Climate change in coastal waters: Time series properties affecting trend estimation

Simple item page
dc.contributor.authorSchlegel, Robert W.
dc.contributor.authorSmit, Albertus J.
dc.date.accessioned2023-02-07T09:18:29Z
dc.date.available2023-02-07T09:18:29Z
dc.date.issued2016
dc.description.abstractIn South Africa, 129 in situ temperature time series of up to 43 years are used for investigations of the thermal characteristics of coastal seawater. They are collected with handheld thermometers or underwater temperature recorders (UTRs) and are recorded at precisions from 0.58 to 0.0018C. Using the natural range of seasonal signals and variability for 84 of these time series, their length, decadal trend, and data precision were systematically varied before fitting generalized least squares (GLS) models to study the effect these variables have on trend detection. The variables that contributed most to accurate trend detection, in decreasing order, were time series length, decadal trend, variance, percentage of missing data (% NA), and measurement precision. Time series greater than 30 years in length are preferred and although larger decadal trends are modeled more accurately, modeled significance (p value) is largely affected by the variance present. The risk of committing both type-1 and type-2 errors increases when $5% NA is present. There is no appreciable effect on model accuracy between measurement precision of 0.18–0.0018C. Measurement precisions of 0.58C require longer time series to give equally accurate model results. The implication is that the thermometer time series in this dataset, and others around the world, must be at least two years longer than their UTR counterparts to be useful for decadal-scale climate change studies. Furthermore, adding older lower-precision UTR data to newer higher-precision UTR data within the same time series will increase their usefulness for this purpose.en_US
dc.identifier.citationSchlegel, R. W., & Smit, A. J. (2016). Climate change in coastal waters: Time series properties affecting trend estimation. Journal of Climate, 29 (24) ,9113-9124. https://doi.org/10.1175/JCLI-D-16-0014.1en_US
dc.identifier.issn1520-0442
dc.identifier.urihttps://doi.org/10.1175/JCLI-D-16-0014.1
dc.identifier.urihttp://hdl.handle.net/10566/8371
dc.language.isoenen_US
dc.publisherAMSen_US
dc.subjectBiodiversityen_US
dc.subjectBiologyen_US
dc.subjectConservationen_US
dc.subjectSouth Africaen_US
dc.subjectClimate changeen_US
dc.titleClimate change in coastal waters: Time series properties affecting trend estimationen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
schlegel_climate change in coastal waters_2016.pdf
Size:
11.96 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Research Articles (Biodiversity and Conservation Biology)