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Sea-level Rise

Effects may vary

Hamlington, B. D., et al. “Observation‐Driven Estimation of the Spatial Variability of 20th Century Sea Level Rise.” Journal of Geophysical Research: Oceans. DOI: 10.1002/2017JC013486

Oceanographers, and scientists in general, often talk about how their measurements might vary depending on the scale they are looking at. In designing their experiments, they must select an appropriate size, region, or length of time to observe. Doing so necessarily limits what sort of phenomena can be resolved. This age-old truism has been the subject of much discussion by some of the great thinkers in our field.

Consider, for example, the effects of sea level change on our planet. Over the past 20 years, satellites have clearly indicated that the global sea level is rising. Several studies based on observational and modeling data have estimated that the global average change is in the range of 1 to 2 mm per year. Many groups have combined these global estimates with historic, local tide gauge data to better understand sea level trends over the past hundred years.

The amount of local sea level change can, however, vary substantially depending on the location. The variability is due to a number of factors including local latitude, bathymetry, and terrestrial inputs like river runoff or glacial melt. Understanding this variability, and projecting it into the future, is of the utmost importance for coastal communities looking to protect their infrastructure and surrounding ecosystems. Dr. Benjamin Hamlington of Old Dominion University sought to better understand local sea level change by reanalyzing historical tide gauge data.

Tide gauges have been around since the beginning of the 19th century. Since then, the instruments have evolved from a pen attached to a float to digital ultrasonic recorders. Scientists and, more recently, local officials attach these devices to structures in the ocean to measure sea height. Sea level height has been recorded almost continuously at several specific locations across the globe. Hamlington notes, however, how inconsistent these long records are both spatially and temporally – the stations are clustered in the northern hemisphere, often have recording gaps, and do not take into account changes in the instruments position on land relative to the sea surface.

Figure 1 – The upper panel is a global map generated from the climate model. The colored dots indicate the gauge locations. The lower plot compares the mean sea level change measured at each station with the modeled values at those points. The y-axis in mm/yr. Blue dots are values from the model and red are from the gauges (adapted from Hamlington et al., 2018).

To reconstruct the local changes in sea level, Hamlington and his collaborators proposed an equation for computing sea level based on ongoing land movements from the last ice age, long term atmospheric trends, ocean dynamics, ice melt patterns, groundwater depletion, and water impoundment by structures (such as dams or docks). The team used this model to generate global maps of sea level change and compared the results to 15 physical tide gauges from around the world. The team selected only stations that had nearly complete records during the 20th century, did not have any gaps in the time series, and were not moved up or down in elevation on land.

By comparing the model results to the actual measurements, Hamlington concluded that the rate of global mean sea level rise is underestimated at the gauge locations (fig. 1). The average difference between the measurements and the model was 0.08 mm/yr. But take note, the team does not suggest that global sea level rise estimates are necessarily off. It is, again, an issue of scale ­– changes at a large scale might look very different locally. The group proposed a number of mechanisms underlying this discrepancy. The most likely is that the gauges are significantly affected by inputs not associated with land movements from the last ice age.

Hamlington points out that his group’s approach has several uncertainties and caveats. But their method represents one of few attempts to comprehensively understand regional sea level trend variability. Moreover, their model allows researchers to explore how individual physical factors might influence the sea level change at a given location. By accounting for such spatial variability, civil engineers and city planners might be able to better prepare their communities for future sea level rise.

Eric Orenstein

Eric is a PhD student at the Scripps Institution of Oceanography. His research in the Jaffe Laboratory for Underwater Imaging focuses on developing methods to quantitatively label image data coming from the Scripps Plankton Camera System. When not science-ing, Eric can be found surfing, canoeing, or trying to learn how to cook.


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