The Virtual Globe application provides a platform for configuring and running high resolution environmental models nearly anywhere in the world. Various global datasets can be used as model inputs, such as the SRTM elevation model, global vegetation data from MODIS, land use classification based on GLOBCOVER, climatic data, soil information, population density, and near real time weather forecasts. The PCRaster-Python Framework is used as a modelling backend, and the platform is developed by the PCRaster team at the Department of Physical Geography at Utrecht University.
Choose one of the demo models, for example the PCR-SNOW model. The snow model only produces results in areas of the world where temperatures are low enough.
Use the find places button to find a location where you want to run the PCR-SNOW model, for example around the Mont Blanc area in the Swiss alps.
Zoom in a little more and click "run model." It may take a minute to complete, and afterwards you can view the output attributes and timesteps.
Every model produces different output maps, each output attribute can be opened by clicking on the 'display' button.
The model runs over the course of two years. Select a different timestep (each timestep represents a month) to explore the output attributes through time.
By clicking on a location in the map you can view a timeseries plot of the attribute value in that particular location over time.