climate

 

Remote Climate Analysis and Visualization

The ViSUS application framework has been used in the climate modeling community to visualize climate change simulations comprising many species over a large number of time steps. This type of data provides the opportunity to both build high quality data analysis routines and challenge the performance of the data management infrastructure. The figure below (left) shows ViSUS rendering 10TB of data used to present findings regarding the Earth's temperature change based on historical and projected simulation data at the December 2009 climate summit meeting in Copenhagen (Denmark). This work showed the possibility of transferring, transforming, analyzing, and rendering a large dataset on geographically distributed computing resources. Below (center) we see the ViSUS framework providing a visualization of global precipitation that dynamically resamples datasets of different spatial dimensions and blends them according to a user-specified operation (average). Below (right) the ViSUS framework providing visualization of climate data showing global temperature and precipitation from sixteen different climate models of differing spatial resolution, dynamically resampled and blended according to a user-specified operation (standard deviation). The ability to dynamically combine heterogenous datasets can help bring novel insights into the dynamics of global carbon cycle, atmospheric chemistry, land and ocean ecological processes and their coupling with climate.


 climate-fig
Climate visualization with ViSUS.(left) The ViSUS framework providing a visualization for a temperature change ensemble simulation for the Earth's surface for the December 2009 climate summit meeting in Copenhagen. (center) Two datasets of different spatial resolution showing global surface precipitation. They are dynamically resampled and blended with ViSUS using an arbitrary user-specified operation (average). (right) Climate simulation showing global temperature and precipitation from sixteen different climate models of differing spatial resolution, dynamically resampled and blended with ViSUS using an arbitrary user-specified operation (standard deviation).