Abstract:
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Modern climate models pose an ever-increasing storage burden to computational facilities, and the upcoming generation of global simulations from the next Intergovernmental Panel on Climate Change will require a substantial share of the budget of research centers worldwide to be allocated just for this task. A suitably validated statistical model can be formulated to draw realizations whose spatio-temporal structure is similar to that of the original computer simulations, and the estimated parameters are effectively all the information that needs to be stored. In this work, we propose a new statistical model defined via a stochastic partial differential equation (SPDE) on the sphere and in evolving time. The model is able to capture nonstationarities across latitudes, longitudes and land/ocean domains for more than 300 million data points, while also overcoming the fundamental limitations of current global statistical models.
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