Sensitivity Analysis and Parameter Tuning Scheme for Global Sea-Ice Modeling
Automatic differentiation (AD) is used to perform a multiple parameter sensitivity analysis for the Los Alamos sea-ice model CICE. Numerical experiments are run by six-hourly, 1997 forcing data with a two-hour time step, and the AD-based sensitivity scheme is validated by comparison with derivatives...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.379.5538 2023-05-15T13:36:48+02:00 Sensitivity Analysis and Parameter Tuning Scheme for Global Sea-Ice Modeling Jong G. Kim A Elizabeth C. Hunke B William H. Lipscomb B The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.379.5538 http://info.mcs.anl.gov/pub/tech_reports/reports/P1282.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.379.5538 http://info.mcs.anl.gov/pub/tech_reports/reports/P1282.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://info.mcs.anl.gov/pub/tech_reports/reports/P1282.pdf Key words sea-ice model automatic differentiation parameter sensitivity ice thickness thermodynamics dynamics Arctic Antarctic Weddell Sea text ftciteseerx 2016-09-18T00:16:35Z Automatic differentiation (AD) is used to perform a multiple parameter sensitivity analysis for the Los Alamos sea-ice model CICE. Numerical experiments are run by six-hourly, 1997 forcing data with a two-hour time step, and the AD-based sensitivity scheme is validated by comparison with derivatives calculated using the conventional finite-difference approach. Twenty-two thermodynamic and dynamic parameters are selected for simultaneous analysis. Of these, the most important for controlling the simulated average sea-ice thickness is ice density; albedos and emissivity predominate in summer, while ice thickness is most sensitive to the ice conductivity in winter. The ice-ocean drag parameter and maximum ice salinity significantly affect the simulation year-round. Gradient information computed by the AD-based sea-ice code is then used in an experiment designed to assess the efficacy of this technique for tuning the parameters against observational data. Preliminary results, obtained with a bound-constrained minimization method and with simulated observational data, show that satisfactory convergence is obtained. Text Antarc* Antarctic Arctic Sea ice Weddell Sea Unknown Antarctic Arctic Weddell Weddell Sea |
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English |
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Key words sea-ice model automatic differentiation parameter sensitivity ice thickness thermodynamics dynamics Arctic Antarctic Weddell Sea |
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Key words sea-ice model automatic differentiation parameter sensitivity ice thickness thermodynamics dynamics Arctic Antarctic Weddell Sea Jong G. Kim A Elizabeth C. Hunke B William H. Lipscomb B Sensitivity Analysis and Parameter Tuning Scheme for Global Sea-Ice Modeling |
topic_facet |
Key words sea-ice model automatic differentiation parameter sensitivity ice thickness thermodynamics dynamics Arctic Antarctic Weddell Sea |
description |
Automatic differentiation (AD) is used to perform a multiple parameter sensitivity analysis for the Los Alamos sea-ice model CICE. Numerical experiments are run by six-hourly, 1997 forcing data with a two-hour time step, and the AD-based sensitivity scheme is validated by comparison with derivatives calculated using the conventional finite-difference approach. Twenty-two thermodynamic and dynamic parameters are selected for simultaneous analysis. Of these, the most important for controlling the simulated average sea-ice thickness is ice density; albedos and emissivity predominate in summer, while ice thickness is most sensitive to the ice conductivity in winter. The ice-ocean drag parameter and maximum ice salinity significantly affect the simulation year-round. Gradient information computed by the AD-based sea-ice code is then used in an experiment designed to assess the efficacy of this technique for tuning the parameters against observational data. Preliminary results, obtained with a bound-constrained minimization method and with simulated observational data, show that satisfactory convergence is obtained. |
author2 |
The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Jong G. Kim A Elizabeth C. Hunke B William H. Lipscomb B |
author_facet |
Jong G. Kim A Elizabeth C. Hunke B William H. Lipscomb B |
author_sort |
Jong G. Kim A |
title |
Sensitivity Analysis and Parameter Tuning Scheme for Global Sea-Ice Modeling |
title_short |
Sensitivity Analysis and Parameter Tuning Scheme for Global Sea-Ice Modeling |
title_full |
Sensitivity Analysis and Parameter Tuning Scheme for Global Sea-Ice Modeling |
title_fullStr |
Sensitivity Analysis and Parameter Tuning Scheme for Global Sea-Ice Modeling |
title_full_unstemmed |
Sensitivity Analysis and Parameter Tuning Scheme for Global Sea-Ice Modeling |
title_sort |
sensitivity analysis and parameter tuning scheme for global sea-ice modeling |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.379.5538 http://info.mcs.anl.gov/pub/tech_reports/reports/P1282.pdf |
geographic |
Antarctic Arctic Weddell Weddell Sea |
geographic_facet |
Antarctic Arctic Weddell Weddell Sea |
genre |
Antarc* Antarctic Arctic Sea ice Weddell Sea |
genre_facet |
Antarc* Antarctic Arctic Sea ice Weddell Sea |
op_source |
http://info.mcs.anl.gov/pub/tech_reports/reports/P1282.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.379.5538 http://info.mcs.anl.gov/pub/tech_reports/reports/P1282.pdf |
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Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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1766084321514356736 |