These vignettes collect R techniques gathered over the years. Each is a self-contained worked example; most use freely available oceanographic and Earth-system data.
Ocean and Earth-system data
| Title | Description |
|---|---|
| Global Earth and ocean data | This vignette intorduces the variety gridded data products available freely on the internet. |
| Dates from netCDF files: two approaches | This vignette demonstrates basic ideas behind dates in netCDF files. |
| Retrieving chlorophyll-a data from ERDDAP servers | This vignette demonstrates basic ideas behind ERDDAP. |
| Wget download from NASA Earthdata | Navigate to NASA’s EARTHDATA and follow the Find Data link: |
| Regridding gridded data | This vignette demonstrates basic ideas behind regridding. |
| Extracting gridded data within a buffer | Download the coastline data for the entire world: |
| Wind stress curl | This vignette demonstrates the basic calculation of wind stress curl in R. |
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Marine heatwaves and cold spells
| Title | Description |
|---|---|
| Downloading and preparing NOAA OISST data: ERDDAP | This vignette demonstrates how to download NOAA OISST data and prepare them for the detection of marine heatwaves. |
| Downloading and preparing NOAA OISST data: Python + CDO | This vignette demonstrates an alternative method for downloading NOAA OISST data (using a python script) and preparing and detecting marine heatwaves. |
| Detecting events in gridded data | This vignette demonstrates how to detect marine heatwaves (MHWs) in dataframes of gridded data in which each pixel is a separate time series. |
| Event horizon plots | Horizon plots provide a snooty, impactful approach for showing patterns in time series. Because they can be set up to highlight events that occur at certain thresholds, they… |
| heatwaveR issues |
Applying detect_event(..., protoEvent = FALSE) (the default) returns protoEvents as part of the climatology even if they were not requested. The protoEvents must only be… |
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Case studies
| Title | Description |
|---|---|
| Plotting the whale sightings and chlorophyll-a concentrations | This vignette demonstrates exploratory data analyses. |
| Spatial localisation, subsetting, and aggregation of the chlorophyll-a data | This vignette demonstrates an example workflow for extracting chlorophyll-a data at the point localities where whales were sighted. |
| Wavelet analysis of diatom time series | On this page I reproduce the analysis in the following paper: |
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High-performance computing
| Title | Description |
|---|---|
| Using Lengau | The Lengau High Performance Computing (HPC) system is a supercomputer located at the Centre for High Performance Computing (CHPC) in Cape Town, South Africa. “Lengau” is a… |
| PBS pro workload manager on Lengau | PBS Pro is a workload management system that is designed to manage and optimise the scheduling of computational tasks on supercomputers and clusters. In PBS Pro, tasks are… |
| PBSPro users and nodes |
To find active nodes associated with a user in PBSPro, you’d typically use the qstat command followed by some parsing to extract the node information. The method to extract…
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| Using tmux | Always work within tmux |
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