Informativeness (information-bearing) of hydrometeorological and astrogeophysical factors in the problem of describing interannual fluctuations of the Greenland Sea ice coverage

Abstract

The interannual changes in ice coverage in the Greenland Sea for the winter (December–April), spring (May– June), summer (July–September), and autumn (October–November) seasons for the period 1950-2018 are considered. The presence of negative linear trends and the polycyclic oscillations of the ice coverage variability for all seasons has been confirmed. Using spectral analysis, the dominant fluctuations from 5 to 22 years were identified. The cross-correlation method allowed us to determine the significant relationship of the Greenland Sea ice coverage with hydrometeorological and astrogeophysical factors. The statistically significant relationship of the ice coverage for a concrete year with similar characteristics for a previous period persisting up to three years had been noted. The highest cross-correlation coefficients were noted in the winter and spring seasons. The ice coverage of the autumn season demonstrates the persistence of the inertia of ice conditions for up to two years. The analysis of correlations with astrogeophysical parameters revealed the closest relationship between the ice coverage and the longitude coordinate of the Earth's pole position, the nutation parameters of the Earth's axis, and the distance between the Earth and the Sun. When constructing the multi-regression equations, we investigated the informativeness of various hydrometeorological and astrogeophysical factors in the models of the ice coverage variability for each season. The following estimates of quality of the models were obtained: correlation coefficients (up to 0.89), determination coefficients (to up 0.80), and a model reliability which depends on the admissible forecast error and includes the mean square deviation of the investigated value) – up to 99%). The informativeness of various factors was estimated and the contribution to the total variance was revealed: hydrometeorological factors – up to 70%; astrogeophysical factors – up to 50%. The obtained statistical equations can be used for the diagnosis and for development of methods for the very-long-term forecast of the Greenland Sea ice coverage.

Keywords

• greenland sea
• hydrometeorological and astrogeophysical impact
• ice coverage
• interannual variability
• multiple regression
• sea ice
• statistical equations for diagnosis