ALBERT

Description: Abstract Multi‐model Arctic Ocean ``Climate Response Function” (CRF) experiments are analyzed in order to explore the effects of anomalous wind forcing over the Greenland Sea (GS) on poleward ocean heat transport, Atlantic Water (AW) pathways, and the extent of Arctic sea ice. Particular emphasis is placed on the sensitivity of the AW circulation to anomalously strong or weak GS winds in relation to natural variability, the latter manifested as part of the North Atlantic Oscillation (NAO). We find that anomalously strong (weak) GS wind forcing, comparable in strength to a strong positive (negative) NAO index, results in an intensification (weakening) of the poleward AW flow, extending from south of the North Atlantic Subpolar Gyre, through the Nordic Seas, and all the way into the Canadian Basin. Reconstructions made utilizing the calculated CRFs explain ~50 % of the simulated AW flow variance; this is the proportion of variability that can be explained by GS wind forcing. In the Barents and Kara Seas there is a clear relationship between the wind‐driven anomalous AW inflow and the sea ice extent. Most of the anomalous AW heat is lost to the atmosphere, and loss of sea ice in the Barents Sea results in even more heat loss to the atmosphere, and thus effective ocean cooling. Release of passive tracers in a subset of the suite of models reveals differences in circulation patterns and shows that the flow of AW in the Arctic Ocean is highly dependent on the wind stress in the Nordic Seas.

Description: Supernova (SN) blast waves inject energy and momentum into the interstellar medium (ISM), control its turbulent multiphase structure and the launching of galactic outflows. Accurate modelling of the blast wave evolution is therefore essential for ISM and galaxy formation simulations. We present an efficient method to compute the input of momentum, thermal energy, and the velocity distribution of the shock-accelerated gas for ambient media (densities of 0.1 ≥ n 0 [cm – 3 ] ≥ 100) with uniform (and with stellar wind blown bubbles), power-law, and turbulent (Mach numbers $\mathcal {M}$ from 1to100) density distributions. Assuming solar metallicity cooling, the blast wave evolution is followed to the beginning of the momentum conserving snowplough phase. The model recovers previous results for uniform ambient media. The momentum injection in wind-blown bubbles depend on the swept-up mass and the efficiency of cooling, when the blast wave hits the wind shell. For power-law density distributions with n ( r ) ~  r –2 (for n ( r ) 〉  n floor ) the amount of momentum injection is solely regulated by the background density n floor and compares to n uni = n floor . However, in turbulent ambient media with lognormal density distributions the momentum input can increase by a factor of 2 (compared to the homogeneous case) for high Mach numbers. The average momentum boost can be approximated as $p_{{\rm turb}}/{p_{{0}}}\ =23.07\, \left(\frac{n_{{0,\rm turb}}}{1\,{\rm cm}^{-3}}\right)^{-0.12} + 0.82 (\ln (1+b^{2}\mathcal {M}^{2}))^{1.49}\left(\frac{n_{{0,\rm turb}}}{1\,{\rm cm}^{-3}}\right)^{-1.6}$ . The velocity distributions are broad as gas can be accelerated to high velocities in low-density channels. The model values agree with results from recent, computationally expensive, three-dimensional simulations of SN explosions in turbulent media.

Description: Sample entropy (SaEn) applied on center-of-pressure (COP) data provides a measure for the regularity of human postural control. Two mechanisms could contribute to altered COP regularity: first, an altered temporal structure (temporal regularity) of postural movements (H1); or second, altered coordination between segment movements (coordinative complexity; H2). The current study used rapid, voluntary head-shaking to perturb the postural control system, thus producing changes in COP regularity, to then assess the two hypotheses. Sixteen healthy participants (age 26.5 ± 3.5; seven females), whose postural movements were tracked via 39 reflective markers, performed trials in which they first stood quietly on a force plate for 30 s, then shook their head for 10 s, finally stood quietly for another 90 s. A principal component analysis (PCA) performed on the kinematic data extracted the main postural movement components. Temporal regularity was determined by calculating SaEn on the time series of these movement components. Coordinative complexity was determined by assessing the relative explained variance of the first five components. H1 was supported, but H2 was not. These results suggest that moderate perturbations of the postural control system produce altered temporal structures of the main postural movement components, but do not necessarily change the coordinative structure of intersegment movements.

Description: We use hydrodynamical simulations in a (256 pc) 3 periodic box to model the impact of supernova (SN) explosions on the multiphase interstellar medium (ISM) for initial densities n  = 0.5–30 cm –3 and SN rates 1–720 Myr –1 . We include radiative cooling, diffuse heating, and the formation of molecular gas using a chemical network. The SNe explode either at random positions, at density peaks, or both. We further present a model combining thermal energy for resolved and momentum input for unresolved SNe. Random driving at high SN rates results in hot gas ( T   10 6  K) filling 〉90 per cent of the volume. This gas reaches high pressures (10 4  〈  P / k B  〈 10 7  K cm –3 ) due to the combination of SN explosions in the hot, low-density medium and confinement in the periodic box. These pressures move the gas from a two-phase equilibrium to the single-phase, cold branch of the cooling curve. The molecular hydrogen dominates the mass (〉50 per cent), residing in small, dense clumps. Such a model might resemble the dense ISM in high-redshift galaxies. Peak driving results in huge radiative losses, producing a filamentary ISM with virtually no hot gas, and a small molecular hydrogen mass fraction (〈〈1 per cent). Varying the ratio of peak to random SNe yields ISM properties in between the two extremes, with a sharp transition for equal contributions. The velocity dispersion in H i remains 10 km s –1 in all cases. For peak driving, the velocity dispersion in Hα can be as high as 70 km s –1 due to the contribution from young, embedded SN remnants.

