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Open AccessArticle

Cloud Computing for Climate Modelling: Evaluation, Challenges and Benefits

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ESEI, Universidade de Vigo, Campus As Lagoas, 32004 Ourense, Spain
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EPhysLab & CIM-UVigo, Campus As Lagoas, 32004 Ourense, Spain
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Oxford e-Research Centre, University of Oxford, Oxford OX1 3QG, UK
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School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK
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Wargaming, Sydney, NSW 2007, Australia
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CITIUS, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain
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Author to whom correspondence should be addressed.
Computers 2020, 9(2), 52; https://doi.org/10.3390/computers9020052
Received: 1 June 2020 / Revised: 16 June 2020 / Accepted: 17 June 2020 / Published: 22 June 2020
Cloud computing is a mature technology that has already shown benefits for a wide range of academic research domains that, in turn, utilize a wide range of application design models. In this paper, we discuss the use of cloud computing as a tool to improve the range of resources available for climate science, presenting the evaluation of two different climate models. Each was customized in a different way to run in public cloud computing environments (hereafter cloud computing) provided by three different public vendors: Amazon, Google and Microsoft. The adaptations and procedures necessary to run the models in these environments are described. The computational performance and cost of each model within this new type of environment are discussed, and an assessment is given in qualitative terms. Finally, we discuss how cloud computing can be used for geoscientific modelling, including issues related to the allocation of resources by funding bodies. We also discuss problems related to computing security, reliability and scientific reproducibility. View Full-Text
Keywords: climate model; cloud computing; supercomputer climate model; cloud computing; supercomputer
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Montes , D.; Añel , J.A.; Wallom , D.C.H.; Uhe , P.; Caderno, P.V.; Pena, T.F. Cloud Computing for Climate Modelling: Evaluation, Challenges and Benefits. Computers 2020, 9, 52.

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