Speaker Drew Purves
Affiliation Microsoft Research Cambridge
Host Harold Javid, Microsoft Research
Date recorded 8 October 2012
To manage the planet on which we all depend, we need to predict the future outcome of various options. How would biofuel subsidies affect crop prices affect deforestation? CO2 emissions affect climate change affect fire? At present, we cannot make such predictions with any confidence. But, as I’ll show in this talk, a computational approach to environmental science can change that. I’ll explain how we built the first fully data-constrained model of the terrestrial carbon cycle, using Big Data, cloud computing, and machine learning. And I’ll demo similar models for global food production, Amazon deforestation, and bird biodiversity. The prototype tools on which these models have been built—for example, FetchClimate, Filzbach, WorldWide Telescope—are freely available, and will hopefully allow other scientists to adopt a rigorous approach to modeling the complexities of the biosphere.
©2012 Microsoft Corporation. All rights reserved.
By the same speaker
Tutorial: Data-Constrained Environmental Modelling: FetchClimate, Filzbach, and Distribution Modeller I
Tutorial: Data-Constrained Environmental Modelling: FetchClimate, Filzbach, and Distribution Modeller II
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