We compare the mass budget of the Arctic sea ice for 15 models submitted to the latest Coupled Model Intercomparison Project (CMIP6), using new diagnostics that have not been available for previous model inter-comparisons. These diagnostics allow us to look beyond the standard metrics of ice cover and thickness to compare the processes of sea ice growth and loss in climate models in a more detailed way than has previously been possible. For the 1960–1989 multi-model mean, the dominant processes causing annual ice growth are basal growth and frazil ice formation, which both occur during the winter. The main processes by which ice is lost are basal melting, top melting and advection of ice out of the Arctic. The first two processes occur in summer, while the latter process is present all year. The sea ice budgets for individual models are strikingly similar overall in terms of the major processes causing ice growth and loss and in terms of the time of year during which each process is important. However, there are also some key differences between the models, and we have found a number of relationships between model formulation and components of the ice budget that hold for all or most of the CMIP6 models considered here. The relative amounts of frazil and basal ice formation vary between the models, and the amount of frazil ice formation is strongly dependent on the value chosen for the minimum frazil ice thickness. There are also differences in the relative amounts of top and basal melting, potentially dependent on how much shortwave radiation can penetrate through the sea ice into the ocean. For models with prognostic melt ponds, the choice of scheme may affect the amount of basal growth, basal melt and top melt, and the choice of thermodynamic scheme is important in determining the amount of basal growth and top melt. As the ice cover and mass decline during the 21st century, we see a shift in the timing of the top and basal melting in the multi-model mean, with more melt occurring earlier in the year and less melt later in the summer. The amount of basal growth reduces in the autumn, but it increases in the winter due to thinner sea ice over the course of the 21st century. Overall, extra ice loss in May–June and reduced ice growth in October–November are partially offset by reduced ice melt in August and increased ice growth in January–February. For the individual models, changes in the budget components vary considerably in terms of magnitude and timing of change. However, when the evolving budget terms are considered as a function of the changing ice state itself, behaviours common to all the models emerge, suggesting that the sea ice components of the models are fundamentally responding in a broadly consistent way to the warming climate. It is possible that this similarity in the model budgets may represent a lack of diversity in the model physics of the CMIP6 models considered here. The development of new observational datasets for validating the budget terms would help to clarify this.

Arctic sea-ice area and volume have substantially decreased since the beginning of the satellite era. Concurrently, the poleward heat transport from the North Atlantic Ocean into the Arctic has increased, partly contributing to the loss of sea ice. Increasing the horizontal resolution of general circulation models (GCMs) improves their ability to represent the complex interplay of processes at high latitudes. Here, we investigate the impact of model resolution on Arctic sea ice and Atlantic Ocean heat transport (OHT) by using five different state-of-the-art coupled GCMs (12 model configurations in total) that include dynamic representations of the ocean, atmosphere and sea ice. The models participate in the High Resolution Model Intercomparison Project (HighResMIP) of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Model results over the period 1950–2014 are compared to different observational datasets. In the models studied, a finer ocean resolution drives lower Arctic sea-ice area and volume and generally enhances Atlantic OHT. The representation of ocean surface characteristics, such as sea-surface temperature (SST) and velocity, is greatly improved by using a finer ocean resolution. This study highlights a clear anticorrelation at interannual time scales between Arctic sea ice (area and volume) and Atlantic OHT north of \(60\,^\circ \hbox {N}\) in the models studied. However, the strength of this relationship is not systematically impacted by model resolution. The higher the latitude to compute OHT, the stronger the relationship between sea-ice area/volume and OHT. Sea ice in the Barents/Kara and Greenland–Iceland–Norwegian (GIN) Seas is more strongly connected to Atlantic OHT than other Arctic seas.

The aim of this work was to generate an inventory of the data on radiocarbon datings obtained from sediments of the São Paulo Bight (southern Brazilian upper margin) and to analyze the data in terms of Late Quaternary sedimentary processes and sedimentation rates. A total of 238 radiocarbon datings from materials collected using differents ampling procedures was considered for this work. The sedimentation rates varied from less than 2 to 68 cm.kyr-1. The highest sedimentation rate values were found in a low-energy (ría type) coastal system as well as in the upwelling zones of Santa Catarina and Cabo Frio. The lowest rates were found on the outer shelf and upper slopes. Our results confirm the strong dependency of the shelf currents, with an emphasis to the terrigenous input from the Río de La Plata outflow which is transported via the Brazilian Coastal Current, as well as of the coupled Brazil Current - Intermediate Western Boundary Current (BC-IWBC) dynamics on the sedimentary processes. At least three indicators ofthe paleo sea level were found at 12200 yr BP (conventional radiocarbon age) (103 meters below sea level - mbsl),8300-8800 cal yr BP (13 mbsl) and 7700-8100 cal yr BP (6 mbsl).

Sea ice information has traditionally been associated with Manual Ice Charts, however the demand for accurate forecasts is increasing. This study presents an improved operational forecast system for the Arctic sea ice focusing on the Greenlandic waters. In addition, we present different observational sea ice products and conduct inter-comparisons. First, a re-analysis forced by ERA5 from 2000 to 2021 is evaluated to ensure that the forecast system is stable over time and to provide statistics for the users. The output is similar to the initial conditions for a forecast. Secondly, the sea ice forecast system is tested and evaluated based on two re-forecasts forced by the high resolution ECMWF-HRES forecast for the period from January 2019 to September 2021. Both the re-analysis and the re-forecasts include assimilation of sea surface temperatures and sea ice concentrations. We validate the re-analysis and the re-forecast systems for sea ice concentration against different remotely sensed observational products by computing the Integrated Ice Edge Error metric at the initial conditions of each system. The results reveal that the re-analysis and the re-forecast perform well. However, the summertime retreat of sea ice near the western Greenlandic coast seems to be delayed a few days compared with the observations. Importantly, part of the bias associated with the model representation of the sea ice edge is associated with the observational errors due to limitations in the passive microwave product in summertime and also near the coast. An inter-comparison of the observational sea ice products suggests that the model performance could be improved by assimilation of sea ice concentrations derived from a newly-developed automated sea ice product. In addition, analysis of persistence shows that the re-forecast has better skill than the persistence forecast for the vast majority of the time.

Low Sea Surface Temperature (SST) is a climate barrier because it may inhibit and reduce seedling growth of mangrove propagules upon dispersal through seawater. Our objective is to analyze the spatio-temporal series of daily SST data from the Multi-scale Ultra-high Resolution (MUR)-SST in order to identify the occurrence of chilling events for mangrove plants at the Eastern South America mangrove limit and beyond. We focus our study on three key sites: (i) the Rhizophora mangle L. distribution limit (Praia do Sonho: 27°53′S), (ii) the Eastern South America mangrove limit (Laguna: 28°30′S) and (iii) one beyond mangrove areas, in Araranguá (28°55′S). Our results show that, in Araranguá, chilling events are more intense and occur more frequently than in the other two sites that have a mangrove cover. We conclude that, the chilling events of SST may play a role in restricting mangroves within their actual limits. In this sense, higher occurrences of chilling events of SST could be an explanation for the absence of R. mangle in Laguna. However, Laguncularia racemosa (L.) C.F. Gaertn. was reported to be tolerant to low temperatures, and yet it is absent from the southernmost study site. This may be an indication of the role of other factors than SST in determining a mangrove range expansion, such as dispersal constraints.