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Poster TitleHow can we make model tuning less laborious and more transparent?  Putting human expertise in the loop in visualization design and expert judgement.
AuthorsSusannah Burrows, Aritra Dasgupta (PNNL), Sarah Reehl (PNNL), Lisa Bramer (PNNL), Kyungsik ("Keith") Han (PNNL), Po-Lun Ma, Phil Rasch (pnl.gov), Yun Qian
GroupAtmosphere
Experiment
Poster CategoryFuture Direction
Submission Typeposter
Poster Link

Metrics_project_2017_ACME_spring_meeting.pptx



Abstract

Climate model calibration (“tuning”) is a complex and laborious task, requiring many thousands of hours of effort by experienced model developers for each new version of a component or coupled model.  Two key obstacles to efficient model fidelity analysis are: (1) comparisons of model fidelity across multiple simulations are time-consuming, and (2) there is limited consensus on the relative importance of different model variables to evaluating overall fidelity. We address these challenges through a unique, close collaboration among climate modellers, visual analytics researchers, and statisticians, as part of an LDRD project at Pacific Northwest National Laboratory. 

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