Analysis of Segmented Sea level Time Series. Boretti, A.
doi  abstract   bibtex   
Records of measurements of sea levels from tide gauges are often “segmented”, i.e., obtained by composing segments originating from the same or different instruments, in the same or different locations, or suffering from other biases that prevent the coupling. A technique is proposed, based on data mining, the application of break-point alignment techniques, and similarity with other segmented and non-segmented records for the same water basin, to quality flag the segmented records. This prevents the inference of incorrect trends for the rate of rise and the acceleration of the sea levels for these segmented records. The technique is applied to the four long-term trend tide gauges of the Indian Ocean, Aden, Karachi, Mumbai, and Fremantle, with three of them segmented.
@article{boretti_analysis_2020,
	title = {Analysis of Segmented Sea level Time Series},
	volume = {10},
	issn = {2076-3417},
	doi = {10.3390/app10020625},
	abstract = {Records of measurements of sea levels from tide gauges are often \“segmented\”, i.e., obtained by composing segments originating from the same or different instruments, in the same or different locations, or suffering from other biases that prevent the coupling. A technique is proposed, based on data mining, the application of break-point alignment techniques, and similarity with other segmented and non-segmented records for the same water basin, to quality flag the segmented records. This prevents the inference of incorrect trends for the rate of rise and the acceleration of the sea levels for these segmented records. The technique is applied to the four long-term trend tide gauges of the Indian Ocean, Aden, Karachi, Mumbai, and Fremantle, with three of them segmented.},
	number = {2},
	journaltitle = {Applied Sciences},
	author = {Boretti, Alberto},
	date = {2020},
	keywords = {Indian Ocean, break-point alignment, data mining, sea levels, similarity, statistic}
}
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