Building confidence and credibility amid growing model and computing complexity (Invited)

Wednesday, December 13, 2017 - 10:29
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As global Earth system models are developed to answer an ever-wider range of science questions, software products that provide robust verification, validation, and evaluation must evolve in tandem. Measuring the degree to which these new models capture past behavior, predict the future, and provide the certainty of predictions is becoming ever more challenging for reasons that are generally well known, yet are still challenging to address. Two specific and divergent needs for analysis of the Accelerated Climate Model for Energy (ACME) model - but with a similar software philosophy - are presented to show how a model developer-based focus can address analysis needs during expansive model changes to provide greater fidelity and execute on multi-petascale computing facilities. A-PRIME is a python script-based quick-look overview of a fully-coupled global model configuration to determine quickly if it captures specific behavior before significant computer time and expense is invested. EVE is an ensemble-based software framework that focuses on verification of performance-based ACME model development, such as compiler or machine settings, to determine the equivalence of relevant climate statistics. The challenges and solutions for analysis of multi-petabyte output data are highlighted from the aspect of the scientist using the software, with the aim of fostering discussion and further input from the community about improving developer confidence and community credibility.

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