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  • 1
    Online Resource
    Online Resource
    ACCESS-OM2 v1.0: a global ocean–sea ice model at three resolutions
    Copernicus GmbH ; 2020
    In:  Geoscientific Model Development Vol. 13, No. 2 ( 2020-02-05), p. 401-442
    Details
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 13, No. 2 ( 2020-02-05), p. 401-442
    Abstract: Abstract. We introduce ACCESS-OM2, a new version of the ocean–sea ice model of the Australian Community Climate and Earth System Simulator. ACCESS-OM2 is driven by a prescribed atmosphere (JRA55-do) but has been designed to form the ocean–sea ice component of the fully coupled (atmosphere–land–ocean–sea ice) ACCESS-CM2 model. Importantly, the model is available at three different horizontal resolutions: a coarse resolution (nominally 1∘ horizontal grid spacing), an eddy-permitting resolution (nominally 0.25∘), and an eddy-rich resolution (0.1∘ with 75 vertical levels); the eddy-rich model is designed to be incorporated into the Bluelink operational ocean prediction and reanalysis system. The different resolutions have been developed simultaneously, both to allow for testing at lower resolutions and to permit comparison across resolutions. In this paper, the model is introduced and the individual components are documented. The model performance is evaluated across the three different resolutions, highlighting the relative advantages and disadvantages of running ocean–sea ice models at higher resolution. We find that higher resolution is an advantage in resolving flow through small straits, the structure of western boundary currents, and the abyssal overturning cell but that there is scope for improvements in sub-grid-scale parameterizations at the highest resolution.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    URL: Article
    URL: Article
    DOI: 10.5194/gmd-13-401-2020
    DOI: 10.5194/gmd-13-401-2020-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2020
    detail.hit.zdb_id: 2456725-5
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  • 2
    Online Resource
    Online Resource
    CAFE60v1: A 60-year large ensemble climate reanalysis. Part I: System design, model configuration and data assimilation.
    American Meteorological Society ; 2021
    In:  Journal of Climate ( 2021-03-22), p. 1-48
    Details
    In: Journal of Climate, American Meteorological Society, ( 2021-03-22), p. 1-48
    Abstract: We detail the system design, model configuration and data assimilation evaluation for the CSIRO Climate retrospective Analysis and Forecast Ensemble system: version 1. CAFE60v1 has been designed with the intention of simultaneously generating both initial conditions for multi-year climate forecasts and a large ensemble retrospective analysis of the global climate system from 1960 to present. Strongly coupled data assimilation (SCDA) is implemented via an ensemble transform Kalman filter in order to constrain a general circulation climate model to observations. Satellite (altimetry, sea surface temperature, sea ice concentration) and in-situ ocean temperature and salinity profiles are directly assimilated each month, whereas atmospheric observations are sub-sampled from the JRA-55 atmospheric reanalysis. Strong coupling is implemented via explicit cross domain covariances between ocean, atmosphere, sea ice and ocean biogeochemistry. Atmospheric and surface ocean fields are available at daily resolution and monthly resolution for the land, subsurface ocean and sea ice. The system produces 96 climate trajectories (state estimates) over the most recent six decades as well as a complete data archive of initial conditions potentially enabling individual forecasts for all members each month over the 60 year period. The size of the ensemble and application of strongly coupled data assimilation lead to new insights for future reanalyses.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    URL: Article
    DOI: 10.1175/JCLI-D-20-0974.1
    DOI: 10.1175/JCLI-D-20-0974.s1
    RVK:
    UA 4548
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2021
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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    Online Resource
  • 3
    Online Resource
    Online Resource
    Exosome-educated macrophages and exosomes differentially improve ligament healing
    Oxford University Press (OUP) ; 2021
    In:  Stem Cells Vol. 39, No. 1 ( 2021-01-01), p. 55-61
    Details
    In: Stem Cells, Oxford University Press (OUP), Vol. 39, No. 1 ( 2021-01-01), p. 55-61
    Abstract: Recently, our group used exosomes from mesenchymal stromal/stem cells (MSCs) to simulate an M2 macrophage phenotype, that is, exosome-educated macrophages (EEMs). These EEMs, when delivered in vivo, accelerated healing in a mouse Achilles tendon injury model. For the current study, we first tested the ability of EEMs to reproduce the beneficial healing effects in a different rodent model, that is, a rat medial collateral ligament (MCL) injury model. We hypothesized that treatment with EEMs would reduce inflammation and accelerate ligament healing, similar to our previous tendon results. Second, because of the translational advantages of a cell-free therapy, exosomes alone were also examined to promote MCL healing. We hypothesized that MSC-derived exosomes could also alter ligament healing to reduce scar formation. Similar to our previous Achilles tendon results, EEMs improved mechanical properties in the healing ligament and reduced inflammation, as indicated via a decreased endogenous M1/M2 macrophage ratio. We also showed that exosomes improved ligament remodeling as indicated by changes in collagen production and organization, and reduced scar formation but without improved mechanical behavior in healing tissue. Overall, our findings suggest EEMs and MSC-derived exosomes improve healing but via different mechanisms. EEMs and exosomes each have attractive characteristics as therapeutics. EEMs as a cell therapy are terminally differentiated and will not proliferate or differentiate. Alternatively, exosome therapy can be used as a cell free, shelf-stable therapeutic to deliver biologically active components. Results herein further support using EEMs and/or exosomes to improve ligament healing by modulating inflammation and promoting more advantageous tissue remodeling.
