SLR Estimation Using CEEMDAN Near the Korean Peninsula
Abstract The rise of sea levels due to global warming is a problem of concern at an international scope and the causes are already known relatively clearly. Every year, the Intergovernmental Panel on Climate Change (IPCC) creates a scenario for greenhouse gas emissions and predicts the global average sea-level rise rate accordingly. It is necessary to estimate the rate of sea-level rise to date in creating such a scenario. In particular, since the height of the sea level changes (SLC) continuously, the errors of SLC may occur due to various causes with a fragmental analysis. To estimate the sea-level rise accurately, we applied Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is based on the Empirical Mode Decomposition (EMD) to decompose the tidal level. Through this, we discover that the differences in the local sea-level rise rate occurred even within a small area. To understand each component of tide level decomposed through CEEMDAN, we confirm the component-wise/regional correlation between tidal stations. In addition, we looked at how local sea-level rise correlated with the global meteorological phenomenon, El Niño-Southern Oscillation (ENSO) which is one of the most influential recurring climate patterns Socioeconomically..
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Preprint| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
ResearchSquare.com - (2022) vom: 23. Mai Zur Gesamtaufnahme - year:2022 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Kim, Young Jin [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| doi: |
10.21203/rs.3.rs-1011105/v1 |
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| 520 | |a Abstract The rise of sea levels due to global warming is a problem of concern at an international scope and the causes are already known relatively clearly. Every year, the Intergovernmental Panel on Climate Change (IPCC) creates a scenario for greenhouse gas emissions and predicts the global average sea-level rise rate accordingly. It is necessary to estimate the rate of sea-level rise to date in creating such a scenario. In particular, since the height of the sea level changes (SLC) continuously, the errors of SLC may occur due to various causes with a fragmental analysis. To estimate the sea-level rise accurately, we applied Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is based on the Empirical Mode Decomposition (EMD) to decompose the tidal level. Through this, we discover that the differences in the local sea-level rise rate occurred even within a small area. To understand each component of tide level decomposed through CEEMDAN, we confirm the component-wise/regional correlation between tidal stations. In addition, we looked at how local sea-level rise correlated with the global meteorological phenomenon, El Niño-Southern Oscillation (ENSO) which is one of the most influential recurring climate patterns Socioeconomically. | ||
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