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

Analysis of Arctic ice thickness, freeboard, and snow cover from the data

of Russian Sever expeditions

V.Y. Alexandrov

S. SandvenNansen Environmental and Remote Sensing Centre/Nansen International Environmental

and Remote Sensing Centre

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.

“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

The number of landings per month of yearLocation of landing sites by decades

Sever data

Analyzed Sever data – mainly for FY-ice

Mean ice and snow thickness on runway and surrounding ice

Distribution of ice and snow thickness

)996.0(37.013.8 2 RFH iceice

Empirical relation between mean ice thickness and freeboard:

Valid:

• Late winter,

• FY-ice

Isostatic equilibrium equation:

Hi= ρw/(ρw - ρi) Fi + ρsn Hsn/(ρw - ρi)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]:

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ερi, ερw, ερsn – uncertainties of ice, water, and snow densities, εHsn – snow depth uncertainty, εFi – error of freeboard measurement

iiullmy HF)(

Ice density

Ice density vs. ice thickness from Sever data – FY-ice

Ice density from literature

For MY ice – average weighted density of upper (ρu, 550 kgm-3) and lower ρl, 920 kgm-3) layers:i

snsniwwi H

HF

05

10152025303540

"S now depth (W )" S now depth (L )

Expedition, periodNumber of measurements

Average snow density

Sever, March 27 336.3±40.1

Sever, April 158 316.4±57.2

Sever, May 169 328.3±43.2

Sever, June 11 339.1±30.2

Sever, March-June 365 324.1±49.6

Polarstern, Lance, March-April

55 315.3±67.7

Snow depth, Central Arctic

00,10,20,30,40,5

"S now dens ity (g/c m3)"

Snow density, Central Arctic

Snow density from Sever data

15.046.9 ii FH 07.124.6 ii FH

Dependence of ice thickness on freeboard in late winter from isostatic equilibrium equation:

FY-ice MY-ice

Typical values and uncertainties of snow and ice density and snow depth for late winter.

Parameter Ice type

FY ice MY ice

Typical value Uncertainty Typical value Uncertainty

Ice freeboard, m 0.01-0.2 0.05 0.3 0.05

Snow depth, m 0.05 0.05 0.35 0.06

Ice density, kgm-3 916.7 35.7 882 23

Snow density, kgm-3 324 50 320 20

Uncertainty of ice thickness calculation For error of ice freeboard retrieval of 0.05 m

FY-ice MY-ice

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.

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.