(Table 2) Characteristics of a turbidite flow inferred from physiography and morphology of the margin and the sediment waves

This paper presents the morpho-sedimentary characterization and interpretations of the assemblage of landforms of the East Greenland continental slope and Greenland Basin, based on swath bathymetry and sub-bottom TOPAS profiles. The interpretation of landforms reveals the glacial influence on recent sedimentary processes shaping the seafloor, including mass-wasting and turbidite flows. The timing of landform development points to a predominantly glacial origin of the sediment supplied to the continental margin, supporting the scenario of a Greenland Ice Sheet extending across the continental shelf, or even to the shelf-edge, during the Last Glacial Maximum (LGM). Major sedimentary processes along the central section of the eastern Greenland Continental Slope, the Norske margin, suggest a relatively high glacial sediment input during the LGM that, probably triggered by tectonic activity, led to the development of scarps and channels on the slope and debris flows on the continental rise. The more southerly Kejser Franz Josef margin has small-scale mass-wasting deposits and an extensive turbidite system that developed in relation to both channelised and unconfined turbidity flows which transferred sediments into the deep Greenland Basin.

Part of the global DOC versus AOU (dissolved organic carbon/apparent oxygen utilization) data compilation, Pacific Ocean

Total organic carbon (TOC) was analyzed on four transects along 140°W in 1992 using a high temperature combustion/discrete injection (HTC/DI) analyzer. For two of the transects, the analyses were conducted on-board ship. Mixed-layer concentrations of organic carbon varied from about 80 µM C at either end of the transect (12°N and 12°S) to about 60 µM C at the equator. Total organic carbon concentrations decreased rapidly below the mixed-layer to about 38-40 µM C at 1000 m across the transect. Little variation was observed below this depth; deep water concentrations below 2000 m were virtually monotonic at about 36 µM C. Repeat measurements made on subsequent cruises consistently found the same concentrations at 1000 m or deeper, but substantial variations were observed in the mixed-layer and the upper water column above 400 m depth. Linear mixing models of total organic carbon versus sigmaT exhibited zones of organic carbon formation and consumption. TOC was found to be inversely correlated with apparent oxygen utilization (AOU) in the region between the mixed-layer and the oxygen minimum. In the mixed-layer, TOC concentrations varied seasonally. Part of the variations in TOC at the equator was driven by changes in the upwelling rate in response to variations in physical forcing related to an El Niño and to the passage of tropical instability waves. TOC export fluxes, calculated from simple box models, averaged 8±4 mmol C/m**2/day at the equator and also varied seasonally. These export fluxes account for 50-75% of the total carbon deficit and are consistent with other estimates and model predictions.

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.