> by spatio-temporal dimension > 4D
Use case: Atmospheric and ocean climate data often come as 4-D x/y/z/t datacubes. The cell values usually represent some physical parameter (called "variable") which, eg, has been simulated. Among such variables are temperature, x and y speed components, pressure, etc. One consequence is that such data do not have an immediate visual semantics (like color and intensity in images), but need to be mapped to some color space for presentation. Climate researchers want to obtain orthogonal 2-D slices from 3-D x/y/t and 4-D x/y/z/t climate simulation output.
The Service: The dataset represents a 4D hypercube of temperature values over Long, Lat, time, at different elevations. Choose subsets on Longitude and Latitude, a date of interest and the elevation levels you want to visualise, then click Run. The choices are used to send parametrized WCPS requests. Their answers are displayed on the globe.