Analysis of relative sea level variations and trends in the Chesapeake Bay: Is there evidence for acceleration in sea level rise?

Abstract

Over the past few decades the pace of relative sea level rise (SLR) in the Chesapeake Bay (CB) has been 2-3 times faster than that of the globally mean absolute sea level. Our study is part of ongoing research that tries to determine if this SLR trend is continuing at the same pace, slowing down (SLR deceleration) or speeding up (SLR acceleration). We introduce a new analysis method for sea level data that is based on Empirical Mode Decomposition (EMD) and Hilbert-Huang Transform (HHT); the analysis separates the SLR trend from other oscillating modes of different scales. Bootstrap calculations using thousands of iterations were used to test the robustness of the method and obtain confidence levels. The analysis shows that most sea level records in the CB have significant positive SLR acceleration, so the SLR rates today are about twice the SLR rates of 60 years ago. The acceleration rates of our calculations are larger than some past studies, but comparable to recent results [1] who show accelerated SLR "hotspots" in the coastal areas between Cape Hatteras and Cape Cod. The results have implications for projections of future SLR and the impact on flooding risks in the Hampton Roads area. The contributions to SLR from land subsidence and climate-related changes in ocean circulation need further research.

Gulf Stream's induced sea level rise and variability along the U.S. mid‐Atlantic coast

“…Record length ranges from three stations with relatively short records of 25–37 years (Duck; Chesapeake Bay Bridge Tunnel, CBBT; Lewisetta) to two stations with relatively long records of over 100 years (Atlantic City and Baltimore). Most of these stations have been used in previous studies of SLR [ Boon et al ., ; Boon , ; Ezer and Corlett , , ; Sallenger et al ., ]. The sea level data spread over a large geographical distance, so one has to distinguish between local and large‐scale impacts.…”

“…Monthly mean sea level records from 10 tide gauge stations (7 in the CB and 3 along the Atlantic coast) were obtained from NOAA's “verified data” (http://tidesandcurrents.noaa.gov/). The CB stations (same as in Ezer and Corlett , , ) are spread from the city of Norfolk, VA, (Sewells Point) in the south to Baltimore, MD, in the north and along the Atlantic coast from Duck, NC, in the south to Atlantic City, NJ, in the north (Figure ). Record length ranges from three stations with relatively short records of 25–37 years (Duck; Chesapeake Bay Bridge Tunnel, CBBT; Lewisetta) to two stations with relatively long records of over 100 years (Atlantic City and Baltimore).…”

“…For example, standard curve‐fitting and filtering methods would have difficulties separating the sea level trend from long‐term variations such as the global 60‐year oscillation cycle [ Chambers et al ., ]. This difficulty led to the development of a new analysis method for sea level [ Ezer and Corlett , , ], which can remove high‐frequency oscillations as well as cycles with long periods that are comparable to the record length itself. We will consider in this study scales ranging from a few months to decadal and long‐term climate‐scale trends.…”

“…We will consider in this study scales ranging from a few months to decadal and long‐term climate‐scale trends. The analysis method is based on Empirical Mode Decomposition (EMD)/Hilbert‐Huang Transformation (HHT) [ Huang et al ., ; Wu and Huang , ; Wu et al ., ; Huang and Wu , ]; to the best of our knowledge, the EMD/HHT method has not been used for analyzing sea level trend before it was introduced by Ezer and Corlett [, ]. Ezer and Corlett used 5000 bootstrap simulations [ Mudelsee , ], i.e., randomly resampling the data itself, to calculate confidence intervals, and show that the SLR trends obtained from the EMD/HHT analysis are accurate within about ±0.5 mm yr −1 with 95% confidence level.…”

“…The HHT‐calculated SLR trends and acceleration in the CB compared very well with results obtained from standard curve fitting methods [ Ezer and Corlett , ]. The method was also used to calculate future projections of local SLR based on extrapolation of past SLR rates and acceleration [ Ezer and Corlett , ]; other global SLR projections are often based on climate numerical models [ Schaeffer et al ., ].…”