Publishing House SB RAS:

Publishing House SB RAS:

Address of the Publishing House SB RAS:
Morskoy pr. 2, 630090 Novosibirsk, Russia



Advanced Search

Earth’s Cryosphere

2022 year, number 5

FREQUENCY OF OCCURRENCE OF FAST ICE CALCULATED FROM POLYGONS OF DIGITIZED ICE CHARTS (BY THE EXAMPLE OF THE KARA SEA)

R.I. May1,2, K.R. Ganieva1, A.G. Topaj3, A.V. Yulin4
1St. Petersburg State University, Universitetskaya emb. 7/9, St. Petersburg, 199034, Russia
2Krylov State Research Center, Moskovskoe shosse 44, St. Petersburg, 196158, Russia
3LLC "Bureau Hyperborea", Kavalergardskaya str. 6A, St. Petersburg, 191015, Russia
4Arctic and Antarctic Research Institute, Beringа str. 38, St. Petersburg, 199397, Russia
Keywords: fast ice, sea ice, Kara Sea, analysis of polygons

Abstract

Many elements of the natural environment are areal objects that change their position and shape at all scales of variability. For sea ice, such elements can be fast ice, drifting ice, polynyas, ice massifs, boundaries of multi-year ice. In other earth sciences, these are the boundaries of glaciers, permafrost, snow cover, forest zone, various isolines of meteorological and oceanological fields (isotherms, isobars, etc.). To analyze such objects, approximations in the form of a grid area (rasterization) or a system of sections are usually used. In this article, we suggest a direct analysis of these objects based on operations with vector polygons. An efficient algorithm for calculating the probability (frequency of occurrence) of an unlimited number of polygons has been developed and tested. A criterion for selecting one of the real edges of a polygon as an analogue of the isoline of probability of intersections of polygons is proposed. The developed method has been tested using data on the fast ice of the Kara Sea taken from the digital ice charts developed by the Arctic and Antarctic Research Institute for 1998-2020. As a result, the maps of fast ice probability for the cold season of each year and for a given time of the year for the entire considered period have been obtained. Based on these data, the operational characteristics of fast ice have been estimated, and a tendency for a decrease in the area of fast ice during the considered period has been revealed. For the beginning of May (period of the maximum development of fast ice), analogues from factual observations characterizing extreme, median, and quartile probability isolines of fast ice occurrence have been found.