skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

Abstract

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates thatmore » model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.« less

Authors:
 [1];  [1];  [1];  [1];  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1325643
Report Number(s):
LA-UR-15-29485
Journal ID: ISSN 2169-9275
Grant/Contract Number:  
AC52-06NA25396
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Geophysical Research. Oceans
Additional Journal Information:
Journal Volume: 121; Journal Issue: 4; Journal ID: ISSN 2169-9275
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; 54 ENVIRONMENTAL SCIENCES; Earth Sciences; sea ice model, uncertainty quantification, global sensitivity analysis, CICE

Citation Formats

Urrego-Blanco, Jorge Rolando, Urban, Nathan Mark, Hunke, Elizabeth Clare, Turner, Adrian Keith, and Jeffery, Nicole. Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model. United States: N. p., 2016. Web. doi:10.1002/2015JC011558.
Urrego-Blanco, Jorge Rolando, Urban, Nathan Mark, Hunke, Elizabeth Clare, Turner, Adrian Keith, & Jeffery, Nicole. Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model. United States. doi:10.1002/2015JC011558.
Urrego-Blanco, Jorge Rolando, Urban, Nathan Mark, Hunke, Elizabeth Clare, Turner, Adrian Keith, and Jeffery, Nicole. Fri . "Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model". United States. doi:10.1002/2015JC011558. https://www.osti.gov/servlets/purl/1325643.
@article{osti_1325643,
title = {Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model},
author = {Urrego-Blanco, Jorge Rolando and Urban, Nathan Mark and Hunke, Elizabeth Clare and Turner, Adrian Keith and Jeffery, Nicole},
abstractNote = {Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.},
doi = {10.1002/2015JC011558},
journal = {Journal of Geophysical Research. Oceans},
number = 4,
volume = 121,
place = {United States},
year = {2016},
month = {4}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 4 works
Citation information provided by
Web of Science

Save / Share:

Works referenced in this record:

Snow grain size retrieval SGSP from optical satellite data: Validation with ground measurements and detection of snow fall events
journal, January 2013


The Community Climate System Model Version 4
journal, October 2011

  • Gent, Peter R.; Danabasoglu, Gokhan; Donner, Leo J.
  • Journal of Climate, Vol. 24, Issue 19
  • DOI: 10.1175/2011JCLI4083.1

Global atmospheric forcing data for Arctic ice-ocean modeling
journal, January 2007

  • Hunke, Elizabeth C.; Holland, Marika M.
  • Journal of Geophysical Research, Vol. 112, Issue C4
  • DOI: 10.1029/2006JC003640

The global climatology of an interannually varying air–sea flux data set
journal, August 2008


An Elastic–Viscous–Plastic Model for Sea Ice Dynamics
journal, September 1997


Thin and thinner: Sea ice mass balance measurements during SHEBA
journal, January 2003


The energetics of the plastic deformation of pack ice by ridging
journal, November 1975


Ridging and strength in modeling the thickness distribution of Arctic sea ice
journal, January 1995

  • Flato, Gregory M.; Hibler, William D.
  • Journal of Geophysical Research, Vol. 100, Issue C9
  • DOI: 10.1029/95JC02091

Four stages of pressure ridging
journal, September 1998

  • Hopkins, Mark A.
  • Journal of Geophysical Research: Oceans, Vol. 103, Issue C10
  • DOI: 10.1029/98JC01257

A parameterization of the ice-ocean drag coefficient
journal, January 2011

  • Lu, Peng; Li, Zhijun; Cheng, Bin
  • Journal of Geophysical Research, Vol. 116, Issue C7
  • DOI: 10.1029/2010JC006878

Thickness sensitivities in the CICE sea ice model
journal, January 2010


Bayesian analysis of computer code outputs: A tutorial
journal, October 2006


Improved Sea Ice Shortwave Radiation Physics in CCSM4: The Impact of Melt Ponds and Aerosols on Arctic Sea Ice
journal, March 2012

  • Holland, Marika M.; Bailey, David A.; Briegleb, Bruce P.
  • Journal of Climate, Vol. 25, Issue 5
  • DOI: 10.1175/JCLI-D-11-00078.1

The Role of Sea Ice Thickness Distribution in the Arctic Sea Ice Potential Predictability: A Diagnostic Approach with a Coupled GCM
journal, April 2012


