Time and tide: analysis of sea level time series
| LEADER | caa a22 4500 | ||
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| 001 | 605472173 | ||
| 003 | CHVBK | ||
| 005 | 20210128100336.0 | ||
| 007 | cr unu---uuuuu | ||
| 008 | 210128e20150701xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00382-014-2224-3 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00382-014-2224-3 | ||
| 245 | 0 | 0 | |a Time and tide: analysis of sea level time series |h [Elektronische Daten] |c [Grant Foster, Patrick Brown] |
| 520 | 3 | |a A number of recent papers have examined sea level data, both local tide gauge records and regional/global averages, to estimate not only how fast sea level is rising but how the rate has changed over time, i.e. its pattern of acceleration and deceleration. In addition, a number of claims of cyclic/quasi-periodic variations have been proposed. However, many of these papers contain technical problems which call their results into question. In particular, the issue of autocorrelation is often ignored, and even when it is addressed its impact has sometimes been misinterpreted. Autocorrelation does more than just affect the standard errors of regression analysis, it can also make the spectrum of a noise process distinctly "red” and therefore be highly suggestive of low-frequency periodic or pseudo-periodic behavior when none is present. If any analysis is applied which acts as a band-pass filter, it can further exaggerate the illusion of oscillatory behavior. These issues are highlighted in a small number of recent papers, in order to improve the quality of future work on this subject. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2014 | ||
| 690 | 7 | |a Time series |2 nationallicence | |
| 690 | 7 | |a Sea level |2 nationallicence | |
| 690 | 7 | |a Climate oscillations |2 nationallicence | |
| 700 | 1 | |a Foster |D Grant |u Tempo Analytics, Dover Foxcroft, ME, USA |4 aut | |
| 700 | 1 | |a Brown |D Patrick |u Duke University, Durham, NC, USA |4 aut | |
| 773 | 0 | |t Climate Dynamics |d Springer Berlin Heidelberg |g 45/1-2(2015-07-01), 291-308 |x 0930-7575 |q 45:1-2<291 |1 2015 |2 45 |o 382 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00382-014-2224-3 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00382-014-2224-3 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Foster |D Grant |u Tempo Analytics, Dover Foxcroft, ME, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Brown |D Patrick |u Duke University, Durham, NC, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Climate Dynamics |d Springer Berlin Heidelberg |g 45/1-2(2015-07-01), 291-308 |x 0930-7575 |q 45:1-2<291 |1 2015 |2 45 |o 382 | ||