Ben Hamlington (Jet Propulsion Laboratory, United States); Angelica Rodriguez (Jet Propulsion Laboratory, United States)

Sea-level rise is one of the most visible impacts of climate change, already exacerbating coastal flooding and threatening built and natural ecosystems. Since 1993, radar satellite altimeters have precisely measured sea-level rise with near-global coverage. However, such sensors are challenged in the coastal zone (within about 20 km of the coastline) due to the presence of land in the altimeter and radiometer footprint. Partly alleviating this challenge are measurements of sea level taken at in-situ tide gauges along the coast. Though tide gauge installations are spatially sparse, they reflect differences in sea-level variability due to the influence of coastal processes such as local vertical land motion, coastal waves, and river runoff. The photon counting Advanced Topography Laser Altimeter System (ATLAS) aboard ICESat-2 has a nominal footprint of ~17 m and thus has the potential to bridge these observational gaps, both along the coast between tide gauges and across the coastal ocean land to the nearshore radar altimeter limit.

Here we investigate coastal sea-level using a suite of observations consisting of tide gauges, radar altimetry and ICESat-2 measurements. We compute monthly time series along the global coastlines from each of these data sources, from which we establish a mean sea surface and estimate linear trends and variance. We assess agreement between the different statistics, with particular focus on spatial variations both perpendicular and parallel to the coastlines. For regions with good agreement, we use statistical techniques to link the various observations and uncover a best-fitting sea surface and its temporal evolution. Where the measurements are in conflict, process-based understanding, such as riverine and atmospheric influences, along with theoretical principles are leveraged to more robustly describe spatiotemporally-consistent coastal sea level.