Description: Postural control research suggests a non-linear, n-shaped relationship between dual-tasking and postural stability. Nevertheless, the extent of this relationship remains unclear. Since kinematic principal component analysis has offered novel approaches to study the control of movement components (PM) and n-shapes have been found in measures of sway irregularity, we hypothesized (H1) that the irregularity of PMs and their respective control, and the control tightness will display the n-shape. Furthermore, according to the minimal intervention principle (H2) different PMs should be affected differently. Finally, (H3) we expected stronger dual-tasking effects in the older population, due to limited cognitive resources. We measured the kinematics of forty-one healthy volunteers (23 aged 26 ± 3; 18 aged 59 ± 4) performing 80 s tandem stances in five conditions (single-task and auditory n-back task; n = 1–4), and computed sample entropies on PM time-series and two novel measures of control tightness. In the PM most critical for stability, the control tightness decreased steadily, and in contrast to H3, decreased further for the younger group. Nevertheless, we found n-shapes in most variables with differing magnitudes, supporting H1 and H2. These results suggest that the control tightness might deteriorate steadily with increased cognitive load in critical movements despite the otherwise eminent n-shaped relationship.

Description: [1]  Coastal polynyas are areas in an ice-covered ocean where the ice cover is exported, mostly by off-shore winds. The resulting reduction of sea ice enables an enhanced ocean–atmosphere heat transfer. Once the water temperatures are at the freezing point, further heat loss induces sea ice production. The heat exchange and ice production in coastal polynyas in the southwestern Weddell Sea is addressed using the Finite-Element Sea-ice Ocean Model, a primitive-equation, hydrostatic ocean circulation model coupled with a dynamicthermodynamic sea-ice model, which allows to quantify the amount of heat associated with cooling of the water column. Three important polynya regions are identified: at Brunt Ice Shelf, at Ronne Ice Shelf and along the southern part of the Antarctic Peninsula. Multiyear winter means (May-September 1990–2009) give an upward heat flux to the atmosphere of 311 W/m 2 in the Brunt polynyas, 511 W/m 2 in Ronne Polynya and 364 W/m 2 in the Antarctic Peninsula polynyas, whereof 57 W/m 2 , 49 W/m 2 and 48 W/m 2 , respectively, are supplied as oceanic heat flux from deeper layers. The mean winter sea ice production is 7.2 cm/d in the Brunt polynyas corresponding to an ice volume of 1.3 · 10 10   m 3 /winter, 13.2 cm/d at Ronne polynya (4.4 · 10 10   m 3 /winter), and 9.2 cm/d in the Antarctic Peninsula polynyas (2.1 · 10 10   m 3 /winter. The heat flux to the atmosphere inside polynyas is 7 to 9 times higher than the heat flux in the adjacent area; polynya ice production per unit area exceeds adjacent values by a factor of 9 to 14.

Description: [1]  This study deals with observations and simulations of the evolution of coastal polynias focusing on the Ronne Polynia. We compare differences in polynia extent and ice drift patterns derived from satellite radar images and from simulations with the Finite Element Sea ice Ocean Model (FESOM), employing three atmospheric forcing data sets that differ in spatial and temporal resolution. Two polynia events are analysed, one from austral summer and one from late fall 2008. The open water area in the polynia is of similar size in the satellite images and in the model simulations, but its temporal evolution differs depending on katabatic winds being resolved in the atmospheric forcing data sets. Modelled ice drift is slower than the observed and reveals greater turning angles relative to the wind direction in many cases. For the summer event, model results obtained with high-resolution forcing are closer to the drift field derived from radar imagery than those from coarse-resolution forcing. For the late-fall event, none of the forcing data yields outstanding results. Our study demonstrates that a dense (1-3 km) model grid and atmospheric forcing provided at high spatial resolution (〈50 km) are critical to correctly simulate coastal polynias with a coupled sea-ice ocean model.

Description: We analyse the CO-dark molecular gas content of simulated molecular clouds from the SILCC-Zoom project. The simulations reach a resolution of 0.1 pc and include H2 and CO formation, radiative stellar feedback and magnetic fields. CO-dark gas is found in regions with local visual extinctions $A_ m {V, 3D} sim$ 0.2–1.5, number densities of 10–103 cm−3 and gas temperatures of few 10–100 K. CO-bright gas is found at number densities above 300 cm−3 and temperatures below 50 K. The CO-dark gas fractions range from 40 per cent to 95 per cent and scale inversely with the amount of well-shielded gas ($A_ m {V, 3D}$ ≳ 1.5), which is smaller in magnetized molecular clouds. We show that the density, chemical abundances and $A_ m {V, 3D}$ along a given line-of-sight cannot be properly determined from projected quantities. As an example, pixels with a projected visual extinction of $A_ m {V, 2D} simeq$ 2.5–5 can be both, CO-bright or CO-dark, which can be attributed to the presence or absence of strong density enhancements along the line-of-sight. By producing synthetic CO(1-0) emission maps of the simulations with RADMC-3D, we show that about 15–65 per cent of the H2 is in regions with intensities below the detection limit. Our clouds have $X_ m {CO}$-factors around 1.5 × 1020 cm−2 (K km s−1)−1 with a spread of up to a factor ∼ 4, implying a similar uncertainty in the derived total H2 masses and even worse for individual pixels. Based on our results, we suggest a new approach to determine the H2 mass, which relies on the availability of CO(1-0) emission and $A_ m {V, 2D}$ maps. It reduces the uncertainty of the clouds’ overall H2 mass to a factor of ≲ 1.8 and for individual pixels, i.e. on sub-pc scales, to a factor of ≲ 3.