Abstract-Microwave model for simulation of radiation from the multilayer system "sea surface-sea icesnow cover-atmosphere" is introduced. In the general case, ice and snow cover is modelled by multilayer medium, where every layer is characterized by its specific physical parameters. Electrodynamical properties of each layer are determined from the original authors' model of the effective permittivity of heterogeneous medium. This model takes into account effects of radiation scattering on irregularities of environment. Measurable physical characteristics of sea ice and snow are used as the model input data. This advantage allows using this model for interpretation of remote sensing images of the ice cover in the Polar Regions. Major attention is drawn to comparison of model calculations with satellite data and visual observations from ships. The collection of SSM/I and SSMIS images from GLOBAL-RT data base, and processed visual observations from ships in Arctic cruises were used. Observations data served as the input parameters for electrodynamical model. Comparison of model results with SSM/I images demonstrated good coincidence at various frequencies.

No abstract

No abstract

No abstract

The paper presents a comparison of sea ice concentration (SIC) derived from satellite microwave radiometry data and dedicated ship observations. For the purpose, the NASA Team (NT), Arctic Radiation and Turbulence Interaction Study (ARTIST) Sea Ice (ASI), and Variation Arctic/Antarctic Sea Ice Algorithm 2 (VASIA2) algorithms were used as well as the database of visual ice observations accumulated in the course of 15 Arctic expeditions. The comparison was performed in line with the SIC gradation (in tenths) into very open (1–3), open (4–6), close (7–8), very close and compact (9–10,10) ice, separately for summer and winter seasons. On average, in summer NT underestimates SIC by 0.4 tenth as compared to ship observations, while ASI and VASIA2 by 0.3 tenth. All three algorithms overestimate total SIC in regions of very open ice and underestimate it in regions of close, very close, and compact ice. The maximum average errors are typical of open ice regions that are most common in marginal ice zones. In winter, NT and ASI also underestimate SIC on average by 0.4 and 0.8 tenths, respectively, while VASIA2, on the contrary, overestimates by 0.2 tenth against the ship data, however, for open and close ice the average errors are significantly higher than in summer. In the paper, we also estimate the impact of ice melt stage and presence of new ice and nilas on SIC derived from NT, ASI, and VASIA2.