Observation-Driven Estimation of the Spatial Variability of 20Century Sea Level Rise

Citation data:

Journal of Geophysical Research: Oceans, ISSN: 2169-9291, Vol: 123, Issue: 3, Page: 2129-2140

Publication Year:
2018
Usage 3
Abstract Views 3
Captures 12
Readers 12
Mentions 1
Blog Mentions 1
Social Media 15
Tweets 15
Repository URL:
https://digitalcommons.odu.edu/oeas_fac_pubs/312
DOI:
10.1002/2017jc013486
Author(s):
Hamlington, B. D.; Burgos, A.; Thompson, P. R.; Landerer, F. W.; Piecuch, C. G.; Adhikari, S.; Caron, L.; Reager, J. T.; Ivins, E. R.
Publisher(s):
American Geophysical Union (AGU)
Tags:
Earth and Planetary Sciences; Agricultural and Biological Sciences; Environmental Science; Sea level; Trends; 20th century; Climate; Oceanography
Most Recent Tweet View All Tweets
Most Recent Blog Mention
article description
Over the past two decades, sea level measurements made by satellites have given clear indications of both global and regional sea level rise. Numerous studies have sought to leverage the modern satellite record and available historic sea level data provided by tide gauges to estimate past sea level rise, leading to several estimates for the 20century trend in global mean sea level in the range between 1 and 2 mm/yr. On regional scales, few attempts have been made to estimate trends over the same time period. This is due largely to the inhomogeneity and quality of the tide gauge network through the 20century, which render commonly used reconstruction techniques inadequate. Here, a new approach is adopted, integrating data from a select set of tide gauges with prior estimates of spatial structure based on historical sea level forcing information from the major contributing processes over the past century. The resulting map of 20century regional sea level rise is optimized to agree with the tide gauge-measured trends, and provides an indication of the likely contributions of different sources to regional patterns. Of equal importance, this study demonstrates the sensitivities of this regional trend map to current knowledge and uncertainty of the contributing processes.