Description: This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations that are obtained following the OMIP-2 protocol (Griffies et al., 2016) and integrated for one cycle (1958–2018) of the JRA55-do atmospheric state and runoff dataset (Tsujino et al., 2018). Our goal is to assess the robustness of climate-relevant improvements in ocean simulations (mean and variability) associated with moving from coarse (∼ 1∘) to eddy-resolving (∼ 0.1∘) horizontal resolutions. The models are diverse in their numerics and parameterizations, but each low-resolution and high-resolution pair of models is matched so as to isolate, to the extent possible, the effects of horizontal resolution. A variety of observational datasets are used to assess the fidelity of simulated temperature and salinity, sea surface height, kinetic energy, heat and volume transports, and sea ice distribution. This paper provides a crucial benchmark for future studies comparing and improving different schemes in any of the models used in this study or similar ones. The biases in the low-resolution simulations are familiar, and their gross features – position, strength, and variability of western boundary currents, equatorial currents, and the Antarctic Circumpolar Current – are significantly improved in the high-resolution models. However, despite the fact that the high-resolution models “resolve” most of these features, the improvements in temperature and salinity are inconsistent among the different model families, and some regions show increased bias over their low-resolution counterparts. Greatly enhanced horizontal resolution does not deliver unambiguous bias improvement in all regions for all models.

Description: The evaluation and model element description of the second version of the unstructured-mesh Finite-volumE Sea ice-Ocean Model (FESOM2.0) are presented. The new version of the model takes advantage of the finite-volume approach, whereas its predecessor version, FESOM1.4 was based on the finite-element approach. The model sensitivity to arbitrary Lagrangian–Eulerian (ALE) linear and nonlinear free-surface formulation, Gent–McWilliams eddy parameterization, isoneutral Redi diffusion and different vertical mixing schemes is documented. The hydrographic biases, large-scale circulation, numerical performance and scalability of FESOM2.0 are compared with its predecessor, FESOM1.4. FESOM2.0 shows biases with a magnitude comparable to FESOM1.4 and simulates a more realistic Atlantic meridional overturning circulation (AMOC). Compared to its predecessor, FESOM2.0 provides clearly defined fluxes and a 3 times higher throughput in terms of simulated years per day (SYPD). It is thus the first mature global unstructured-mesh ocean model with computational efficiency comparable to state-of-the-art structured-mesh ocean models. Other key elements of the model and new development will be described in follow-up papers.

Description: We present a new framework for global ocean–sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean–sea-ice models (JRA55-do). We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean–ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean–sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80 % of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP-2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP-2. For example, the sea surface temperatures of the OMIP-2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating process-level responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean–sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework.

Description: Disintegration of ice shelves in the Amundsen Sea, in front of the West Antarctic Ice Sheet, has the potential to cause sea level rise by inducing an acceleration of ice discharge from upstream grounded ice. Moore et al. (2018) proposed that using a submarine wall to block the penetration of warm water into the subsurface cavities of these ice shelves could reduce this risk. We use a global sea ice–ocean model to show that a wall shielding the Amundsen Sea below 350 m depth successfully suppresses the inflow of warm water and reduces ice shelf melting. However, these warm water masses get redirected towards neighboring ice shelves, which reduces the net effectiveness of the wall. The ice loss is reduced by 10 %, integrated over the entire Antarctic continent.

Description: Recently, it has been shown that under pressure, unexpected and counterintuitive chemical compounds become stable. Laser shock experiments (A. Rode, unpublished) on alumina (Al2O3) have shown non-equilibrium decomposition of alumina with the formation of free Al and a mysterious transparent phase. Inspired by these observations, we have explored the possibility of the formation of new chemical compounds in the system Al-O. Using the variable-composition structure prediction algorithm USPEX, in addition to the well-known Al2O3, we have found two extraordinary compounds Al4O7 and AlO2 to be thermodynamically stable in the pressure ranges 330-443 GPa and above 332 GPa, respectively. Both of these compounds at the same time contain oxide O2− and peroxide O22− ions, and both are insulating. Peroxo-groups are responsible for gap states, which significantly reduce the electronic band gap of both Al4O7 and AlO2. Scientific Reports 5 doi: 10.1038/srep09518

Description: Cell-in-cell structures (CICs), characterized by the presence of one or more viable cells inside another one, were recently found important player in development, immune homeostasis and tumorigenesis etc. Incompatible with ever-increasing interests on this unique phenomenon, reliable methods available for high throughput quantification and systemic investigation are lacking. Here, we report a flow cytometry-based method for rapid analysis and sorting of heterotypic CICs formed between lymphocytes and tumor cells. In this method, cells were labeled with fluorescent dyes for fluorescence-activated cell sorting (FACS) by flow cytometry, conditions for reducing cell doublets were optimized such that high purity (〉95%) of CICs could be achieved. By taking advantage of this method, we analyzed CICs formation between different cell pairs, and found that factors from both internalized effector cells and engulfing target cells affect heterotypic CICs formation. Thus, flow cytometry-based FACS analysis would serve as a high throughput method to promote systemic researches on CICs. Scientific Reports 5 doi: 10.1038/srep09588

Description: We aimed to exploit novel compounds with high selectivity to clear cell renal cell carcinoma (ccRCC) with common mutations. Using the GDSC databases, we searched for compounds with high selectivity for ccRCC with VHL and/or SETD2 mutations. Clinical impact and gene interactions were analysed using TCGA database. In vitro and in vivo studies were performed to validate the inhibitory effects of the compound. We identified the selective PI3Kβ inhibitor TGX221 as a selective inhibitor for ccRCC with both VHL and SETD2 mutations. TGX221 also targeted cancer cells with CDKN2A and PTEN mutations. Changes in PTEN and CDKN2A gene sets were associated with worsened prognosis of ccRCC. TGX221 substantially and selectively inhibited the down stream products of VHL, SETD2, and PTEN in ccRCC cells with VHL and SETD2 mutations. TGX221 also exhibited significant selectivity in inhibiting cell motility and tumourigenesis of ccRCC cells with VHL and SETD2 mutations. TGX221 is a novel inhibitor with high selectivity for ccRCC with VHL and SETD2 mutations. It also targeted PTEN and CDKN2A mutations. How those genes were associated with PI3Kβ warranted further investigations. Scientific Reports 5 doi: 10.1038/srep09465