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Title:Influence of very large spatial heterogeneity on estimates of sea-level trends
Authors:Shapoval, Alexander (Author)
Le Mouël, Jean-Louis (Author)
Courtillot, Vincent (Author)
Shnirman, M. (Author)
Files:This document has no files. This document may have a phisical copy in the library of the organization, check the status via COBISS. Link is opened in a new window
Language:English
Work type:Unknown ()
Tipology:1.01 - Original Scientific Article
Organization:UNG - University of Nova Gorica
Abstract:We propose a new method to estimate sub-decadal to centennial time scales of sea-level change. Since the coastal data exhibit large spatial heterogeneity and temporal variability, the global sea-level rate is estimated as an appropriate average of the rates observed at available locations and computed with sliding windows. We claim that under such heterogeneity the median serves as a better representative of an adequate average than the mean. With this approach, the sea-level rate in 60 to 70 yr windows over the past century is found to be smaller than 1.7-1.9 mm/yr. These upper estimates are in line with those obtained with a scarce list of available long quasi-gapless series
Keywords:sea-level rise, median, sliding window, statistically significant trend
Year of publishing:2020
Number of pages:str. 1-9
Numbering:Vol. 386, 386
COBISS_ID:55313923 Link is opened in a new window
UDC:519.2
ISSN on article:0096-3003
URN:URN:SI:UNG:REP:8FWHSWGV
DOI:10.1016/j.amc.2020.125485 Link is opened in a new window
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Title:Applied mathematics and computation
Shortened title:Appl. math. comput.
Publisher:Elsevier
ISSN:0096-3003
COBISS.SI-ID:24983808 New window

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