DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Moving beyond the total sea ice extent in gauging model biases

Journal Article · · Journal of Climate
 [1];  [2];  [2];  [2];  [3]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Nansen Environmental and Remote Sensing Center and Bjerknes Centre for Climate Research, Bergen (Norway)
  2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  3. Columbia Univ., New York, NY (United States)

Here, reproducing characteristics of observed sea ice extent remains an important climate modeling challenge. This study describes several approaches to improve how model biases in total sea ice distribution are quantified, and applies them to historically forced simulations contributed to phase 5 of the Coupled Model Intercomparison Project (CMIP5). The quantity of hemispheric total sea ice area, or some measure of its equatorward extent, is often used to evaluate model performance. A new approach is introduced that investigates additional details about the structure of model errors, with an aim to reduce the potential impact of compensating errors when gauging differences between simulated and observed sea ice. Using multiple observational datasets, several new methods are applied to evaluate the climatological spatial distribution and the annual cycle of sea ice cover in 41 CMIP5 models. It is shown that in some models, error compensation can be substantial, for example resulting from too much sea ice in one region and too little in another. Error compensation tends to be larger in models that agree more closely with the observed total sea ice area, which may result from model tuning. The results herein suggest that consideration of only the total hemispheric sea ice area or extent can be misleading when quantitatively comparing how well models agree with observations. Further work is needed to fully develop robust methods to holistically evaluate the ability of models to capture the finescale structure of sea ice characteristics; however, the “sector scale” metric used here aids in reducing the impact of compensating errors in hemispheric integrals.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC52-07NA27344
OSTI ID:
1342069
Report Number(s):
LLNL-JRNL-680923
Journal Information:
Journal of Climate, Vol. 29, Issue 24; ISSN 0894-8755
Publisher:
American Meteorological SocietyCopyright Statement
Country of Publication:
United States
Language:
English

References (42)

Intercomparison of passive microwave sea ice concentration retrievals over the high-concentration Arctic sea ice journal January 2007
The Flexible Global Ocean-Atmosphere-Land system model, Spectral Version 2: FGOALS-s2 journal April 2013
The Arctic Sea ice in the CMIP3 climate model ensemble ??? variability and anthropogenic change posted_content December 2012
The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation journal January 2012
Antarctic sea-ice thickness and volume estimates from ice charts between 1995 and 1998 journal January 2015
The ACCESS coupled model: description, control climate and evaluation journal March 2013
ACCESS-OM: the ocean and sea-ice core of the ACCESS coupled model journal March 2013
Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, Version 1 null January 1996
Passive microwave algorithms for sea ice concentration: A comparison of two techniques journal June 1997
Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5 journal February 2013
GFDL’s ESM2 Global Coupled Climate–Carbon Earth System Models. Part I: Physical Formulation and Baseline Simulation Characteristics journal October 2012
Sea Ice Index, Version 2 dataset January 2016
The Community Climate System Model Version 4 journal October 2011
The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments journal February 2000
The GFDL CM3 Coupled Climate Model: Characteristics of the Ocean and Sea Ice Simulations journal July 2011
EC-Earth V2.2: description and validation of a new seamless earth system prediction model journal December 2011
The Norwegian Earth System Model, NorESM1-M – Part 2: Climate response and scenario projections journal January 2012
Australia's CMIP5 submission using the CSIRO-Mk3.6 model journal March 2013
Arctic sea-ice change: a grand challenge of climate science journal January 2010
Sea-Ice in Twentieth-Century Simulations by New MIROC Coupled Models: A Comparison between Models with High Resolution and with Ice Thickness Distribution journal January 2012
An enhancement of the NASA Team sea ice algorithm journal May 2000
The HadGEM2 family of Met Office Unified Model Climate configurations journal January 2011
Constraining projections of summer Arctic sea ice journal January 2012
Tuning the climate of a global model: TUNING THE CLIMATE OF A GLOBAL MODEL journal March 2012
Comparison of passive microwave ice concentration algorithm retrievals with AVHRR imagery in arctic peripheral seas journal June 2005
Sea-ice extent and its trend provide limited metrics of model performance journal January 2014
How well must climate models agree with observations? journal October 2015
Arctic sea-ice evolution as modeled by Max Planck Institute for Meteorology's Earth system model journal April 2013
Evaluation of the simulation of the annual cycle of Arctic and Antarctic sea ice coverages by 11 major global climate models journal January 2006
MIROC4h^|^mdash;A New High-Resolution Atmosphere-Ocean Coupled General Circulation Model journal January 2012
Separating signal and noise in atmospheric temperature changes: The importance of timescale: TEMPERATURE SIGNAL-TO-NOISE RATIOS journal November 2011
Configuration and assessment of the GISS ModelE2 contributions to the CMIP5 archive: GISS MODEL-E2 CMIP5 SIMULATIONS journal March 2014
Arctic sea ice area in CMIP3 and CMIP5 climate model ensembles – variability and change journal January 2015
Assessment of sea ice simulations in the CMIP5 models journal January 2015
Trends in Arctic sea ice extent from CMIP5, CMIP3 and observations: ARCTIC SEA ICE EXTENT FROM CMIP5 journal August 2012
Summarizing multiple aspects of model performance in a single diagram journal April 2001
The CNRM-CM5.1 global climate model: description and basic evaluation journal January 2012
Simulating present-day climate with the INMCM4.0 coupled model of the atmospheric and oceanic general circulations journal August 2010
A sea ice free summer Arctic within 30 years: An update from CMIP5 models: SUMMER ARCTIC SEA ICE journal September 2012
How Well does BCC_CSM1.1 Reproduce the 20th Century Climate Change over China? journal January 2013
Reproduction of the large-scale state of water and sea ice in the Arctic Ocean in 1948–2002: Part I. Numerical model journal June 2009
How does internal variability influence the ability of CMIP5 models to reproduce the recent trend in Southern Ocean sea ice extent? journal January 2013

Cited By (9)

Understanding the Seasonal Cycle of Antarctic Sea Ice Extent in the Context of Longer‐Term Variability journal July 2019
Tropical Teleconnections to Antarctic Sea Ice During Austral Spring 2016 in Coupled Pacemaker Experiments journal June 2019
Progressing emergent constraints on future climate change journal March 2019
Towards improved and more routine Earth system model evaluation in CMIP journal January 2016
Consistent biases in Antarctic sea ice concentration simulated by climate models journal January 2018
Satellite passive microwave sea-ice concentration data set intercomparison: closed ice and ship-based observations journal January 2019
Impact of sea ice floe size distribution on seasonal fragmentation and melt of Arctic sea ice journal January 2020
Satellite Passive Microwave Sea-Ice Concentration Data Set Intercomparison: Closed Ice and Ship-Based Observations journal June 2019
Consistent biases in Antarctic sea ice concentration simulated by climate models journal July 2017