A scalable framework for the global offline community land model ensemble simulation

Dali Wang, Jens Domke, Jiafu Mao, Xiaoying Shi, Daniel M. Ricciuto

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Current earth system models have a large range of uncertainty, owing to differences in the simulation of feedbacks and insufficient information to constrain model parameters. Parameter disturbance experiment provides a straightforward method to quantify the variation (uncertainty) outputs caused by model inputs. Owing to the software complexity and computational intensity of earth system models, a large-scale simulation framework is needed to support ensemble simulation required by parameter disturbance experiment. This paper presents a parallel framework for the community land model ensemble simulation. After a software structure review of the community land model simulation, a single factor parameter disturbance experiment of a reference computational experiment design is used to demonstrate the software design principles, computational characteristics of individual application, parallel ensemble simulation implementation, as well as the weak scalability of this simulation framework on a high-end computer. Finally, the paper discusses some preliminary diagnostic analysis results of the single factor parameter disturbance experiments. The framework design considerations and implementation details described in this paper can be beneficial to many other research programmes involving large scale, legacy modelling system.

Original languageEnglish
Pages (from-to)73-85
Number of pages13
JournalInternational Journal of Computational Science and Engineering
Volume12
Issue number1
DOIs
StatePublished - 2016

Keywords

  • computational sciences
  • earth system modeling
  • high-end computing
  • performance profiling
  • scalability.

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