Towards scalable ad-hoc climate anomalies search
Peter Baumann, Dimitar Mišev · 2012
Meteorological data contribute significantly to "Big Data"; however, not only is their volume ranging into Petabyte sizes for single objects a challenge, but also the number of dimensions -- such general 4-D spatio-temporal data cannot be handled through traditional GIS methods and tools. Actually, climate data tend to transcend these dimensions and add an extra time dimension for the simulation run time, ending up with 5-D data cubes.