Level-ice melt ponds in the Los Alamos sea ice model, CICE
journal, November 2013


Surprising return of deep convection to the subpolar North Atlantic Ocean in winter 2007–2008
journal, November 2008

  • Våge, Kjetil; Pickart, Robert S.; Thierry, Virginie
  • Nature Geoscience, Vol. 2, Issue 1
  • DOI: 10.1038/ngeo382

A physically based parameterization of gravity drainage for sea-ice modeling
journal, September 2014

  • Rees Jones, David W.; Worster, M. Grae
  • Journal of Geophysical Research: Oceans, Vol. 119, Issue 9
  • DOI: 10.1002/2013JC009296

Winter Northern Hemisphere weather patterns remember summer Arctic sea-ice extent: SUMMER SEA ICE AFFECTS WINTER WEATHER
journal, April 2009

  • Francis, Jennifer A.; Chan, Weihan; Leathers, Daniel J.
  • Geophysical Research Letters, Vol. 36, Issue 7
  • DOI: 10.1029/2009GL037274

The thermal conductivity of seasonal snow
journal, January 1997


Compositional convection in the solidification of binary alloys
journal, October 1994


Generalized Additive Models
journal, August 1986


Satellite observations of Antarctic sea ice thickness and volume: ANTARCTIC SEA ICE THICKNESS
journal, August 2012

  • Kurtz, N. T.; Markus, T.
  • Journal of Geophysical Research: Oceans, Vol. 117, Issue C8
  • DOI: 10.1029/2012JC008141

Spectral albedo of seasonal snow during intensive melt period at Sodankylä, beyond the Arctic Circle
journal, January 2013

  • Meinander, O.; Kazadzis, S.; Arola, A.
  • Atmospheric Chemistry and Physics, Vol. 13, Issue 7
  • DOI: 10.5194/acp-13-3793-2013

Arctic sea ice decline and ice export in the CMIP5 historical simulations
journal, November 2013


Role of microbial and phytoplanktonic communities in the control of seawater viscosity off East Antarctica (30-80° E)
journal, May 2010

  • Seuront, Laurent; Leterme, Sophie C.; Seymour, Justin R.
  • Deep Sea Research Part II: Topical Studies in Oceanography, Vol. 57, Issue 9-10
  • DOI: 10.1016/j.dsr2.2008.09.018

Sensitivity analysis and parameter tuning scheme for global sea-ice modeling
journal, January 2006


Desalination processes of sea ice revisited
journal, January 2009

  • Notz, Dirk; Worster, M. Grae
  • Journal of Geophysical Research, Vol. 114, Issue C5
  • DOI: 10.1029/2008JC004885

How to avoid a perfunctory sensitivity analysis
journal, December 2010


A Decomposition of Feedback Contributions to Polar Warming Amplification
journal, September 2013


Two modes of sea-ice gravity drainage: A parameterization for large-scale modeling: GRAVITY DRAINAGE
journal, May 2013

  • Turner, Adrian K.; Hunke, Elizabeth C.; Bitz, Cecilia M.
  • Journal of Geophysical Research: Oceans, Vol. 118, Issue 5
  • DOI: 10.1002/jgrc.20171

Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates
journal, February 2001


Changes in Arctic sea ice result in increasing light transmittance and absorption
journal, December 2012

  • Nicolaus, M.; Katlein, C.; Maslanik, J.
  • Geophysical Research Letters, Vol. 39, Issue 24
  • DOI: 10.1029/2012GL053738

Scrambling Sobol' and Niederreiter–Xing Points
journal, December 1998


Evaluation of the air-sea bulk formula and sea-surface temperature variability from observations
journal, January 2006

  • Vickers, Dean; Mahrt, L.
  • Journal of Geophysical Research, Vol. 111, Issue C5
  • DOI: 10.1029/2005JC003323

Maintenance of the Sea-Ice Edge
journal, August 2005

  • Bitz, C. M.; Holland, M. M.; Hunke, E. C.
  • Journal of Climate, Vol. 18, Issue 15
  • DOI: 10.1175/JCLI3428.1

Exopolymer alteration of physical properties of sea ice and implications for ice habitability and biogeochemistry in a warmer Arctic
journal, February 2011

