Probabilistic models for the prediction of a ship performance in dynamic ice

We introduce two probabilistic, data-driven models that predict a ship's speed and the situations where a ship is probable to get stuck in ice based on the joint effect of ice features such as the thickness and concentration of level ice, ice ridges, rafted ice, moreover ice compression is considered. To develop the models to datasets were utilized. First, the data from the Automatic Identification System about the performance of a selected ship was used. Second, a numerical ice model HELMI, developed in the Finnish Meteorological Institute, provided information about the ice field. The relations between the ice conditions and ship movements were established using Bayesian learning algorithms. The case study presented in this paper considers a single and unassisted trip of an ice-strengthened bulk carrier between two Finnish ports in the presence of challenging ice conditions, which varied in time and space. The obtained results show good prediction power of the models. This means, on average 80% for predicting the ship's speed within specified bins, and above 90% for predicting cases where a ship may get stuck in ice. We expect this new approach to facilitate the safe and effective route selection problem for ice-covered waters where the ship performance is reflected in the objective function.

Future CO2-induced ocean acidification mediates the physiological performance of a green tide alga Ulva prolifera

The oceans take up more than 1 million tons of CO2 from the air per hour, about one-quarter of the anthropogenically released amount, leading to disrupted seawater chemistry due to increasing CO2 emissions. Based on the fossil fuel-intensive CO2 emission scenario (A1F1; Houghton et al., 2001), the H+ concentration or acidity of surface seawater will increase by about 150% (pH drop by 0.4) by the end of this century, the process known as ocean acidification (OA; Sabine et al., 2004; Doney et al., 2009; Gruber et al., 2012). Seawater pH is suggested to decrease faster in the coastal waters than in the pelagic oceans due to the interactions of hypoxia, respiration, and OA (Cai et al., 2011). Therefore, responses of coastal algae to OA are of general concern, considering the economic and social services provided by the coastal ecosystem that is adjacent to human living areas and that is dependent on coastal primary productivity. On the other hand, dynamic environmental changes in the coastal waters can interact with OA (Beardall et al., 2009).