154 resultados para models for the sp³ carbon atom

em Publishing Network for Geoscientific


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We use a suite of eight ocean biogeochemical/ecological general circulation models from the MAREMIP and CMIP5 archives to explore the relative roles of changes in winds (positive trend of Southern Annular Mode, SAM) and in warming- and freshening-driven trends of upper ocean stratification in altering export production and CO2 uptake in the Southern Ocean at the end of the 21st century. The investigated models simulate a broad range of responses to climate change, with no agreement ona dominance of either the SAM or the warming signal south of 44° S. In the southernmost zone, i.e., south of 58° S, they concur on an increase of biological export production, while between 44 and 58° S the models lack consensus on the sign of change in export. Yet, in both regions, the models show an enhanced CO2 uptake during spring and summer. This is due to a larger CO 2 (aq) drawdown by the same amount of summer export production at a higher Revelle factor at the end of the 21st century. This strongly increases the importance of the biological carbon pump in the entire Southern Ocean. In the temperate zone, between 30 and 44° S all models show a predominance of the warming signal and a nutrient-driven reduction of export production. As a consequence, the share of the regions south of 44° S to the total uptake of the Southern Ocean south of 30° S is projected to increase at the end of the 21st century from 47 to 66% with a commensurable decrease to the north. Despite this major reorganization of the meridional distribution of the major regions of uptake, the total uptake increases largely in line with the rising atmospheric CO2. Simulations with the MITgcm-REcoM2 model show that this is mostly driven by the strong increase of atmospheric CO2, with the climate-driven changes of natural CO2 exchange offsetting that trend only to a limited degree (~10%) and with negligible impact of climate effects on anthropogenic CO2 uptake when integrated over a full annual cycle south of 30° S.

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During IODP Expedition 302 (Arctic Coring Expedition-ACEX), the first scientific drilling campaign in the permantly ice-covered central Arctic Ocean, a 430 m thick sequence of upper Cretaceaous to Quaternary sediments has been drilled. The lower half of this sequence is composed of organic-carbon-rich (black shale-type) sediments with total organic carbon contents of about 1-14%. Significant amounts of the organic matter preserved in these sediments is of algae-type origin and accumulated under anoxic/euxinic conditions. Here, for the first time detailed data on the source-rock potential of these black shales are presented, indicating that most of the Eocene sediments have a (fair to) good source-rock potential, prone to generate a gas/oil mixture. The source-rock potential of the Campanian and upper Paleocene sediments, on the other hand, is rather low. The presence of oil or gas already generated in situ, however, can be ruled out due to the immaturity of the ACEX sediments.

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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.

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Fragilariopsis kerguelensis, a dominant diatom species throughout the Antarctic Circumpolar Current, is coined to be one of the main drivers of the biological silicate pump. Here, we study the distribution of this important species and expected consequences of climate change upon it, using correlative species distribution modeling and publicly available presence-only data. As experience with SDM is scarce for marine phytoplankton, this also serves as a pilot study for this organism group. We used the maximum entropy method to calculate distribution models for the diatom F. kerguelensis based on yearly and monthly environmental data (sea surface temperature, salinity, nitrate and silicate concentrations). Observation data were harvested from GBIF and the Global Diatom Database, and for further analyses also from the Hustedt Diatom Collection (BRM). The models were projected on current yearly and seasonal environmental data to study current distribution and its seasonality. Furthermore, we projected the seasonal model on future environmental data obtained from climate models for the year 2100. Projected on current yearly averaged environmental data, all models showed similar distribution patterns for F. kerguelensis. The monthly model showed seasonality, for example, a shift of the southern distribution boundary toward the north in the winter. Projections on future scenarios resulted in a moderately to negligibly shrinking distribution area and a change in seasonality. We found a substantial bias in the publicly available observation datasets, which could be reduced by additional observation records we obtained from the Hustedt Diatom Collection. Present-day distribution patterns inferred from the models coincided well with background knowledge and previous reports about F. kerguelensis distribution, showing that maximum entropy-based distribution models are suitable to map distribution patterns for oceanic planktonic organisms. Our scenario projections indicate moderate effects of climate change upon the biogeography of F. kerguelensis.