The Sea-Level Changes in Hong Kong From Tide-Gauge Records and Remote Sensing Observations Over the Last Seven Decades

Zou, Fang; Tenzer, Robert; Fok, Hok Sum; Meng, Guojie; Zhao, Qian

doi:10.1109/jstars.2021.3087263

Cited by 10 publications

(4 citation statements)

References 62 publications

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“…5 mm yr −1(Zou et al 2021, Ministry of Natural Resources 2023, and the mean subsidence rate is about 2.5 mm yr −1(Ma et al 2019, Wang et al 2012b. The sum of the two rates is 6 mm yr −1 , consistent with the findings ofNicholls et al (2021).…”

supporting

confidence: 80%

Characterization and process understanding of tropical cyclone-induced floods derived from observations in Shenzhen, China

Liu,

Tian,

Dobbie

et al. 2023

Environ. Res. Lett.

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Coastal cities like Shenzhen are confronting escalating flood risks under the combined impact of climate change and rapid urbanization, especially the tropical cyclones (TC)-induced flood. Incorporating the impact of climate change and urbanization on the flood, this study constructed a new TC-induced flood model on western Shenzhen embedded with a unique statistical approach. Based on extensive historical data and machine learning techniques, the temporal characteristics and changes of flooding were revealed. The results reveal an increase in the frequency of TC-induced floods between 1964-2022, especially after the 1990s, which is attributed to a decrease in the distance of the location of the maximum intensity of TCs (observed within an 800km range of the study area) relative to the land, averaging a reduction of 11.4 km per decade. This shift towards land is likely due to changes in the locations of TC genesis. Furthermore, the "rainfall sea level" threshold for western Shenzhen was accordingly derived from the results of modelling, which would enable decision-makers to quickly assess TC-induced flood risks. The study's proposed methods offer alternative approaches for predicting TC-induced floods in regions where the gathering of hydro-meteorological data is challenging or where economic and technological resources are limited.

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supporting

confidence: 80%

Characterization and process understanding of tropical cyclone-induced floods derived from observations in Shenzhen, China

Liu,

Tian,

Dobbie

et al. 2023

Environ. Res. Lett.

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“…The increase in SST in what is known as the Indian Ocean Dipole was also found to increase SLR rates [23]. The warming effects of ENSO (El Niño oscillations) events were also found, alongside other climatic components, to affect SLR in southeast Asia [39,40].…”

Section: Climatic Driversmentioning

confidence: 89%

Exploring Key Aspects of Sea Level Rise and Their Implications: An Overview

Elneel,

Zitouni,

Mukhtar

et al. 2024

Water

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Sea level rise (SLR) is one of the most pressing challenges of climate change and has drawn noticeable research interest over the past few decades. Factors induced by global climate change, such as temperature increase, have resulted in both direct and indirect changes in sea levels at different spatial scales. Various climatic and non-climatic events contribute to sea level changes, posing risks to coastal and low-lying areas. Nevertheless, changes in sea level are not uniformly distributed globally due to several regional factors such as wave actions, storm surge frequencies, and tectonic land movement. The high exposure to those factors increases the vulnerability of subjected areas to SLR impacts. The impacts of events induced by climate change and SLR are reflected in biophysical, socioeconomic, and environmental aspects. Different indicator-based and model-based approaches are used to assess coastal areas’ vulnerabilities, response to impacts, and implementation of adaptation and mitigation measures. Various studies have been conducted to project future SLR impacts and evaluate implemented protection and adaptation approaches, aiding policymakers in planning effective adaptation and mitigation measures to reduce damage. This paper provides an overview of SLR and its key elements, encompassing contributing factors, impacts, and mitigation and adaptation measures, featuring a dedicated section on the Arabian Gulf, a semi-enclosed sea.

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“…Among these, the impact of global climate change on sea level is both long term and periodic, which is also manifested in the study area. Furthermore, the study area is located in the western Pacific and is therefore significantly affected by ENSO, which exhibits quasi-periodicity with a cycle of 2-7 years [18,34,77,78]. To more explicitly analyze this influence, the IMF8, IMF9, and IMF10 components corresponding to the period of QUB are superimposed and reconstructed, and subsequently denoted as IMF8-10.…”

Section: Analysis Of the Impact Of Enso On Sea-level Changementioning

confidence: 99%

Multiscale Analysis and Prediction of Sea Level in the Northern South China Sea Based on Tide Gauge and Satellite Data

Yang

Cheng

Tsou

et al. 2023

JMSE

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Under the influence of global warming, the problem of sea-level rise is becoming increasingly prominent. The northern part of the South China Sea (SCS) is low lying, with intense economic development, and densely populated. These characteristics make the region extremely sensitive to the consequences of rising sea levels. This study aims to reveal the trends of sea-level changes in the northern SCS and provide scientific insights into the potential flooding risks in low-lying areas. To achieve this, the Ensemble Empirical Mode Decomposition (EEMD) method is used to analyze the water level time series data from three tide gauges along the coast of Hong Kong. This analysis reveals the multidimensional change characteristics and response mechanisms of the sea level in the SCS. The findings reveal distinct seasonal, interannual, decadal, and interdecadal variations in sea-level changes. Furthermore, we explore the impact of the El Niño-Southern Oscillation (ENSO) on sea-level changes in the study area, finding a 6-month lagged correlation between the sea level and ENSO. Spatially, the rate of sea-level change is faster in nearshore areas than in the open ocean and higher in the northern regions than in the southern regions. The Multifractal Detrended Fluctuation Analysis (MF-DFA) method is employed to analyze the sea-level change time series, revealing long-range correlations and multifractal characteristics. In addition, we propose a sea-level prediction method that combines EEMD with Long Short-Term Memory (LSTM) neural networks and conducts empirical research on sea-level changes in the northern South China Sea. The results indicate that the EEMD-LSTM model outperforms the standalone LSTM model in terms of predictive accuracy, effectively eliminating noise from signals and providing a valuable reference. In summary, this research delves into the multiscale characteristics and influencing factors of sea-level changes in the northern SCS, proposing an improved sea-level prediction method that integrates EEMD and LSTM. The findings lay the groundwork for evaluating the risks of sea-level rise in low-lying regions of the northern SCS and inform future response strategies.

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The Sea-Level Changes in Hong Kong From Tide-Gauge Records and Remote Sensing Observations Over the Last Seven Decades

Cited by 10 publications

References 62 publications

Characterization and process understanding of tropical cyclone-induced floods derived from observations in Shenzhen, China

Characterization and process understanding of tropical cyclone-induced floods derived from observations in Shenzhen, China

Exploring Key Aspects of Sea Level Rise and Their Implications: An Overview

Multiscale Analysis and Prediction of Sea Level in the Northern South China Sea Based on Tide Gauge and Satellite Data

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