  • Krembs, Christopher; Eicken, Hajo; Deming, Jody W.
  • Proceedings of the National Academy of Sciences, Vol. 108, Issue 9
  • DOI: 10.1073/pnas.1100701108

Surface Albedo of the Antarctic Sea Ice Zone
journal, September 2005

  • Brandt, Richard E.; Warren, Stephen G.; Worby, Anthony P.
  • Journal of Climate, Vol. 18, Issue 17
  • DOI: 10.1175/JCLI3489.1

Physical properties of Arctic versus subarctic snow: Implications for high latitude passive microwave snow water equivalent retrievals: ARCTIC VERSUS SUBARCTIC SNOW
journal, June 2014

  • Derksen, C.; Lemmetyinen, J.; Toose, P.
  • Journal of Geophysical Research: Atmospheres, Vol. 119, Issue 12
  • DOI: 10.1002/2013JD021264

Importance measures in global sensitivity analysis of nonlinear models
journal, April 1996


A distribution-free test for the relationship between model input and output when using Latin hypercube sampling
journal, March 2003


Uncertainties in Arctic sea ice thickness and volume: new estimates and implications for trends
journal, January 2014


The Community Climate System Model Version 3 (CCSM3)
journal, June 2006

  • Collins, William D.; Bitz, Cecilia M.; Blackmon, Maurice L.
  • Journal of Climate, Vol. 19, Issue 11
  • DOI: 10.1175/JCLI3761.1

The central role of diminishing sea ice in recent Arctic temperature amplification
journal, April 2010


Thermal evolution of permeability and microstructure in sea ice: PERMEABILITY AND MICROSTRUCTURE IN SEA ICE
journal, August 2007

  • Golden, K. M.; Eicken, H.; Heaton, A. L.
  • Geophysical Research Letters, Vol. 34, Issue 16
  • DOI: 10.1029/2007GL030447

Recent development of the Met Office operational ocean forecasting system: an overview and assessment of the new Global FOAM forecasts
journal, January 2014

  • Blockley, E. W.; Martin, M. J.; McLaren, A. J.
  • Geoscientific Model Development, Vol. 7, Issue 6
  • DOI: 10.5194/gmd-7-2613-2014

Optical properties of melting first‐year A rctic sea ice
journal, November 2015

  • Light, Bonnie; Perovich, Donald K.; Webster, Melinda A.
  • Journal of Geophysical Research: Oceans, Vol. 120, Issue 11
  • DOI: 10.1002/2015JC011163

Bayesian calibration of computer models
journal, August 2001

  • Kennedy, Marc C.; O'Hagan, Anthony
  • Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 63, Issue 3
  • DOI: 10.1111/1467-9868.00294

Parameterizing Turbulent Exchange over Sea Ice in Winter
journal, February 2010

  • Andreas, Edgar L.; Persson, P. Ola G.; Grachev, Andrey A.
  • Journal of Hydrometeorology, Vol. 11, Issue 1
  • DOI: 10.1175/2009JHM1102.1

A Model for the Spectral Albedo of Snow. I: Pure Snow
journal, December 1980


Parametrizing turbulent exchange over summer sea ice and the marginal ice zone
journal, April 2010

  • Andreas, Edgar L.; Horst, Thomas W.; Grachev, Andrey A.
  • Quarterly Journal of the Royal Meteorological Society, Vol. 136, Issue 649
  • DOI: 10.1002/qj.618

Sensitivity analysis in presence of model uncertainty and correlated inputs
journal, October 2006

  • Jacques, Julien; Lavergne, Christian; Devictor, Nicolas
  • Reliability Engineering & System Safety, Vol. 91, Issue 10-11
  • DOI: 10.1016/j.ress.2005.11.047

Status and future of global and regional ocean prediction systems
journal, August 2015

  • Tonani, Marina; Balmaseda, Magdalena; Bertino, Laurent
  • Journal of Operational Oceanography, Vol. 8, Issue sup2
  • DOI: 10.1080/1755876X.2015.1049892

Probabilistic sensitivity analysis of complex models: a Bayesian approach
journal, August 2004

  • Oakley, Jeremy E.; O'Hagan, Anthony
  • Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 66, Issue 3
  • DOI: 10.1111/j.1467-9868.2004.05304.x

