Sea level rise around Korea

Analysis of tide gauge station data with the ensemble empirical mode decomposition method

Yeonjoo Kim, Kwangwoo Cho

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

This study estimates the trend and acceleration of sea level rise (SLR) at the tide gauge stations around Korea as now the data from the stations are recorded for approximately 50 years, which allow us to estimate the acceleration of SLR. We use not only traditional polynomial regression analysis but also the ensemble empirical mode decomposition (EEMD) approach, whose strength is the elimination of long-term variations in sea level data, to process this relatively short-term data. The relative sea level data from the five tide gauge stations around Korea, including Mokpo, Jeju, Busan, Ulsan and Mukho are used in this study. With Jeju showing the highest trend of SLR, all stations exhibit rising trend of sea level regardless of the methods used in this study. Positive accelerations of SLR are found in four out of five stations with the highest acceleration at Mukho. We also compare the results based on the EEMD approach and those based on the regression analysis and find generally consistent results between two. While the trends show the slight differences at the five stations with no tendency toward over- or under-estimation, the accelerations are slightly lower with the EEMD approach than with the regression analysis at all four stations with positive accelerations.

Original languageEnglish
Pages (from-to)138-145
Number of pages8
JournalJournal of Hydro-Environment Research
Volume11
DOIs
Publication statusPublished - 2013 Oct 16

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Tide gages
tide gauge
Sea level
decomposition
Decomposition
Regression analysis
regression analysis
sea level
analysis
method
station
sea level rise
Polynomials
trend

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Environmental Chemistry
  • Civil and Structural Engineering
  • Water Science and Technology
  • Management, Monitoring, Policy and Law

Cite this

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abstract = "This study estimates the trend and acceleration of sea level rise (SLR) at the tide gauge stations around Korea as now the data from the stations are recorded for approximately 50 years, which allow us to estimate the acceleration of SLR. We use not only traditional polynomial regression analysis but also the ensemble empirical mode decomposition (EEMD) approach, whose strength is the elimination of long-term variations in sea level data, to process this relatively short-term data. The relative sea level data from the five tide gauge stations around Korea, including Mokpo, Jeju, Busan, Ulsan and Mukho are used in this study. With Jeju showing the highest trend of SLR, all stations exhibit rising trend of sea level regardless of the methods used in this study. Positive accelerations of SLR are found in four out of five stations with the highest acceleration at Mukho. We also compare the results based on the EEMD approach and those based on the regression analysis and find generally consistent results between two. While the trends show the slight differences at the five stations with no tendency toward over- or under-estimation, the accelerations are slightly lower with the EEMD approach than with the regression analysis at all four stations with positive accelerations.",
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N2 - This study estimates the trend and acceleration of sea level rise (SLR) at the tide gauge stations around Korea as now the data from the stations are recorded for approximately 50 years, which allow us to estimate the acceleration of SLR. We use not only traditional polynomial regression analysis but also the ensemble empirical mode decomposition (EEMD) approach, whose strength is the elimination of long-term variations in sea level data, to process this relatively short-term data. The relative sea level data from the five tide gauge stations around Korea, including Mokpo, Jeju, Busan, Ulsan and Mukho are used in this study. With Jeju showing the highest trend of SLR, all stations exhibit rising trend of sea level regardless of the methods used in this study. Positive accelerations of SLR are found in four out of five stations with the highest acceleration at Mukho. We also compare the results based on the EEMD approach and those based on the regression analysis and find generally consistent results between two. While the trends show the slight differences at the five stations with no tendency toward over- or under-estimation, the accelerations are slightly lower with the EEMD approach than with the regression analysis at all four stations with positive accelerations.

AB - This study estimates the trend and acceleration of sea level rise (SLR) at the tide gauge stations around Korea as now the data from the stations are recorded for approximately 50 years, which allow us to estimate the acceleration of SLR. We use not only traditional polynomial regression analysis but also the ensemble empirical mode decomposition (EEMD) approach, whose strength is the elimination of long-term variations in sea level data, to process this relatively short-term data. The relative sea level data from the five tide gauge stations around Korea, including Mokpo, Jeju, Busan, Ulsan and Mukho are used in this study. With Jeju showing the highest trend of SLR, all stations exhibit rising trend of sea level regardless of the methods used in this study. Positive accelerations of SLR are found in four out of five stations with the highest acceleration at Mukho. We also compare the results based on the EEMD approach and those based on the regression analysis and find generally consistent results between two. While the trends show the slight differences at the five stations with no tendency toward over- or under-estimation, the accelerations are slightly lower with the EEMD approach than with the regression analysis at all four stations with positive accelerations.

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