PPT-Quantifying uncertainty and sensitivity in sea ice models
Author : cheeserv | Published Date : 2020-07-02
Objective The Los Alamos Sea Ice model has a number of input parameters for which accurate values are not always well established We conduct a variancebased sensitivity
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Quantifying uncertainty and sensitivity in sea ice models: Transcript
Objective The Los Alamos Sea Ice model has a number of input parameters for which accurate values are not always well established We conduct a variancebased sensitivity analysis of hemispheric sea ice properties to 39 input parameters The method accounts for nonlinear and nonadditive effects in the model. Oneway sensitivity analysis allows a reviewer to assess the im pact t hat c hang es in a cer ain par amet er will ha ve on the model57557s conclusions Sensitivity analysis can help the reviewer to determine which par amet er ar he driv er of a model In collaboration with:. Elizabeth Whitaker, Erica Briscoe, Ethan . Trewhitt. , . Georgia Tech. Kevin Murphy, Frank Ritter, John . Horgan. , Penn State. Caroline Kennedy-Pipe, . Univ. of Hull. Presented to:. Jake Blanchard. Fall 2010. Uncertainty Analysis for Engineers. 1. Instructor. Jake Blanchard. Engineering Physics. 143 Engineering Research Building. blanchard@engr.wisc.edu. Uncertainty Analysis for Engineers. Jake Blanchard. Fall . 2010. Introduction. Sensitivity Analysis = the study of how uncertainty in the output of a model can be apportioned to different input parameters. Local sensitivity = focus on sensitivity at a particular set of input parameters, usually using gradients or partial derivatives. John L. Campbell. 1. , Ruth D. Yanai. 2. , Mark B. . Green. 1,3. , Carrie . Rose . Levine. 2. , Mary Beth Adams. 1. , Douglas A. Burns. 4. ,. . Donald C. Buso. 5. , . Mark E. Harmon. 6. , Trevor Keenan. for S2D forecasting. EUPORIAS wp31. Nov 2012, Ronald Hutjes. Background. S2D impact prediction. Uncertainty explosion / Skill implosion ??. SST. Weather. (Downscaling). Soil moisture. Plant productivity. An Evaluation of Development Viability. Peter Byrne. Pat McAllister. Peter Wyatt. www.henley.reading.ac.uk/rep/fulltxt/0810.pdf. Structure. Main Research questions. Background and context. Current practice. Inclined Manometer. http://. www.dwyer-inst.com. U-tube Manometer. Sensitivity. Inclined Manometer. http://. www.dwyer-inst.com. U-tube Manometer. Pitot. Static Probe. Measures fluid velocity . v. Based on Bernoulli’s law. Stanford University, USA. A strategy for managing uncertainty. Importance of uncertainty and risk. New well planned. P1. P2. P3. P4. West-Coast Africa (WCA) slope-valley system. Data courtesy of Chevron. US National Combustion Meeting‘17. April 25, 2017. University of Maryland. Pavan. B. . Govindaraju. Matthias . Ihme. Special thanks to . Tim Edwards, AFRL. CRECK Modeling Group in . Politecnico. Di Milano. This project proposes to study sensitivity analysis for guiding the evaluation of uncertainty of data in the visual analytics process. We aim to achieve:. Semi-automatic Extraction of Sensitivity Information. Fall . 2010. Introduction. Sensitivity Analysis = the study of how uncertainty in the output of a model can be apportioned to different input parameters. Local sensitivity = focus on sensitivity at a particular set of input parameters, usually using gradients or partial derivatives. Sea Ice . in CMIP5 Climate Model Simulations. . Xiangdong . Zhang, . and . Chuhan. Lu. International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, AK . 99775. Email: . xdz@iarc.uaf.edu. 1. ERiMA. : . Envisioning Risk Models for Assessment of AI-based applications.. 2. Dr Huma Samin. 1. Post Doctoral Research Associate Computer Science. Durham University, UK. huma.samin@durham.ac.uk.
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