We investigate the spatial scales that are necessary to detect an externally forced signal in regional sea level within a selected fixed time period. Detection on a regional scale is challenging due to the increasing magnitude of unforced variability in dynamic sea level on progressingly smaller spatial scales. Using unforced control simulations with no evolving forcing we quantify the magnitude of regional internal variability depending on the degree of spatial averaging. We test various averaging techniques such as zonal averaging and averaging grid points within selected radii. By comparing the results from the control simulations with historical and 21st-century simulations, the procedure allows to estimate to what degree the data has to be averaged spatially in order to detect a forced signal within certain periods (e.g. periods with good observational coverage).
We find that zonal averaging over ocean basins is necessary to detect a forced signal in steric and dynamic sea level during the past 25 years, while a signal emerges in 63% of the ocean areas over the past 45 years when smoothing with a 2000 km filter or less is applied. We also demonstrate that the addition of the glacier contribution increases the signal-to-noise ratio of regional sea level changes, thus leading to an earlier emergence by 10–20 years away from the sources of the ice mass loss. With smoothing, this results in the detection of an external signal in 90% of the ocean areas over the past 45 years.
Institute for Atmospheric and Cryospheric Sciences, University of Innsbruck, Innrain 52f, 6020 Innsbruck, Austria;Institute of Geography, University of Bremen, Bremen, Germany;Faculty of Civil Engineering and Geosciences, Delft University of Technology, Netherlands
Recommended Citation:
Kristin Richter,Ben Marzeion,Riccardo Riva. The effect of spatial averaging and glacier melt on detecting a forced signal in regional sea level[J]. Environmental Research Letters,2017-01-01,12(3)