Influence of El Nino on the variability of global shoreline position

In this study, the authors use a global dataset of satellite-derived shoreline positions, and demonstrate that their interannual evolution is dominated by El Nino through its worldwide influence of sea level, river discharge and ocean waves Coastal zones are fragile and complex dynamical systems that are increasingly under threat from the combined effects of anthropogenic pressure and climate change. Using global satellite derived shoreline positions from 1993 to 2019 and a variety of reanalysis products, here we show that shorelines are under the influence of three main drivers: sea-level, ocean waves and river discharge. While sea level directly affects coastal mobility, waves affect both erosion/accretion and total water levels, and rivers affect coastal sediment budgets and salinity-induced water levels. By deriving a conceptual global model that accounts for the influence of dominant modes of climate variability on these drivers, we show that interannual shoreline changes are largely driven by different ENSO regimes and their complex inter-basin teleconnections. Our results provide a new framework for understanding and predicting climate-induced coastal hazards.

Automated summary

Using a global dataset of satellite-derived shoreline positions, the authors demonstrate that the interannual evolution of shorelines is mainly influenced by El Nino, which affects sea level, river discharge, and ocean waves on a worldwide scale. Coastal zones are fragile and complex dynamical systems that face increasing threats from anthropogenic pressure and climate change. Through analyzing global satellite data from 1993 to 2019, the study reveals that shorelines are impacted by three main drivers: sea level, ocean waves, and river discharge. The research also shows that interannual changes in shorelines are primarily driven by different ENSO regimes and their complex teleconnections between basins. These findings provide a new framework for understanding and predicting climate-induced coastal hazards.