1. Analysis of Arctic ice thickness, freeboard, and snow cover from the data of Russian Sever expeditions V.Y. Alexandrov S. Sandven Nansen Environmental and Remote Sensing Centre/Nansen International Environmental and Remote Sensing Centre

2. Objectives: Development of ice freeboard – thickness transformation using in situ measurements of sea ice and snow parameters, Analysis of ice thickness and freeboard measurements, conducted in high-latitude “Sever” expeditions, Estimation of accuracy of ice thickness calculation from its freeboard.

3. “SEVER” expeditions The High-Latitude Airborne Annual Expeditions Sever (Sever means North) took place in 1937, 1941, 1948-1952, and 1954-1993 The most extensive data set of sea ice and snow measurements was collected during aircraft landings in the Soviet Union's historical Sever airborne programs The data set contains measurements of sea ice and snow parameters

4. The number of landings per month of year Location of landing sites by decades Sever data

5. Analyzed Sever data – mainly for FY-ice

6. Mean ice and snow thickness on runway and surrounding ice

7. Distribution of ice and snow thickness

8. Empirical relation between mean ice thickness and freeboard: Valid: Late winter, FY-ice

9. Isostatic equilibrium equation: Hi= ρ w /(ρ w - ρ i ) F i + ρ sn H sn /(ρ w - ρ i ) ρw – seawater density, ρi – ice density, ρsn – snow density, Fi – freeboard, Hsn – snow depth. The error of ice thickness calculation from its freeboard [Giles et al., 2007]: ε ρi, ε ρw, ε ρsn – uncertainties of ice, water, and snow densities, ε Hsn – snow depth uncertainty, ε Fi – error of freeboard measurement

10. Ice density Ice density vs. ice thickness from Sever data – FY-ice Ice density from literature For MY ice – average weighted density of upper (ρ u, 550 kgm -3 ) and lower ρ l, 920 kgm -3 ) layers:

11. Expedition, period Number of measure ments Average snow density Sever, March27336.3±40.1 Sever, April158316.4±57.2 Sever, May169328.3±43.2 Sever, June11339.1±30.2 Sever, March-June365324.1±49.6 Polarstern, Lance, March- April 55315.3±67.7 Snow depth, Central Arctic Snow density, Central Arctic Snow density from Sever data

12. Dependence of ice thickness on freeboard in late winter from isostatic equilibrium equation: FY-iceMY-ice Typical values and uncertainties of snow and ice density and snow depth for late winter. ParameterIce type FY iceMY ice Typical valueUncertaintyTypical valueUncertainty Ice freeboard, m0.01-0.20.050.30.05 Snow depth, m0.05 0.350.06 Ice density, kgm -3 916.735.788223 Snow density, kgm -3 3245032020

13. Uncertainty of ice thickness calculation For error of ice freeboard retrieval of 0.05 m FY-ice MY-ice

15. Conclusions: Relation between thickness and freeboard of the FY-ice, derived from their measurements in “Sever” expeditions allows calculating FY-ice thickness from RA -measurements of its freeboard in the period March-May, The mean and standard deviation of FY-ice density, thickness and density of snow on the FY-ice were calculated from the measurements in “Sever” expeditions. Thickness of the FY-ice can be calculated from the isostatic equilibrium equation in the period March-May using these estimates. The maximum uncertainty of ice thickness calculation amounts to 0.91m, The density of MY-ice is less than that for FY-ice. The MY-ice density calculated as weighted average оf density values for its upper and lower layers amount to (882±23) kgm -3. The maximum uncertainty of MY-ice thickness retrieval is less than that for the FY- ice and amount to 0.79 m for ice thickness of 3.9 m.

16. Acknowledgements: This work was supported by the EU FP6 project DAMOCLES (Developing Arctic Modelling and Observing Capabilities for Long-term Environment Studies, no. 018509), the Research Council of Norway (project No. 178916/S30 Ice-ocean-atmosphere research in Svalbard using satellite and field data – promotion of Russian and Norwegian PhD cooperation), and the ESA Prodex project “CryoSat sea ice validation and process studies in the European Arctic” (contract No. C90318). The Sever data are provided by World Data Center for Glaciology/National Snow and Ice Data Center, University of Colorado, Boulder, Colorado.