How to improve estimates of real-time acceleration in the mean sea level signal

Watson, Phil J.

doi:10.2112/si75-157.1

Cited by 5 publications

(3 citation statements)

References 31 publications

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“…The applied methodology can be appropriately partitioned into analysis of the historical tide-gauge record and that of the AR5 ensemble projection-model outputs. The selection and application of SSA and other key steps in the analysis are broadly underpinned by unprecedented time-series research, development, and analysis of ocean water-level data [16,[22][23][24][25][26].…”

Section: Methodsmentioning

confidence: 99%

How Well Do AR5 Sea Surface-Height Model Projections Match Observational Rates of Sea-Level Rise at the Regional Scale?

Watson¹

2018

JMSE

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The reliance upon and importance of climate models continues to grow in line with strengthening evidence of a changing climate system and the necessity to provide credible projections for risk assessment to guide policy development, mitigation and adaptation responses. The utility of the models to project regional rates of sea-level rise over the course of the 21st century is reliant on evaluating model outputs against global observational data (principally altimetry products). This study compares rates of sea-level rise from observational data records (tide gauges) against the ensemble mean of the model-projection products used in AR5 at 19 sites around the world over the decade of common data coverage (2007-2016) using enhanced time-series analysis techniques. Although it could be concluded that the observational and model-projected average velocity agree (95% confidence level (CL)), error margins are comparatively wide, masking the fact that the mean velocity for the model-projection products exceed observational records for nearly all stations and Representative Concentration Pathway (RCP) experiments, and are likely in the range of 1.6-2.5 mm/year. The analysis might provide an early warning sign that the evaluation of ocean model components with respect to projected mean sea level could be relevantly improved.

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Section: Methodsmentioning

confidence: 99%

How Well Do AR5 Sea Surface-Height Model Projections Match Observational Rates of Sea-Level Rise at the Regional Scale?

Watson¹

2018

JMSE

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“…SSA can readily decompose an original time series into components of slowly varying trend, oscillatory components with variable amplitude and a structureless noise [Golyandina and Zhigljavsky, 2013]. The choice of SSA is based on the most extensive appraisal yet of time series analysis techniques for their utility to isolate the trend with improved temporal accuracy from conventional, long, individual ocean water level data sets [Watson, 2016a[Watson, , 2016b. Watson [2016b] tested a broad range of analytical techniques including linear and polynomial regression, robust locally weighted regression smoothing, smoothing splines, moving averages, structural models, digital filters, singular spectrum analysis (SSA), empirical mode decomposition, wavelets, and their respective derivatives.…”

Section: 1002/2016gl069653mentioning

confidence: 99%

“…The starting point is improved estimates of the temporal kinematic properties of the GMSL signal using techniques such as those espoused in this paper. From here, the search for acceleration is perhaps more practically inferred by considering whether or not peaks in the instantaneous velocity and acceleration time series are increasing, becoming more sustained or statistically abnormal (or different) over time in the context of the historical record [Watson, 2016a].…”

Section: 1002/2016gl069653mentioning

confidence: 99%

A new perspective on global mean sea level (GMSL) acceleration

Watson

2016

Geophysical Research Letters

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The vast body of contemporary climate change science is largely underpinned by the premise of a measured acceleration from anthropogenic forcings evident in key climate change proxies—greenhouse gas emissions, temperature, and mean sea level. By virtue, over recent years, the issue of whether or not there is a measurable acceleration in global mean sea level has resulted in fierce, widespread professional, social, and political debate. Attempts to measure acceleration in global mean sea level (GMSL) have often used comparatively crude analysis techniques providing little temporal instruction on these key questions. This work proposes improved techniques to measure real‐time velocity and acceleration based on five GMSL reconstructions spanning the time frame from 1807 to 2014 with substantially improved temporal resolution. While this analysis highlights key differences between the respective reconstructions, there is now more robust, convincing evidence of recent acceleration in the trend of GMSL.

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Acceleration in U.S. Mean Sea Level? A New Insight using Improved Tools

Watson

2016

Journal of Coastal Research

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How to improve estimates of real-time acceleration in the mean sea level signal

Cited by 5 publications

References 31 publications

How Well Do AR5 Sea Surface-Height Model Projections Match Observational Rates of Sea-Level Rise at the Regional Scale?

How Well Do AR5 Sea Surface-Height Model Projections Match Observational Rates of Sea-Level Rise at the Regional Scale?

A new perspective on global mean sea level (GMSL) acceleration

Acceleration in U.S. Mean Sea Level? A New Insight using Improved Tools

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