Open Access
June 2020 Compression of climate simulations with a nonstationary global SpatioTemporal SPDE model
Geir-Arne Fuglstad, Stefano Castruccio
Ann. Appl. Stat. 14(2): 542-559 (June 2020). DOI: 10.1214/20-AOAS1340


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 statistical model can be used as a means to mitigate the storage burden by providing a stochastic approximation of the climate simulations. Indeed, if a suitably validated statistical model can be formulated to draw realizations whose spatiotemporal structure is similar to that of the original computer simulations, then 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 available for compression. Once the model is trained, surrogate runs can be instantaneously generated on a laptop by storing just 20 Megabytes of parameters as opposed to more than six Gigabytes of the original ensemble.


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Geir-Arne Fuglstad. Stefano Castruccio. "Compression of climate simulations with a nonstationary global SpatioTemporal SPDE model." Ann. Appl. Stat. 14 (2) 542 - 559, June 2020.


Received: 1 October 2019; Revised: 1 February 2020; Published: June 2020
First available in Project Euclid: 29 June 2020

zbMATH: 07239873
MathSciNet: MR4117819
Digital Object Identifier: 10.1214/20-AOAS1340

Keywords: climate model , global model , nonstationary , space-time model , Stochastic partial differential equation

Rights: Copyright © 2020 Institute of Mathematical Statistics

Vol.14 • No. 2 • June 2020
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