Estimation of extreme sea levels along the Bangladesh coast due to storm surge and sea level rise using EEMD and EVA

Abstract

[1] Extreme sea levels due to storm surge and future sea level rise (SLR) in the year 2050 are estimated using ensemble empirical mode decomposition (EEMD) and extreme value analysis (EVA) based on long-term sea level records from Hiron Point (HP) on the coast of western Bangladesh. EEMD is an adaptive method that can detrend the nonlinear trend and separate the tidal motions from the original sea level records to reconstruct storm surge levels at HP. The reconstructed storm surge levels are then applied to EVA to obtain the extreme storm surges in the target return periods at a 95% confidence interval (CI). The 30, 50, and 100 year return levels at HP obtained by EVA are 1.59, 1.66, and 1.75 m. The SLR trend obtained from EEMD is 4.46 mm/yr over April 1990 to March 2009, which is larger than the recent altimetry-based global rate of 3.3 6 0.4 mm/yr over the period from 1993 to 2007. The resulting SLR in 2050 is estimated as 0.34 m. Therefore, the extreme sea level in 2050 due to SLR and the storm surge at a 100 year return level would be 2.09 m (95% CI from 1.91 to 2.48 m). The SLR depends not only on changes in the mass and volume of sea water but also on other factors, such as local subsidence, river discharge, sediment and the effects of vegetation. The residual nonlinear trend of SLR obtained from EEMD can be regarded as an adaptive sea level after considering those factors and their nonlinearity.Citation: Lee, H. S. (2013), Estimation of extreme sea levels along the Bangladesh coast due to storm surge and sea level rise using EEMD and EVA,

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

“…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).…”

Modelling Extreme Sea Levels Due to Sea Level Rise and Storm Surge in the Seto Inland Sea, Japan

“…On the other hands, in the coastal defense against extreme storm surges using deterministic hydrodynamic modeling approaches (2013a; Haigh et al, 2013b) or statistical modeling approaches (Butler et al, 2007a;2007b;2013a;Haigh et al, 2013b), the impact of SLR is not usually and explicitly considered, either. Lee (2013) recently reported a novel way to explicitly estimate the regional extreme sea levels due to both sea level rise and storm surge in Bangladesh, and showed further projection for regional scenarios of extreme sea levels. The Seto Inland Sea (SIS) is a largest long channel-shaped enclosed coastal sea in the western part of Japan with a size of about 23,000 km 2 , a length of about 500 km and an average depth of about 38 m (Tsuge and Washida, 2003;Yamamoto, 2003;Yanagi et al, 1982).…”

“…In this study, we estimate the extreme sea level due to (1) storm surge and (2) future SLR based on data-driven statistical modeling approach using ensemble empirical mode decomposition (EEMD) and extreme value analysis (EVA) with long-term sea level records in and around the SIS, Japan, as illustrated in Lee (2013). We demonstrate regional projection of extreme sea level (=extreme positive storm surges + SLR) to the mid-and long-term future by the years of 2050 and 2100.…”

Cyclone disaster mapping, monitoring and management using satellite remote sensing and spatial analysis

“…To develop the local sea level rise scenario for evaluating the climate change impact on future tropical cyclones, a historical gauge station data were acquired from Bangladesh Water Development Board (BWDB). However, the projection of local sea level rise scenarios was from the study of Lee (2013) as this used the same sources of data of the same location in his analysis.…”

“…The local scenario was adopted from the study of Lee (2013) Bangladesh (Sarwar 2013;Islam et al 2016). This study followed Lee's (2013) result as the selected tide gauge station (Hiron point) was closed to the present study site. The 0.34 m sea level rise scenario selected was integrated with different return period surge models for estimating the climate change impacts.…”