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Ilia N. Mordvintsev

Publications and source records attributed to Ilia N. Mordvintsev.

3 recordsLinked to original sources

Estimating the time of melt onset and freeze onset over Arctic sea-ice area using active and passive microwave data

Accurate calculation of the time of melt onset, freeze onset, and melt duration over Arctic sea-ice area is crucial for climate and global change studies because it affects accuracy of surface energy balance estimates. This comparative study evaluates several methods used to estimate sea-ice melt and freeze onset dates: (1) the melt onset database derived from SSM/I passive microwave brightness temperatures ( T b s) using Drobot and Anderson's [J. Geophys. Res. 106 (2001) 24033] Advanced Horizontal Range Algorithm (AHRA) and distributed by the National Snow and Ice Data Center (NSIDC); (2) the International Arctic Buoy Program/Polar Exchange at the Sea (IABP/POLES) surface air temperatures (SATs); (3) an elaborated version of the AHRA that uses IABP/POLES to avoid anomalous results (Passive Microwave and Surface Temperature Analysis [PMSTA]); (4) another elaborated version of the AHRA that uses T b variance to avoid anomalous results (Mean Differences and Standard Deviation Analysis [MDSDA]); (5) Smith's [J. Geophys. Res. 103 (1998) 27753] vertically polarized T b algorithm for estimating melt onset in multiyear (MY) ice (SSM/I 19V–37V); and (6) analyses of concurrent backscattering cross section ( σ °) and brightness temperature ( T b ) from OKEAN-01 satellite series. Melt onset and freeze onset maps were created and compared to understand how the estimates vary between different satellite instruments and methods over different Arctic sea-ice regions. Comparisons were made to evaluate relative sensitivities among the methods to slight adjustments of the T b calibration coefficients and algorithm threshold values. Compared to the PMSTA method, the AHRA method tended to estimate significantly earlier melt dates, likely caused by the AHRA's susceptibility to prematurely identify melt onset conditions. In contrast, the IABP/POLES surface air temperature data tended to estimate later melt and earlier freeze in all but perennial ice. The MDSDA method was least sensitive to small adjustments of the SMMR–SSM/I inter-satellite calibration coefficients. Differences among methods varied by latitude. Freeze onset dates among methods were most disparate in southern latitudes, and tended to converge northward. Surface air temperatures (IABP/POLES) indicated freeze onset well before the MDSDA method, especially in southern peripheral seas, while PMSTA freeze estimates were generally intermediate. Surface air temperature data estimated latest melt onset dates in southern latitudes, but earliest melt onset in northern latitudes. The PMSTA estimated earliest melt onset dates in southern regions, and converged with the MDSDA northward. Because sea-ice melt and freeze are dynamical transitional processes, differences among these methods are associated with differing sensitivities to changing stages of environmental and physical development. These studies contribute to the growing body of documentation about the levels of disparity obtained when Arctic seasonal transition parameters are estimated using various types of microwave data and algorithms.

Remote Sensing of Environment↗

Comparative analysis of multisensor satellite monitoring of Arctic sea-ice

This report represents comparative analysis of nearly coincident Russian OKEAN-01 polar orbiting satellite data, Special Sensor Microwave Imager (SSM/I) and Advanced Very High Resolution Radiometer (AVHRR) imagery. OKEAN-01 ice concentration algorithms utilize active and passive microwave measurements and a linear mixture model for measured values of the brightness temperature and the radar backscatter. SSM/I and AVHRR ice concentrations were computed with NASA Team algorithm and visible and thermal-infrared wavelength AVHRR data, accordingly

Book↗

Assessing variability and trends in Arctic sea ice distribution using satellite data

Trends in the annual minimum, minimum monthly-mean, and the sea ice extent at the end of August were investigated for the Barents and western Kara Seas and adjacent parts of the Arctic Ocean during 1966 to 1994 using data from Russian ice maps (1974-1994), Kosmos-Okean and ALMAZ SAR satellite series (1984-1994), and published literature. Four definitions of sea ice extent were examined based on thresholds of ice concentration: >90%, >70%, >40% and >10% (E1, E2, E3, and E4, respectively). Root-mean-square differences between sea ice maps and satellite-image sea ice classifications for coincident areas were subjected to Monte-Carlo analyses to construct confidence intervals for the 20-year ice-map trends. With probability p=0.8, the average 20-year change in the minimum monthly-mean sea ice extent (followed in brackets by the average change in the absolute annual minimum ice extent) was between 30-60% [19-71%], 29-61% [15-67%], 31-63%[18-69%] and 18-48% [7-55%] in the Barents sea; (-24)-(-4)% [(-25)-(12)%], (-27)-(-9)% [(-34)-(-4)%], (-32)-(-15)% [(-39)-(-9)%] and (-33)-(-15)%[(-38)-(-8)%] in the western Kara sea; and (-3)-19% [(-8)-29%], (-4)-18% [(-11)-26%,] (-6)-16% [(-11)(-24)%] and (-7)-15% [(-12)-24%] in the combined Barents and Kara Seas, for sea ice concentration E1-E4, respectively. Including published data from 1966-1983, the trend in minimum monthly-mean sea ice extent for the combined 30-year period showed an average increasing of 11.8% in the Barents Sea and of 47.4% reduction in the western Kara Sea; sea ice extent at the end of August showed an average reduction of 4.7% in the Barents Sea.

Conference Paper↗