    Type of Medium: Online Resource
    ISSN: 1066-5099 , 1549-4918
    URL: Article
    DOI: 10.1002/stem.3291
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2030643-X
    detail.hit.zdb_id: 1143556-2
    detail.hit.zdb_id: 605570-9
    SSG: 12
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  • 4
    Online Resource
    Online Resource
    Coupled Data Assimilation and Ensemble Initialization with Application to Multiyear ENSO Prediction
    American Meteorological Society ; 2019
    In:  Journal of Climate Vol. 32, No. 4 ( 2019-02), p. 997-1024
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 32, No. 4 ( 2019-02), p. 997-1024
    Abstract: We develop and compare variants of coupled data assimilation (DA) systems based on ensemble optimal interpolation (EnOI) and ensemble transform Kalman filter (ETKF) methods. The assimilation system is first tested on a small paradigm model of the coupled tropical–extratropical climate system, then implemented for a coupled general circulation model (GCM). Strongly coupled DA was employed specifically to assess the impact of assimilating ocean observations [sea surface temperature (SST), sea surface height (SSH), and sea surface salinity (SSS), Argo, XBT, CTD, moorings] on the atmospheric state analysis update via the cross-domain error covariances from the coupled-model background ensemble. We examine the relationship between ensemble spread, analysis increments, and forecast skill in multiyear ENSO prediction experiments with a particular focus on the atmospheric response to tropical ocean perturbations. Initial forecast perturbations generated from bred vectors (BVs) project onto disturbances at and below the thermocline with similar structures to ETKF perturbations. BV error growth leads ENSO SST phasing by 6 months whereupon the dominant mechanism communicating tropical ocean variability to the extratropical atmosphere is via tropical convection modulating the Hadley circulation. We find that bred vectors specific to tropical Pacific thermocline variability were the most effective choices for ensemble initialization and ENSO forecasting.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    URL: Article
    DOI: 10.1175/JCLI-D-18-0189.1
    DOI: 10.1175/jcli-d-18-0189.s1
    RVK:
    UA 4548
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2019
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 5
    Online Resource
    Online Resource
    CAFE60v1: A 60-year large ensemble climate reanalysis. Part II: Evaluation
    American Meteorological Society ; 2021
    In:  Journal of Climate ( 2021-03-22), p. 1-62
    Details
    In: Journal of Climate, American Meteorological Society, ( 2021-03-22), p. 1-62
    Abstract: The CSIRO Climate retrospective Analysis and Forecast Ensemble system: version 1 (CAFE60v1) provides a large (96 member) ensemble retrospective analysis of the global climate system from 1960 to present with sufficiently many realizations and at spatio-temporal resolutions suitable to enable probabilistic climate studies. Using a variant of the ensemble Kalman filter, 96 climate state estimates are generated over the most recent six decades. These state estimates are constrained by monthly mean ocean, atmosphere and sea ice observations such that their trajectories track the observed state while enabling estimation of the uncertainties in the approximations to the retrospective mean climate over recent decades. For the atmosphere, we evaluate CAFE60v1 in comparison to empirical indices of the major climate teleconnections and blocking with various reanalysis products. Estimates of the large scale ocean structure, transports and biogeochemistry are compared to those derived from gridded observational products and climate model projections (CMIP). Sea ice (extent, concentration and variability) and land surface (precipitation and surface air temperatures) are also compared to a variety of model and observational products. Our results show that CAFE60v1 is a useful, comprehensive and unique data resource for studying internal climate variability and predictability, including the recent climate response to anthropogenic forcing on multi-year to decadal time scales.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    URL: Article
    DOI: 10.1175/JCLI-D-20-0518.1
    DOI: 10.1175/JCLI-D-20-0518.s1
    RVK:
    UA 4548
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2021
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 6
    Online Resource
    Online Resource
    Extracellular Vesicle-Educated Macrophages Promote Early Achilles Tendon Healing
