ALBERT

Description: For several decades, theory and research has drawn links between dopaminergic neurotransmission and various aspects of personality and individual differences, as well as major personality processes. Recent increases in the availability and affordability of neuroscience methods have permitted thorough investigation of such links as part of the thriving field of personality neuroscience. However, the picture emerging from this body of research is somewhat puzzling; Rather than being linked to only a few converging dimensions of individual differences in psychological functioning, dopamine seems to be associated with a wide range of rather disparate traits and psychopathological conditions including (among various others) impulsivity, extraversion, anxiety, reward sensitivity, approach behaviour, achievement motivation, working memory performance, cognitive flexibility, depression, anhedonia, attention deficit hyperactivity disorder (ADHD), and schizophrenia. Empirical research in this area typically focuses on only one piece of this puzzle based on a specific strand of theory and a narrow section of relevant prior findings. The present research topic will, for the first time, attempt to provide a fairly complete picture of the whole puzzle including all its disparate parts. Contributors will therefore be explicitly encouraged to go beyond their own specific dopamine-personality hypotheses and place their work in a broader context, thereby helping to forge links between largely non-overlapping research traditions.

Description: Statistical models of the variability of plasma in the topside ionosphere based on the Swarm data have been developed in the “Swarm Variability of Ionospheric Plasma” (Swarm-VIP) project within the European Space Agency’s Swarm+4D-Ionosphere framework. The models can predict the electron density, its gradients for three horizontal spatial scales – 20, 50 and 100 km – along the North-South direction and the level of the density fluctuations. Despite being developed by leveraging on Swarm data, the models provide predictions that are independent of these data, having a global coverage, fed by various parameters and proxies of the helio-geophysical conditions. Those features make the Swarm-VIP models useful for various purposes, which include the possible support for already available ionospheric models and proxy of the effect of ionospheric irregularities of the medium scales that affect the signals emitted by Global Navigation Satellite Systems (GNSS). The formulation, optimisation and validation of the Swarm-VIP models are reported in Paper 1 (Wood et al. 2024. J Space Weather Space Clim. in press). This paper describes the performance assessment of the models, by addressing their capability to reproduce the known climatological variability of the modelled quantities, and the ionospheric weather as depicted by ground-based GNSS, as a proxy for the ionospheric effect on GNSS signals. Additionally, we demonstrate that, under certain conditions, the model can better reproduce the ionospheric variability than a physics-based model, namely the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIE-GCM).

Description: Published

Description: 4

Description: OSA3: Climatologia e meteorologia spaziale

Description: JCR Journal

Description: The Antarctic Ice Sheet represents the largest source of uncertainty in future sea level rise projections, with a contribution to sea level by 2100 ranging from −5 to 43 cm of sea level equivalent under high carbon emission scenarios estimated by the recent Ice Sheet Model Intercomparison for CMIP6 (ISMIP6). ISMIP6 highlighted the different behaviors of the East and West Antarctic ice sheets, as well as the possible role of increased surface mass balance in offsetting the dynamic ice loss in response to changing oceanic conditions in ice shelf cavities. However, the detailed contribution of individual glaciers, as well as the partitioning of uncertainty associated with this ensemble, have not yet been investigated. Here, we analyze the ISMIP6 results for high carbon emission scenarios, focusing on key glaciers around the Antarctic Ice Sheet, and we quantify their projected dynamic mass loss, defined here as mass loss through increased ice discharge into the ocean in response to changing oceanic conditions. We highlight glaciers contributing the most to sea level rise, as well as their vulnerability to changes in oceanic conditions. We then investigate the different sources of uncertainty and their relative role in projections, for the entire continent and for key individual glaciers. We show that, in addition to Thwaites and Pine Island glaciers in West Antarctica, Totten and Moscow University glaciers in East Antarctica present comparable future dynamic mass loss and high sensitivity to ice shelf basal melt. The overall uncertainty in additional dynamic mass loss in response to changing oceanic conditions, compared to a scenario with constant oceanic conditions, is dominated by the choice of ice sheet model, accounting for 52 % of the total uncertainty of the Antarctic dynamic mass loss in 2100. Its relative role for the most dynamic glaciers varies between 14 % for MacAyeal and Whillans ice streams and 56 % for Pine Island Glacier at the end of the century. The uncertainty associated with the choice of climate model increases over time and reaches 13 % of the uncertainty by 2100 for the Antarctic Ice Sheet but varies between 4 % for Thwaites Glacier and 53 % for Whillans Ice Stream. The uncertainty associated with the ice–climate interaction, which captures different treatments of oceanic forcings such as the choice of melt parameterization, its calibration, and simulated ice shelf geometries, accounts for 22 % of the uncertainty at the ice sheet scale but reaches 36 % and 39 % for Institute Ice Stream and Thwaites Glacier, respectively, by 2100. Overall, this study helps inform future research by highlighting the sectors of the ice sheet most vulnerable to oceanic warming over the 21st century and by quantifying the main sources of uncertainty.

Description: Ice flow models of the Antarctic ice sheet are commonly used to simulate its future evolution in response to different climate scenarios and inform on the mass loss that would contribute to future sea level rise. However, there is currently no consensus on estimated the future mass balance of the ice sheet, primarily because of differences in the representation of physical processes and the forcings employed. This study presents results from 18 simulations from 15 international groups focusing on the evolution of the Antarctic ice sheet during the period 2015–2100, forced with different scenarios from the Coupled Model Intercomparison Project Phase 5 (CMIP5) representative of the spread in climate model results. The contribution of the Antarctic ice sheet in response to increased warming during this period varies between −7.8 and 30.0 cm of Sea Level Equivalent (SLE). The evolution of the West Antarctic Ice Sheet varies widely among models, with an overall mass loss up to 21.0 cm SLE in response to changes in oceanic conditions. East Antarctica mass change varies between −6.5 and 16.5 cm SLE, with a significant increase in surface mass balance outweighing the increased ice discharge under most RCP 8.5 scenario forcings. The inclusion of ice shelf collapse, here assumed to be caused by large amounts of liquid water ponding at the surface of ice shelves, yields an additional mass loss of 8 mm compared to simulations without ice shelf collapse. The largest sources of uncertainty come from the ocean-induced melt rates, the calibration of these melt rates based on oceanic conditions taken outside of ice shelf cavities and the ice sheet dynamic response to these oceanic changes. Results under RCP 2.6 scenario based on two CMIP5 AOGCMs show an overall mass loss of 10 mm SLE compared to simulations done under present-day conditions, with limited mass gain in East Antarctica.

Description: The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2,3,4,5,6,7,8, but primarily used previous-generation scenarios9 and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12 using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.