Demo /

By Spatial Dimensionality / 5D   

Use case: Simplify calendar handling in the E-OBS dataset of daily mean temperatures over Europe since 1951. A problem with the time axis is that aggregated time units, such as months and years, are highly non-regular. To this end, the single time axis has been unfolded into further time axes, each one representing one level of granularity of extra time dimensions to obtain one dimension per temporal granularity unit. In such a "ragged" setup, a cube has the dimensions year, month, day, followed by the spatial dimensions x and y. Cells going beyond the day limit in a month are set to null. This allows convenient access on all levels of detail by simply using the subsetting and aggregating functionality.

The Service: The below WCPS queries demonstrate data extraction and processing at various temporal intervals.