about.Rmd
As mentioned on this package’s README page, eReefs is a collaborative information system created by the Great Barrier Reef Foundation, CSIRO, the Australian Institute of Marine Science, Bureau of Meteorology, and Queensland Government. As such, each collaborator has been working on different ways to visualise and explore what is currently happening on the reef, and what will likely happen in the future.
These tools and information are hosted on multiple websites. For example, while the main website combines info from all the parts:
CSIRO has a visualisation portal and an information site;
The National Computational Infrastructure (NCI)—Australia’s leading high-performance data, storage and computing organisation—hosts two main data services: the raw CSIRO model data with the highest time resolution (hourly for hydrology model, daily for biogeochemistry) and has curvilinear data;
The Bureau of Meteorology provides the ReefTemp NextGen—a set of high resolution mapping products that provide information on coral bleaching risk for the Great Barrier Reef region;
The Australian Institute of Marine Science (AIMS) also provides a Visualisation Portal, and maintains this R package. In addition, the AIMS eReefs data service contains the aggregated data services (daily, monthly, annual for hydrology model, monthly and annual for biogeochemistry) on a regular grid. Importantly, our R package focuses on accessing the data from NCI, not the AIMS eReefs data service.
If you want to extract time-series of the most commonly needed physical and chemical variables from the main versions of the eReefs model outputs at a fixed set of geolocations at a fixed depth from mean sea level, the AIMS web-based eReefs data extraction tool is usually faster and easier to use. If you want animations of the most commonly-needed variables at the surface, and do not need them to be customised, the AIMS eReefs visualisation portal offers pre-generated animations at several scales in an easy-to-navigate format.
Snippets of code for interactive with the eReefs data, including in python.
The GBRF website, with videos and descriptions by comms professionals.