NDLI: Statistical modeling and trend detection of extreme sea level records in the Pearl River Estuary

Content Provider	Springer Nature Link
Author	Wang, Weiwen Zhou, Wen
Copyright Year	2017
Abstract	Sea level rise has become an important issue in global climate change studies. This study investigates trends in sea level records, particularly extreme records, in the Pearl River Estuary, using measurements from two tide gauge stations in Macau and Hong Kong. Extremes in the original sea level records (daily higher high water heights) and in tidal residuals with and without the 18.6-year nodal modulation are investigated separately. Thresholds for defining extreme sea levels are calibrated based on extreme value theory. Extreme events are then modeled by peaks-over-threshold models. The model applied to extremes in original sea level records does not include modeling of their durations, while a geometric distribution is added to model the duration of extremes in tidal residuals. Realistic modeling results are recommended in all stationary models. Parametric trends of extreme sea level records are then introduced to nonstationary models through a generalized linear model framework. The result shows that, in recent decades, since the 1960s, no significant trends can be found in any type of extreme at any station, which may be related to a reduction in the influence of tropical cyclones in the region. For the longer-term record since the 1920s at Macau, a regime shift of tidal amplitudes around the 1970s may partially explain the diverse trend of extremes in original sea level records and tidal residuals.
Starting Page	383
Ending Page	396
Page Count	14
File Format	PDF
ISSN	02561530
Journal	Advances in Atmospheric Sciences
Volume Number	34
Issue Number	3
e-ISSN	18619533
Language	English
Publisher	Science Press
Publisher Date	2017-01-31
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	sea level rise extreme climate change extreme value theory Pearl River Estuary Atmospheric Sciences Meteorology Geophysics/Geodesy
Content Type	Text
Resource Type	Article
Subject	Atmospheric Science

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