The tasks of the expedition: - conducting complex hydrometeorological observations in the spring-summer period in the Arctic basin of the Arctic Ocean; - obtaining data on the morphometry of the ice cover, the physical and mechanical properties of ice; - study of hydrometeorological and oceanographic conditions.

Global phytoplankton production monthly maps for 2017 are produced using an artificial neural network to perform a generalized nonlinear regression of PP on several predictive variables, including latitude, longitude, day length, MLD, SST, PBopt computed according to Behrenfeld and Falkowski (1997), PAR and CHL(0 m). More details about this model can be found in Scardi (2001). Behrenfeld, M. J., Falkowski, P. G. (1997), Photosynthetic rates derived from satellite-based chlorophyll concentration, Limnology & Oceanography, 42(1), 1–20. Scardi, M. (2001), Advances in neural network modeling of phytoplankton primary production, Ecological Modelling, 146, 33–45.