Browsing by Author "Schlegel, Robert W."

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    Climate change in coastal waters: Time series properties affecting trend estimation
    (AMS, 2016) Schlegel, Robert W.; Smit, Albertus J.
    In 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.
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    A novel approach to quantify metrics of upwelling intensity, frequency, and duration
    (Public Library of Science, 2021) Abrahams, Amieroh; Schlegel, Robert W.; Smit, Albertus J.
    The importance of coastal upwelling systems is widely recognized. However, several aspects of the current and future behaviors of these systems remain uncertain. Fluctuations in temperature because of anthropogenic climate change are hypothesized to affect upwelling-favorable winds and coastal upwelling is expected to intensify across all Eastern Boundary Upwelling Systems. To better understand how upwelling may change in the future, it is necessary to develop a more rigorous method of quantifying this phenomenon. In this paper, we use SST data and wind data in a novel method of detecting upwelling signals and quantifying metrics of upwelling intensity, duration, and frequency at four sites within the Benguela Upwelling System. We found that indicators of upwelling are uniformly detected across five SST products for each of the four sites and that the duration of those signals is longer in SST products with higher spatial resolutions. Moreover, the high-resolution SST products are significantly more likely to display upwelling signals at 25 km away from the coast when signals were also detected at the coast.
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    Predominant atmospheric and oceanic patterns during coastal marine heatwaves
    (Frontiers Media, 2017) Schlegel, Robert W.; Oliver, Eric C. J.; Perkins-Kirkpatrick, Sarah; Kruger, Andries
    As the mean temperatures of the worlds oceans increase, it is predicted that marine heatwaves (MHWs) will occur more frequently and with increased severity. However, it has been shown that variables other than increases in sea water temperature have been responsible for MHWs. To better understand these mechanisms driving MHWs we have utilized atmospheric (ERA-Interim) and oceanic (OISST, AVISO) data to examine the patterns around southern Africa during coastal (<400 m from the low water mark; measured in situ) MHWs. Nonmetric multidimensional scaling (NMDS) was first used to determine that the atmospheric and oceanic states during MHW are different from daily climatological states. Self-organizing maps (SOMs) were then used to cluster the MHW states into one of nine nodes to determine the predominant atmospheric and oceanic patterns present during these events. It was found that warmwater forced onto the coast via anomalous ocean circulation was the predominant oceanic pattern during MHWs. Warm atmospheric temperatures over the subcontinent during onshore or alongshore winds were the most prominent atmospheric patterns. Roughly one third of the MHWs were clustered into a node with no clear patterns, which implied that they were not forced by a recurring atmospheric or oceanic state that could be described by the SOManalysis. Because warm atmospheric and/or oceanic temperature anomalies were not the only pattern associated withMHWs, the current trend of a warming earth does not necessarily mean that MHWs will increase apace; however, aseasonal variability in wind and current patterns was shown to be central to the formation of coastal MHWs, meaning that where climate systems shift from historic records, increases in MHWs will likely occur.