Global Mean Sea Level Change Projections up to 2100 Using a Weighted Singular Spectrum Analysis

This paper forecasts global mean sea level (GMSL) changes from 2024 to 2100 using weighted singular spectrum analysis (SSA) that considers the formal errors of the previous GMSL time series. The simulation experiments are first carried out to evaluate the performance of the weighted and traditional...

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Main Authors: Fengwei Wang, Yunzhong Shen, Jianhua Geng, Qiujie Chen
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Journal of Marine Science and Engineering
Subjects:
Online Access:https://www.mdpi.com/2077-1312/12/12/2124
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author Fengwei Wang
Yunzhong Shen
Jianhua Geng
Qiujie Chen
author_facet Fengwei Wang
Yunzhong Shen
Jianhua Geng
Qiujie Chen
author_sort Fengwei Wang
collection DOAJ
description This paper forecasts global mean sea level (GMSL) changes from 2024 to 2100 using weighted singular spectrum analysis (SSA) that considers the formal errors of the previous GMSL time series. The simulation experiments are first carried out to evaluate the performance of the weighted and traditional SSA approaches for GMSL change prediction with two evaluation indices, the root mean square error (RMSE) and mean absolute error (MAE). The results show that all the RMSEs and MAEs of the weighted SSA are smaller than those of the traditional SSA, indicating that the weighed SSA can predict GMSL changes more accurately than the traditional SSA. The real GMSL change rate derived from weighted SSA is approximately 1.70 ± 0.02 mm/year for 1880–2023, and the predicted GMSL changes with the first two reconstructed components reaches 796.75 ± 55.92 mm by 2100, larger than the 705.25 ± 53.73 mm predicted with traditional SSA, with respect to the baseline from 1995 to 2014. According to the sixth Assessment Report of Intergovernmental Panel on Climate Change (IPCC AR6), the GMSL change by 2100 is 830.0 ± 152.42 mm/year with the high-emission scenarios is closer to weighted SSA than traditional SSA, though SSA predictions are within the prediction range of IPCC AR6. Therefore, the weighted SSA can provide an alternative future GMSL rise prediction.
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spelling doaj-art-a16ae3d0d1c541c9b1bae097f2b947eb2025-08-20T02:00:38ZengMDPI AGJournal of Marine Science and Engineering2077-13122024-11-011212212410.3390/jmse12122124Global Mean Sea Level Change Projections up to 2100 Using a Weighted Singular Spectrum AnalysisFengwei Wang0Yunzhong Shen1Jianhua Geng2Qiujie Chen3State Key Laboratory of Marine Geology, Tongji University, Shanghai 200092, ChinaCollege of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, ChinaState Key Laboratory of Marine Geology, Tongji University, Shanghai 200092, ChinaCollege of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, ChinaThis paper forecasts global mean sea level (GMSL) changes from 2024 to 2100 using weighted singular spectrum analysis (SSA) that considers the formal errors of the previous GMSL time series. The simulation experiments are first carried out to evaluate the performance of the weighted and traditional SSA approaches for GMSL change prediction with two evaluation indices, the root mean square error (RMSE) and mean absolute error (MAE). The results show that all the RMSEs and MAEs of the weighted SSA are smaller than those of the traditional SSA, indicating that the weighed SSA can predict GMSL changes more accurately than the traditional SSA. The real GMSL change rate derived from weighted SSA is approximately 1.70 ± 0.02 mm/year for 1880–2023, and the predicted GMSL changes with the first two reconstructed components reaches 796.75 ± 55.92 mm by 2100, larger than the 705.25 ± 53.73 mm predicted with traditional SSA, with respect to the baseline from 1995 to 2014. According to the sixth Assessment Report of Intergovernmental Panel on Climate Change (IPCC AR6), the GMSL change by 2100 is 830.0 ± 152.42 mm/year with the high-emission scenarios is closer to weighted SSA than traditional SSA, though SSA predictions are within the prediction range of IPCC AR6. Therefore, the weighted SSA can provide an alternative future GMSL rise prediction.https://www.mdpi.com/2077-1312/12/12/2124global mean sea level risesingular spectrum analysisforecastingformal error
spellingShingle Fengwei Wang
Yunzhong Shen
Jianhua Geng
Qiujie Chen
Global Mean Sea Level Change Projections up to 2100 Using a Weighted Singular Spectrum Analysis
Journal of Marine Science and Engineering
global mean sea level rise
singular spectrum analysis
forecasting
formal error
title Global Mean Sea Level Change Projections up to 2100 Using a Weighted Singular Spectrum Analysis
title_full Global Mean Sea Level Change Projections up to 2100 Using a Weighted Singular Spectrum Analysis
title_fullStr Global Mean Sea Level Change Projections up to 2100 Using a Weighted Singular Spectrum Analysis
title_full_unstemmed Global Mean Sea Level Change Projections up to 2100 Using a Weighted Singular Spectrum Analysis
title_short Global Mean Sea Level Change Projections up to 2100 Using a Weighted Singular Spectrum Analysis
title_sort global mean sea level change projections up to 2100 using a weighted singular spectrum analysis
topic global mean sea level rise
singular spectrum analysis
forecasting
formal error
url https://www.mdpi.com/2077-1312/12/12/2124
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AT yunzhongshen globalmeansealevelchangeprojectionsupto2100usingaweightedsingularspectrumanalysis
AT jianhuageng globalmeansealevelchangeprojectionsupto2100usingaweightedsingularspectrumanalysis
AT qiujiechen globalmeansealevelchangeprojectionsupto2100usingaweightedsingularspectrumanalysis