Is sea level rise accelerating in the Chesapeake Bay? A demonstration of a novel new approach for analyzing sea level data

Abstract

[1] Sea level data from the Chesapeake Bay are used to test a novel new analysis method for studies of sea level rise (SLR). The method, based on Empirical Mode Decomposition and Hilbert-Huang Transformation, separates the sea level trend from other oscillating modes and reveals how the mean sea level changes over time. Bootstrap calculations test the robustness of the method and provide confidence levels. The analysis shows that rates of SLR have increased from $1-3 mm y À1 in the 1930s to $4-10 mm y À1 in 2011, an acceleration of $0.05-0.10 mm y À2 that is larger than most previous studies, but comparable to recent findings by Sallenger and collaborators. While land subsidence increases SLR rates in the bay relative to global SLR, the acceleration results support Sallenger et al.'s proposition that an additional contribution to SLR from climatic changes in ocean circulation is affecting the region. Citation: Ezer, T., and W. B. Corlett (2012), Is sea level rise accelerating in the Chesapeake Bay? A demonstration of a novel new approach for analyzing sea level data, Geophys.

Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

“…Due to this controversy, in our discussion below we refer to the AMO index of Trenberth and Shea (2006) as ''the *60-year cycle of SST index.'' Tide gauge observations detected robust accelerations of SLR along the highly populated US northeast coast since 1950 and especially since 1970 (Sallenger et al 2012;Boon 2012;Ezer and Corlett 2012). Existing studies suggest that the *60-year cycle in sea level, which is present in most tide gauge stations along the US northeast coast (Kenigson and Han 2014) with rapid SLR since 1970 coinciding with the positive transition of the *60-year cycle of SST index, has a significant contribution to the observed SLR acceleration (Kopp 2013;Ezer 2013;Scafetta 2014;Kenigson and Han 2014).…”

Evaluation of empirical mode decomposition for quantifying multi-decadal variations and acceleration in sea level records

“…Already, several authors have performed an EMD on El Niño-Southern Oscillation (ENSO) indices and argued they have extracted distinct modes of interannual to multi-decadal variability (Wu and Huang, 2004;Franzke, 2009;Yang et al, 2010); their argument based solely on the fact that such modes are extracted during the EMD process, but with no physical explanation for them. The same has been done to sea level measurements made by tide gauges, and individual IMFs are interpreted as distinct climatic modes (Ezer and Corlett, 2012;Ezer et al, 2013).…”

“…IMFs extracted from various tide gauge records have been correlated with several climate indices (e.g., Ezer and Corlett, 2012;Ezer et al, 2013), which gives some credence to extracted signals. Moreover, authors have argued that the final IMF, representing the continuously increasing sea level mode, is a better representation of an acceleration, or nonlinear trend, than simply fitting a quadratic to the original data using ordinary least squares (Huang and Wu, 2008;Ezer and Corlett, 2012;Ezer et al, 2013).…”

“…Over the last decade, several papers have used the method of empirical mode decomposition (EMD) (Huang et al, 1998;Huang and Wu, 2008) to evaluate non-stationary patterns in time series as disparate as electromyographic signals (Andrade et al, 2006) and sea level (Breaker and Ruzmaikin, 2011;Ezer and Corlett, 2012;Ezer et al, 2013;Lee, 2013;Chen et al, 2014). The use of EMD in sea level records has been motivated in large part by numerous papers discussing the appearance of decadal and longer-period fluctuations in tide gauge records and global mean sea level estimates based on tide gauge records (e.g., Feng et al, 2004;Miller and Douglas, 2007;Woodworth et al, 2009;Bromirski et al, 2011;Sturges and Douglas, 2011;Chambers et al, 2012;Calafat and Chambers, 2013;Becker et al, 2014;Dangerdorf et al, 2014).…”

Choosing a Future Shoreline for the San Francisco Bay: Strategic Coastal Adaptation Insights from Cost Estimation

“…Specifically, sea level rise in estuaries will result in landward movement of both the average and storm-driven high water lines; landward migration of the salinity gradient in surface and groundwater; changes in sediment transport and deposition; and coastal "squeeze", resulting in a loss of inter-tidal wetlands as well as damage to conventional urban districts and infrastructure [4,8]. Globally, some urban estuaries are already grappling with these threats, including the Thames Estuary [9] and the Wash region of the United Kingdom [10], the Elbe in Germany [11], and the Chesapeake Bay in the United States [12]. The San Francisco Bay urban region is also constructed in an estuary context, and presents an opportunity to gain insights about various physical adaptation strategies for shoreline realignment by estimating their adaptation costs and systematically varying key drivers of those costs.…”