Evaluation of sea ice thickness reproduction in AOMIP models Mark Johnson and Tatiana Proshutinsky (Institute of Marine Science, University of Alaska, Fairbanks (IMS-UAF), USA) Andrey Proshutinsky (Wood Hole Oceanographic Institution (WHOI), USA) Beverly de Cuevas (National Oceanography Centre, Southampton (NOC), UK) Nikolay Diansky (Moscow, Russian Academy of Science (MRAS), Russia) Sirpa Hakkinen (Goddard Space Flight Center (GSFC), USA) Wieslaw Maslowski (Naval Postgraduate School (NPL), USA) An T. Nguyen (Jet Propulsion Laboratory (JPL), USA) Jinlun Zhang (Polar Science Center, University of Washington (PSC-UW), USA)

Major goals Validate AOMIP models and recommend model improvements Investigate variability of sea ice thickness and sea ice volume in the Arctic Ocean and a role of different factors influencing their changes

Major objectives: Collect sea ice thickness observational data; Validate regional Arctic models based on observations; Investigate major problems causing discrepancies among model results and observations; Recommend ways for model improvements;

Gerdes, R., and C. Koberle (2007), Comparison of Arctic sea ice thickness variability in IPCC Climate of the 20th Century experiments and in ocean – sea ice hindcasts, J. Geophys. Res., 112, C04S13, doi:10.1029/2006JC003616. No direct comparison with observed sea ice thickness was done because sea ice thickness data that cover the Arctic Ocean spatially and temporarily with the necessary resolution are not available. The AOMIP hindcast results are similar among each other in many respects. Especially, the variability of sea ice thickness distribution is apparently mostly determined by the identical, prescribed atmospheric forcing. The AWI1 hindcast results have been validated earlier with the available direct sea ice draft observations. That comparison and the strong relationship between atmospheric forcing and simulated sea ice thickness variability justify our use of AOMIP hindcast results as a benchmark for the IPCC model results. It should be clear, however, that the AOMIP results are model results and that there exists a certain range of results among the AOMIP hindcasts that indicate the degree of uncertainty in those calculations.

Gerdes, R., and C. Koberle (2007) “No direct comparison with observed sea ice thickness was done because sea ice thickness data that cover the Arctic Ocean spatially and temporarily with the necessary resolution are not available. The AOMIP hindcast results are similar among each other in many respects. Especially, the variability of sea ice thickness distribution is apparently mostly determined by the identical, prescribed atmospheric forcing. The AWI1 hindcast results have been validated earlier with the available direct sea ice draft observations. That comparison justify our use of AOMIP hindcast results as a benchmark for the IPCC model results. It should be clear, however, that the AOMIP results are model results and that there exists a certain range of results among the AOMIP hindcasts that indicate the degree of uncertainty in those calculations. “

Sea Ice thickness data sources Upward Looking Sonar data from submarines Upward Looking Sonar data from moorings Sea ice thickness from electromagnetic surveys Sea ice thickness from coastal marine observatories, drifting stations and buoys (such as IMBs – Ice-Mass Balance buoys)

These data have been analyzed by : Bourke, R. H., and R. P. Garrett (1987) McLaren, A. S. (1989) Wadhams, P. (1990) Wadhams, P., and N. R. Davis (2000) Winsor, P. (2001) Tucker,W. B., J.W.Weatherly, D. T. Eppler, L. D. Farmer, and D. L. Bentley (2001) Wensnahan, M., and D. A. Rothrock (2005) Wensnahan, M., D. A. Rothrock, and P. Hezel (2007) Rothrock, D. A., D. B. Percival, and M. Wensnahan (2008) Naval submarines have collected operational data of sea-ice draft (93% of thickness) in the Arctic Ocean since 1958. Data from 34 U.S. cruises are publicly archived. They span the years 1975 to 2000. The data are available at: National Snow and Ice Data Center (2006), Submarine upward looking sonar ice draft profile data and statistics, Boulder, Colorado USA: National Snow and Ice Data Center/World Data Center for Glaciology. Digital media.

Climatologic ice thickness in different AOMIP models UW GSFC ORCA MRAS

Model validation based on submarine data

Model validation based on submarine data

Satellite ice-thickness Data Kwok, R., G. F. Cunningham, M. Wensnahan, I. Rigor, H. J. Zwally, and D. Yi (2009), Thinning and volume loss of the Arctic Ocean sea ice cover: 2003–2008, J. Geophys. Res., 114, C07005, doi:10.1029/2009JC005312. “We present our best estimate of the thickness and volume of the Arctic Ocean ice cover from 10 Ice, Cloud, and land Elevation Satellite (ICESat) campaigns that span a 5-year period between 2003 and 2008. Derived ice drafts are consistently within 0.5 m of those from a submarine cruise in mid-November of 2005 and 4 years of ice draft profiles from moorings in the Chukchi and Beaufort seas.”

Satellite data in common grid

Errors: Satellite minus UW model data RESULTS: MSE=0.43 m^2 Mean error=0.28 m Mean abs error=0.48 m

Errors: Satellite minus GSFC model data RESULTS: MSE= 2.3 m^2 Mean error=0.34 m Mean abs error=0.99 m

Errors: Satellite minus ECCO2 model data RESULTS: MSE= 0.44 m^2 Mean error= -0.11 m Mean abs error= 0.51 m

Observed-simulated trends 2004-2008 UW SAT GSFC ECCO2

Ice volume integration region Ice volume changes

Preliminary conclusions The major goals of this AOMIP activity are to: (1) validate AOMIP models and recommend model improvements, and (2) investigate variability of sea ice thickness and sea ice volume in the Arctic Ocean and a role of different factors influencing their changes. The major objectives are to: (1) Collect sea ice thickness observational data; (2)Validate regional Arctic models based on observations; (3) Investigate major problems causing discrepancies among model results and observations; (4) Recommend ways for model improvements. Four sea ice thickness data sources are planned to be collected for this study: (1) Upward Looking Sonar data from submarines; (2) Upward Looking Sonar data from moorings; (3) Sea ice thickness from electromagnetic survey; and (4) Sea ice thickness from coastal marine observatories, drifting stations and buoys (such as IMBs – Ice-Mass Balance buoys). At this stage, the simulated monthly sea ice thickness data from five AOMIP models representing University of Washington (PIOMAS model), Goddard Space Flight Center (GSFC model), Jet Propulsion Laboratory (ECCO2 model), National Oceanographic Center, Southampton (ORCA model), and from Institute of Numerical Mathematics, Russian Academy of Sciences (MRAS model) from were used. These data were compared with observations from submarines for 1979-2002 and with observations from satellites (R. Kwok, 2009) for February-March of 2004-2008. Preliminary analyses of this project results allows us to conclude: that statistical characteristics of model uncertainties have shown that the UW and ECCO2 models have errors comparable with uncertainties of the observational data while the other models results have higher errors.