A Stochastic Integration Toolkit fo rComprehensive Global Weather and Climate Models
Stochastic parameterization of large scale models is becoming an important tool for evaluating climate predictability and for enabling accurate representation of effects of micro-scale and short time physics on long time climate statistics. The models currently used to evaluate climate risk do not incorporate these stochastic effects, but represent multi-year development and collaboration between tens to hundreds of scientists spanning a number of disciplines in the atmospheric, physical and numerical sciences. Because of the significant time and resources that have been devoted to the development and validation of these models, there is a critical need to develop approaches to stochastic parameterization that are minimally invasive to the existing model structure. Argos Intelligence is addressing this issue by developing the Stochastic Parameterization Toolkit (SPT) to bridge the technology gap between the established stochastic integration techniques and operational numerical prediction models. SPT will provide a platform for introducing stochastic terms into existing code base using a simple, high-level, user-friendly language.
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