Coastal communities across the United States (U.S.) are experiencing an increase in the frequency of high‐tide flooding (HTF). This increase is mainly due to sea‐level rise (SLR), but other factors such as intra‐ to inter‐annual mean sea level variability, tidal anomalies, and non‐tidal residuals also contribute to HTF events. Here we introduce a novel decomposition approach to develop and then analyze a new database of different sea‐level components. Those components represent processes that act on various timescales to contribute to HTF along the U.S. coastline. We find that the relative importance of components to HTF events strongly varies in space and time. Tidal anomalies contribute the most along the west and northeast coasts, where HTF events mostly occur in winter. Non‐tidal residuals are most important along the Gulf of Mexico and mid‐Atlantic coasts, where HTF events mostly occur in fall. We also quantify the minimum number of components that were required to cause HTF events in the past and how this number changed over time. The results highlight that at present, due to SLR, fewer components are needed to combine to push water levels above HTF thresholds, but tidal anomalies alone are still not sufficient to reach HTF thresholds in most locations. Finally, we explore how co‐variability between different components leads to compounding effects. In some places, positive correlation between sea‐level components leads to significantly more HTF events than would be expected if sea‐level components were uncorrelated, whereas in other places negative correlation leads to fewer HTF events.

Rocks are heterogeneous multiscale porous media: two rock samples with identical bulk properties can vary widely in microstructure. The advent of digital rock technology and modern 3‐D printing provides new opportunities to replicate rocks. However, the inherent trade‐off between imaging resolution and sample size limits the scales over which microstructure and macrostructure can be identified and related to each other. Here, we develop a multiscale digital rock construction strategy by combining X‐ray computed microtomography and focused‐ion beam (FIB)‐scanning electron microscope (SEM) images, and we apply the technique to a tight sandstone. The computed tomography (CT) scanning images characterize macroscale pore structures, while the FIB‐SEM images capture microscale pore textures. The FIB‐SEM images are then coupled to CT images via a template‐matching algorithm and superposition. Bulk properties, including porosity and pore and throat size distribution, can be recovered with this approach. Permeability prediction with a pore network model for the largest connected pore network are 3 orders and 1 order of magnitude greater than the bulk rock measured value using the CT‐only and the SEM‐CT coupled images, respectively.

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