Impact of Variable Atmospheric and Oceanic Form Drag on Simulations of Arctic Sea Ice
journal, May 2014

  • Tsamados, Michel; Feltham, Daniel L.; Schroeder, David
  • Journal of Physical Oceanography, Vol. 44, Issue 5
  • DOI: 10.1175/JPO-D-13-0215.1

Ridging, strength, and stability in high-resolution sea ice models
journal, January 2007

  • Lipscomb, William H.; Hunke, Elizabeth C.; Maslowski, Wieslaw
  • Journal of Geophysical Research, Vol. 112, Issue C3
  • DOI: 10.1029/2005JC003355

The relation between sea ice thickness and freeboard in the Arctic
journal, January 2010


A high-resolution ocean and sea-ice modelling system for the Arctic and North Atlantic oceans
journal, January 2015

  • Dupont, F.; Higginson, S.; Bourdallé-Badie, R.
  • Geoscientific Model Development, Vol. 8, Issue 5
  • DOI: 10.5194/gmd-8-1577-2015

The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate
journal, January 2013

  • Bentsen, M.; Bethke, I.; Debernard, J. B.
  • Geoscientific Model Development, Vol. 6, Issue 3
  • DOI: 10.5194/gmd-6-687-2013

Effects of snow physical parameters on spectral albedo and bidirectional reflectance of snow surface
journal, April 2000

  • Aoki, Teruo; Aoki, Tadao; Fukabori, Masashi
  • Journal of Geophysical Research: Atmospheres, Vol. 105, Issue D8
  • DOI: 10.1029/1999JD901122

Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index
journal, February 2010

  • Saltelli, Andrea; Annoni, Paola; Azzini, Ivano
  • Computer Physics Communications, Vol. 181, Issue 2
  • DOI: 10.1016/j.cpc.2009.09.018

The thickness distribution of sea ice
journal, November 1975

  • Thorndike, A. S.; Rothrock, D. A.; Maykut, G. A.
  • Journal of Geophysical Research, Vol. 80, Issue 33
  • DOI: 10.1029/JC080i033p04501

A sea-ice sensitivity study with a global ocean-ice model
journal, July 2012


Modelling and smoothing parameter estimation with multiple quadratic penalties
journal, May 2000

  • Wood, S. N.
  • Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 62, Issue 2
  • DOI: 10.1111/1467-9868.00240

A sensitivity study of the sea ice simulation in the global coupled climate model, HadGEM3
journal, February 2014


The sea ice mass budget of the Arctic and its future change as simulated by coupled climate models
journal, November 2008

  • Holland, Marika M.; Serreze, Mark C.; Stroeve, Julienne
  • Climate Dynamics, Vol. 34, Issue 2-3
  • DOI: 10.1007/s00382-008-0493-4

Coordinated Ocean-ice Reference Experiments (COREs)
journal, January 2009


On the formulation of snow thermal conductivity in large-scale sea ice models: SNOW REPRESENTATION IN SEA ICE MODELS
journal, July 2013

  • Lecomte, O.; Fichefet, T.; Vancoppenolle, M.
  • Journal of Advances in Modeling Earth Systems, Vol. 5, Issue 3
  • DOI: 10.1002/jame.20039

Design and implementation of the infrastructure of HadGEM3: the next-generation Met Office climate modelling system
journal, January 2011

  • Hewitt, H. T.; Copsey, D.; Culverwell, I. D.
  • Geoscientific Model Development, Vol. 4, Issue 2
  • DOI: 10.5194/gmd-4-223-2011

    Works referencing / citing this record:

    The NUIST Earth System Model (NESM) version 3: description and preliminary evaluation
    journal, January 2018


    Quality control for community-based sea-ice model development
    journal, August 2018

    • Roberts, Andrew F.; Hunke, Elizabeth C.; Allard, Richard
    • Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 376, Issue 2129
    • DOI: 10.1098/rsta.2017.0344

    Quality control for community-based sea-ice model development
    journal, August 2018

    • Roberts, Andrew F.; Hunke, Elizabeth C.; Allard, Richard
    • Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 376, Issue 2129
    • DOI: 10.1098/rsta.2017.0344

    The NUIST Earth System Model (NESM) version 3: description and preliminary evaluation
    journal, January 2018