound flooding potential along the contiguous United States (CONUS) coastline from all flooding drivers, using observations and reanalysis data sets. We assess the overall dependence from observations by using Kendall's rank correlation coefficient (τ) and tail (extremal) dependence (χ). Geographically, we find the highest dependence between different drivers at locations in the Gulf of Mexico, southeastern, and southwestern coasts. Regarding different driver combinations, the highest dependence exists between surge–waves, followed by surge–precipitation, surge–discharge, waves–precipitation, and waves–discharge. We also perform a seasonal dependence analysis (tropical vs. extra-tropical season), where we find higher dependence between drivers during the tropical season along the Gulf and parts of the East Coast and stronger dependence during the extra-tropical season on the West Coast. Finally, we compare the dependence structure of different combinations of flooding drivers, using observations and reanalysis data, and use the Kullback–Leibler (KL) divergence to assess significance in the differences of the tail dependence structure. We find, for example, that models underestimate the tail dependence between surge–discharge on the East and West coasts and overestimate tail dependence between surge–precipitation on the East Coast, while they underestimate it on the West Coast. The comprehensive analysis presented here provides new insights on where the compound flooding potential is relatively higher, which variable combinations are most likely to lead to compounding effects, during which time of the year (tropical versus extra-tropical season) compound flooding is more likely to occur, and how well reanalysis data capture the dependence structure between the different flooding drivers.

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 caused by these four main flooding sources using state-of-the-art databases with homogenous forcing (i.e., ERA5). First, we perform an analysis to assess 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; 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's 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 hotspots of compound flooding potential located along the southern coast of the North Atlantic Ocean and the northern coast of the Mediterranean Sea.

Abstract. Flooding is of particular concern in low-lying coastal zones that are prone to flooding impacts from multiple drivers: oceanographic (storm surge and wave), fluvial (excessive river discharge), and/or pluvial (surface runoff). In this study, we analyse for the first time the compound flooding potential along the contiguous United States (CONUS) coastline from all flooding drivers, using observations and reanalysis datasets. We assess the overall dependence from observations by using Kendall’s rank correlation coefficient (τ) and tail (extremal) dependence (χ). Geographically, we find highest dependence between different drivers at locations in the Gulf of Mexico, southeast, and southwest coasts. Regarding different driver combinations, the highest dependence exists between surge-waves, followed by surge-precipitation, surge-discharge, waves-precipitation, and waves-discharge. We also perform a seasonal dependence analysis (tropical vs extra-tropical season), where we find higher dependence between drivers during the tropical season along the Gulf and parts of the East coast and stronger dependence during the extra-tropical season on the West coast. Finally, we compare the dependence structure of different combinations of flooding drivers using observations and reanalysis data and use the Kullback–Leibler (KL) Divergence to assess significance in the differences of the tail dependence structure. We find, for example, that models underestimate the tail dependence between surge-discharge on the East and West coasts and overestimate tail dependence between surge-precipitation on the East coast, while they underestimate it on the West coast. The comprehensive analysis presented here provides new insights on where compound flooding potential is relatively higher, which variable combinations are most likely to lead to compounding effects, during which time of the year (tropical versus extra-tropical season) compound flooding is more likely to occur, and how well reanalysis data captures the dependence structure between the different flooding drivers.

Coastal compound flooding events occur when extreme events of rainfall, river discharge and sea level coincide and collectively increase water surface elevation, exacerbating flooding. The meteorological conditions that generate these events are usually low-pressure systems that generate high winds and intense rainfall. In this study, we identify the types of synoptic atmospheric conditions that are typically associated with coastal compound events using a weathertype approach, for the North Atlantic coastlines (encompassing northwest Europe and the east coast of the United States). Compound events are identified along the estuaries of the study region from 1980 to 2014 based on an impact function defined by water surface elevation that resulted from the combination of river discharge and sea level. We find that compound events are more frequent along European as opposed to U.S. coastlines. In both cases, they are associated with a few dominant weather patterns. European hotspots of compound events are concentrated in the west coast of United Kingdom, the northwest coast of the Iberian Peninsula and around the Strait of Gibraltar.These areas share the same weather patterns which represent the main pathways of storms that cross the North Atlantic Ocean. In the case of U.S. locations, the areas with highest number of compound events are located mainly in the Gulf of Mexico and along Mexico and along the mid-eastern U.S. coastlines. In these areas, compound events are produced by transitional weather patterns, which describe storms that travel northward parallel to the coastline. Splitting the occurrence of compound events in the corresponding weather types discriminates the interannual variability based on the relationship with dominant climate indices in the North Atlantic Ocean.

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