IGOR POLYAKOV
I. Polyakov, G. V. Alekseev, R. V. Bekryaev, U. Bhatt, R. Colony, M. Johnson, V. P. Karklin, D. Walsh, and A. V. Yulin
[for more details read the papers Polyakov et al, 2002, 2003]
Russian historical records of arctic sea-ice extent and thickness extend back to the beginning of the 20th century. There are several distinct periods in the history of Russian sea-ice observations. Occasional ship observations of summer ice edge started in the first decade of the 1900s when the first Russian hydrographic surveys and commercial shipping routes along the Siberian coast began. These data have been analyzed by the Russian climatologist Vize (1944). Some data for this period have also been obtained from Russian navigation books. Starting in 1929, when the Soviet Polar Aircraft Fleet was created, aircraft-based observations began, which improved the quality of the data substantially. However, systematic aircraft and ship observations of sea ice from the Kara Sea through the Chukchi Sea began only in 1932, when the Northern Sea Route was created. There were information gaps during World War II (1942-45). The missing data have been reconstructed using statistical (regression-like) models relating atmospheric processes (SLP gradients and SAT) to ice extent (Kovalev and Nikolaev 1976; Yulin 1990). Aircraft ice-edge observations continued until 1979, when the satellite era began, but until recently a combination of satellite and aircraft summer ice-edge observations was used. Since 1990 all ice-extent observations have been satellite-based.
In this study, we use August ice extent for the four seas (the regions from which the data were collected are shown in Figure 1). The errors in defining ice-edge position from ship and aircraft are about 2-10km. These data were mapped, and the ice-covered area was estimated. Generalization of this information for the whole domain may introduce rather large errors if only a few measurements of ice edge position are available. Also, it is rather difficult to evaluate possible errors introduced by this generalization into the total ice-extent estimate. This is especially true for the beginning of the 20th century, when observational data were extremely scarce. While these data may have substantial errors, they are unique in indicating important changes in the arctic environment since the dawn of the industrial era.
Five locations where measurements are available of fast-ice thickness (motionless sea ice anchored to the sea floor and/or the shore) are shown in Figure 1 by stars; these data extend back to 1936. The observations were carried out at Russian polar stations, where observers drilled holes in ice and directly measured thickness, a rather precise method of observation (though not necessarily representative of the areal average). Measurements of fast-ice thickness are also invaluable because they provide an opportunity to separate, to some extent, the contribution of thermodynamical and dynamical factors in the formation of arctic ice since they measure ``pure'' thermodynamical ice growth. The annual maximum ice thickness typically reached in May is analyzed.
The data and their wavelet analyses are shown in Figures 2 and 3. Detailed description of the data may be found in (Polyakov et al., 2002, 2003).
Bug (April 14, 2003):
Attention, Dr. Wang Xuezhong found a bug in the ice
thickness data. The order of stations was wrong. Should be:
DI ST SA WR CH
Sorry for this inconvenience.
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These data are available on web (download the data: Unix tar format or Windows zip format)
The file with data is ice_arctic_seas.tar or ice_arctic_seas.zip. This file is a converted form of a directory named "ice_arctic_seas".
The Unix command:
tar xvf ice_arctic_seas.tar
will transfer this file to the directory "ice_arctic_seas" which includes two files with the ice time series. One file named H_ice_4seas includes fast-ice thickness data. The second file named extent_4seas includes four time series of ice extent. The format of these data is self-explanatory.
Windows XP can handle zip format internally, and there are several commercial and freeware programs (ZipCentral, StuffIt, WinZip, PKZip) for other versions of Windows.
This data set is publicly available and its compilation was made possible through the cooperation of various international groups. We request that users acknowledge the use of this data set by including a citation to the paper [Polyakov I., et al., 2003] in the reference list of published work. Thank you.
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Vize V. Yu., 1944: The Basics of Long-term Ice Forecasts for the Arctic Seas (in Russian), 274 pp., Glavsevmorput', Moscow.
Kovalev, E. G., and Yu. V. Nikolaev, 1976: Application of discriminant analysis for long-term forecast of ice area of arctic seas, in Transactions of the Arctic and Antarctic Research Institute (in Russian), 4-26, vol. 320, Gidrometeoizdat, Leningrad.
Polyakov, I. V., G. V. Alekseev, R. V. Bekryaev, U. Bhatt, R. Colony, M. A. Johnson, V. P. Karklin, A. P. Makshtas, D. Walsh, and A. V. Yulin, 2002: Observationally-based assessment of polar amplification of global warming, Geophys. Res. Lett., 29, 1878, doi:1029/2001GL011111 [ Download PDF file].
Polyakov, I., G. V. Alekseev, R. V. Bekryaev, U. Bhatt, R. Colony, M. A. Johnson, V. P. Karklin, D. Walsh, and A. V. Yulin, 2003: Long-term ice variability in arctic marginal seas, J. Climate, accepted [Download PDF file].
Yulin, A. V., 1990: Automatization program system for analysis and generalization of hydrometeorological information used in prognostic system ``PEGAS'', in Transactions of the Arctic and Antarctic Research Institute (in Russian), 157-162, vol. 418, Gidrometeoizdat, St. Petersburg.
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Figure 1.
Map of the Arctic Ocean, with colors denoting ice extent analysis regions. Locations of sea level pressure observations are shown by red dots. Red stars denote stations where ice thickness data were collected. Red lines denote locations of cross sections used for analysis of the modeling ice and water transports.
Figure 2.
(Left panels) Time series of the ice-extent anomalies (1000km^2) in four arctic seas. Dotted lines show annual means from observations (blue) and modeling (red), solid lines show six-year running means from observations (blue) and modeling (red), green dashed lines show linear trends (quoted limits represent 95% confidence levels). Note axis scalings are not uniform. (Right panels) Wavelet transform of annual ice extent using the Mexican Hat (m=2) wavelet (Torrence and Compo 1998). Vertical axes show the period in years. The black contours are the 95% (thick) and 68% (thin) confidence levels, the black cross-hatched area denotes the region of the wavelet spectrum in which edge effects become important. The time series and wavelet transform indicate two periods of minimum ice extent associated with positive LFO phases (and warming in the 1930-40s and late 1980s-90s) and two periods of maximum ice extent associated with negative LFO phases (and cooling prior to the 1920s and in the 1960-70s).
Figure 3.
Left panels. Time series of ice-thickness anomalies (cm) at five locations. Dotted blue lines show annual means and solid blue lines show six-year running means, green dashed lines show linear trends (quoted limits represent 95% confidence levels).
Right panels. Wavelet transform of annual fast-ice thickness using the ``Mexican Hat'' (m=2) wavelet. Vertical axes show the period in years. The black contours are the 95% (thick) and 68% (thin) confidence levels, the black cross-hatched area denotes the region of the wavelet spectrum in which edge effects become important (hence statistical significance is low). The time series and wavelet transform at Dikson and Sterlegov (Kara Sea) and Chetirekhstolbovii (East Siberian Sea) indicate two periods of minimum ice extent associated with positive LFO phases and one period of maximum ice extent associated with negative LFO phase.
Last modified: December 10, 2004. 08:48:11 am