Ocean

A global overview of marine heatwaves in a changing climate

This review synthesizes recent advances in marine heatwave research, covering their three-dimensional structure, physical drivers, links with other extremes, future change, and present-day predictability. It highlights the need for stronger mechanistic understanding across the full ocean depth, improved observing systems, and models capable of representing the processes that control marine heatwaves and their impacts in a warming climate.

A novel approach to quantify metrics of upwelling intensity, frequency, and duration

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. Our findings promote the viability of using SST and wind time series data to detect upwelling signals within coastal upwelling systems. We highlight the importance of high-resolution data products to improve the reliability of such estimates. This study represents an important step towards the development of an objective method for describing the behavior of coastal upwelling systems.

Variation and Change of Upwelling Dynamics Detected in the World’s Eastern Boundary Upwelling Systems

Global increases in temperature are altering land-sea temperature gradients. Bakun (1990) hypothesized that changes within these gradients will directly affect atmospheric pressure cells associated with the development of winds and will consequently impact upwelling patterns within ecologically important Eastern Boundary Upwelling Systems (EBUS). In this study we used daily time series of NOAA Optimally Interpolated sea surface temperature (SST) and ERA 5 reanalysis wind products to calculate a series novel of metrics related to upwelling dynamics. We then use these to objectively describe upwelling signals in terms of their frequency, intensity and duration throughout the four EBUS during summer months over the last 37 years (1982–2019). We found that a decrease (increase) in SST is associated with an increase (decrease) in the number of upwelling “events,” a decrease (increase) in the intensity of upwelling, and an increase (decrease) in the cumulative intensity of upwelling, with differences between EBUS and regions within EBUS. The Humboldt Current is the only EBUS that shows a consistent response from north to south with a general intensification of upwelling. However, we could not provide clear evidence for associated changes in the wind dynamics hypothesized to drive the upwelling dynamics.

Predominant Atmospheric and Oceanic Patterns during Coastal Marine Heatwaves

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 warm water 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 SOM analysis. Because warm atmospheric and/or oceanic temperature anomalies were not the only pattern associated with MHWs, 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.

Mapping with ggplot2

Objective

There are many different things that require scientists to use programming languages (like R). Far too many to count here. There is however one common use amongst almost all environmental scientists: mapping. Almost every report, research project or paper will have need to refer to a study area. This is almost always “Figure 1”. To this end, whenever I teach R, or run workshops on it, one of the questions I am always prepared for is how to create a map of a particular area. Being a happy convert to the tidyverse I only teach the graphics of ggplot2. I have found that people often prefer to use the ggmap extension to create ggplot quality figures with Google map backgrounds, but I personally think that a more traditional monotone background for maps looks more professional. What I’ve decided to showcase this week is the data and code required to create a publication quality map. Indeed, the following code will create the aforementioned obligatory “Figure 1” in a paper I am currently preparing for submission.