Methods and results of statistical analysis of Baltic sea monitoring data obtained by Alg@line system

The report presents a statistical analysis of sea water temperature and salinity measurements, implemented in framework of Alg@line project. The specificity of this information is that the measurements are performed at a depth 5 m with temporal discreteness about 20 sec and spatial resolution 200-250 m. In statistical analysis we will take as ensemble of realizations in space of desired configuration. Measurement data obtained from route Helsinki-Lübeck were used in this work; the cruises are quasiregular: their average duration is about 26 hours, the sections length L=1132 km, vessel speed on some areas is a random variable, sailing schedule have seasonal and inter-annual changes. Due to cruises “regularity”, in pattern space it becomes possible to split the ensemble of “spatial field inhomogeneity and its temporal variability” into algebraic field inhomogeneity and polycyclicity of its variability (in daily, synoptic, seasonal and inter-annual ranges). The dimensionality reduction of two-dimensional space (r_i, t_i) in one-dimensional space is achieved due to dependence r_i=ct_i, where (r_i, t_i) are fixed, c - ship speed - is the random variable. It enables to use for data analysis the theory of almost periodically correlated random processes (Dragan, Rozhkov, Yayorskiy. Methods of probabilistic analysis of oceanographic processes rhythmics. Gidrometeoizdat, 1987). In the report the concept “rhythmics” is using in terms of cruises “regularity” and diurnal temperature variation of water, hence the daily rhythm should be analyzed in the astronomical time. Stochasticity has different meaning depending on selected probabilistic model. Probabilistic model can be represented as: ξ(r, t) = Σa_k(t)φ_k(r), where a_k(t) - stochastic process, φ_k(r) - basis. The analysis - esults are presented in the report in the form: TS-diagrams typical for cruises, spatial TS-trends, parameters of the temperature daily rhythmic, synoptic variability parameters, considering its seasonal modulation.