OASIS: a coupling software for next generation earth system modelling

In this article we present a new version of the Ocean Atmosphere Sea Ice Soil coupling software (OASIS4). With this new fully parallel OASIS4 coupler we target the needs of Earth system modelling in its full complexity. The primary focus of this article is to describe the design of the OASIS4 software and how the coupling software drives the whole coupled model system ensuring the synchronization of the different component models. The application programmer interface (API) manages the coupling exchanges between arbitrary climate component models, as well as the input and output from and to files of each individual component. The OASIS4 Transformer instance performs the parallel interpolation and transfer of the coupling data between source and target model components. As a new core technology for the software, the fully parallel search algorithm of OASIS4 is described in detail. First benchmark results are discussed with simple test configurations to demonstrate the efficiency and scalability of the software when applied to Earth system model components. Typically the compute time needed to perform the search is in the order of a few seconds and is only weakly dependant on the grid size

Quantifying Arctic contributions to climate predictability in a regional coupled ocean-ice-atmosphere model

The relative importance of regional processes inside the Arctic climate system and the large scale atmospheric circulation for Arctic interannual climate variability has been estimated with the help of a regional Arctic coupled ocean-ice-atmosphere model. The study focuses on sea ice and surface climate during the 1980s and 1990s. Simulations agree reasonably well with observations. Correlations between the winter North Atlantic Oscillation index and the summer Arctic sea ice thickness and summer sea ice extent are found. Spread of sea ice extent within an ensemble of model runs can be associated with a surface pressure gradient between the Nordic Seas and the Kara Sea. Trends in the sea ice thickness field are widely significant and can formally be attributed to large scale forcing outside the Arctic model domain. Concerning predictability, results indicate that the variability generated by the external forcing is more important in most regions than the internally generated variability. However, both are in the same order of magnitude. Local areas such as the Northern Greenland coast together with Fram Straits and parts of the Greenland Sea show a strong importance of internally generated variability, which is associated with wind direction variability due to interaction with atmospheric dynamics on the Greenland ice sheet. High predictability of sea ice extent is supported by north-easterly winds from the Arctic Ocean to Scandinavia

Early development and tuning of a global coupled cloud resolving model, and its fast response to increasing CO2

Since the dawn of functioning numerical dynamical atmosphere- and ocean models, their resolution has steadily increased, fed by an exponential growth in computational capabilities. However, because resolution of models is at all times limited by computational power a number of mostly small-scale or micro-scale processes have to be parameterised. Particularly those of atmospheric moist convection and ocean eddies are problematic when scientists seek to interpret output from model experiments. Here we present the first coupled ocean-atmosphere model experiments with sufficient resolution to dispose of moist convection and ocean eddy parameterisations. We describe the early development and discuss the challenges associated with conducting the simulations with a focus on tuning the global mean radiation balance in order to limit drifts. A four-month experiment with quadrupled CO2 is then compared with a ten-member ensemble of low-resolution simulations using MPI-ESM1.2-LR. We find broad similarities of the response, albeit with a more diversified spatial pattern with both stronger and weaker regional warming, as well as a sharpening of precipitation in the inter tropical convergence zone. These early results demonstrate that it is already now possible to learn from such coupled model experiments, even if short by nature

Genome-wide meta-analysis in alopecia areata resolves HLA associations and reveals two new susceptibility loci

Alopecia areata (AA) is a prevalent autoimmune disease with 10 known susceptibility loci. Here we perform the first meta-analysis of research on AA by combining data from two genome-wide association studies (GWAS), and replication with supplemented ImmunoChip data for a total of 3,253 cases and 7,543 controls. The strongest region of association is the major histocompatibility complex, where we fine-map four independent effects, all implicating human leukocyte antigen-DR as a key aetiologic driver. Outside the major histocompatibility complex, we identify two novel loci that exceed the threshold of statistical significance, containing ACOXL/BCL2L11(BIM) (2q13); GARP (LRRC32) (11q13.5), as well as a third nominally significant region SH2B3(LNK)/ATXN2 (12q24.12). Candidate susceptibility gene expression analysis in these regions demonstrates expression in relevant immune cells and the hair follicle. We integrate our results with data from seven other autoimmune diseases and provide insight into the alignment of AA within these disorders. Our findings uncover new molecular pathways disrupted in AA, including autophagy/apoptosis, transforming growth factor beta/Tregs and JAK kinase signalling, and support the causal role of aberrant immune processes in AA

Segond's fracture: a biomechanical cadaveric study using navigation

Background Segond’s fracture is a well-recognised radiological sign of an anterior cruciate ligament (ACL) tear. While previous studies evaluated the role of the anterolateral ligament (ALL) and complex injuries on rotational stability of the knee, there are no studies on the biomechanical effect of Segond’s fracture in an ACL deficient knee. The aim of this study was to evaluate the effect of a Segond’s fracture on knee rotation stability as evaluated by a navigation system in an ACL deficient knee. Materials and methods Three different conditions were tested on seven knee specimens: intact knee, ACL deficient knee and ACL deficient knee with Segond’s fracture. Static and dynamic measurements of anterior tibial translation (ATT) and axial tibial rotation (ATR) were recorded by the navigation system (2.2 OrthoPilot ACL navigation system B. Braun Aesculap, Tuttlingen, Germany). Results Static measurements at 30 showed that the mean ATT at 30 of knee flexion was 5.1 ± 2.7 mm in the ACL intact condition, 14.3 ± 3.1 mm after ACL cut (P = 0.005), and 15.2 ± 3.6 mm after Segond’s fracture (P = 0.08). The mean ATR at 30 of knee flexion was 20.7 ± 4.8 in the ACL intact condition, 26.9 ± 4.1 in the ACL deficient knee (P[0.05) and 30.9 ± 3.8 after Segond’s fracture (P = 0.005). Dynamic measurements during the pivot-shift showed that the mean ATT was 7.2 ± 2.7 mm in the intact knee, 9.1 ± 3.3 mm in the ACL deficient knee(P = 0.04) and 9.7 ± 4.3 mm in the ACL deficient knee with Segond’s fracture (P = 0.07). The mean ATR was 9.6 ± 1.8 in the intact knee, 12.3 ± 2.3 in the ACL deficient knee (P[0.05) and 19.1 ± 3.1 in the ACL deficient knee with Segond’s lesion (P = 0.016). Conclusion An isolated lesion of the ACL only affects ATT during static and dynamic measurements, while the addition of Segond’s fracture has a significant effect on ATR in both static and dynamic execution of the pivot-shift test, as evaluated with the aid of navigation