    Oxford University Press (OUP) ; 2019
    In:  Stem Cells Vol. 37, No. 5 ( 2019-05-01), p. 652-662
    Details
    In: Stem Cells, Oxford University Press (OUP), Vol. 37, No. 5 ( 2019-05-01), p. 652-662
    Abstract: Tendon healing follows a complex series of coordinated events, which ultimately produces a mechanically inferior tissue more scar-like than native tendon. More regenerative healing occurs when anti-inflammatory M2 macrophages play a more dominant role. Mesenchymal stromal/stem cells (MSCs) are able to polarize macrophages to an M2 immunophenotype via paracrine mechanisms. We previously reported that coculture of CD14+ macrophages (MQs) with MSCs resulted in a unique M2-like macrophage. More recently, we generated M2-like macrophages using only extracellular vesicles (EVs) isolated from MSCs creating “EV-educated macrophages” (also called exosome-educated macrophages [EEMs]), thereby foregoing direct use of MSCs. For the current study, we hypothesized that cell therapy with EEMs would improve in vivo tendon healing by modulating tissue inflammation and endogenous macrophage immunophenotypes. We evaluated effects of EEMs using a mouse Achilles tendon rupture model and compared results to normal tendon healing (without any biologic intervention), MSCs, MQs, or EVs. We found that exogenous administration of EEMs directly into the wound promoted a healing response that was significantly more functional and more regenerative. Injured tendons treated with exogenous EEMs exhibited (a) improved mechanical properties, (b) reduced inflammation, and (c) earlier angiogenesis. Treatment with MSC-derived EVs alone were less effective functionally but stimulated a biological response as evidenced by an increased number of endothelial cells and decreased M1/M2 ratio. Because of their regenerative and immunomodulatory effects, EEM treament could provide a novel strategy to promote wound healing in this and various other musculoskeletal injuries or pathologies where inflammation and inadequate healing is problematic. Stem Cells  2019;37:652–662
    Type of Medium: Online Resource
    ISSN: 1066-5099 , 1549-4918
    URL: Article
    DOI: 10.1002/stem.2988
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
    detail.hit.zdb_id: 2030643-X
    detail.hit.zdb_id: 1143556-2
    detail.hit.zdb_id: 605570-9
    SSG: 12
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  • 7
    Online Resource
    Online Resource
    Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models
    Copernicus GmbH ; 2020
    In:  Biogeosciences Vol. 17, No. 16 ( 2020-08-18), p. 4173-4222
    Details
    In: Biogeosciences, Copernicus GmbH, Vol. 17, No. 16 ( 2020-08-18), p. 4173-4222
    Abstract: Abstract. Results from the fully and biogeochemically coupled simulations in which CO2 increases at a rate of 1 % yr−1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon–concentration and carbon–climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent (sixth) Coupled Model Intercomparison Project (CMIP6) and compared with eight models from the fifth CMIP (CMIP5). The strength of the carbon–concentration feedback is of comparable magnitudes over land (mean ± standard deviation = 0.97 ± 0.40 PgC ppm−1) and ocean (0.79 ± 0.07 PgC ppm−1), while the carbon–climate feedback over land (−45.1 ± 50.6 PgC ∘C−1) is about 3 times larger than over ocean (−17.2 ± 5.0 PgC ∘C−1). The strength of both feedbacks is an order of magnitude more uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77 ± 0.37 ∘C EgC−1 and is similar to that found in CMIP5 models (1.63 ± 0.48 ∘C EgC−1) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.
    Type of Medium: Online Resource
    ISSN: 1726-4189
    URL: Article
    URL: Article
    DOI: 10.5194/bg-17-4173-2020
    DOI: 10.5194/bg-17-4173-2020-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2020
    detail.hit.zdb_id: 2158181-2
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  • 8
    Online Resource
    Online Resource
    Combining Argo and Satellite Data Using Model-Derived Covariances: Blue Maps
    Frontiers Media SA ; 2021
    In:  Frontiers in Earth Science Vol. 9 ( 2021-6-17)
    Details
    In: Frontiers in Earth Science, Frontiers Media SA, Vol. 9 ( 2021-6-17)
    Abstract: Blue Maps aims to exploit the versatility of an ensemble data assimilation system to deliver gridded estimates of ocean temperature, salinity, and sea-level with the accuracy of an observation-based product. Weekly maps of ocean properties are produced on a 1/10°, near-global grid by combining Argo profiles and satellite observations using ensemble optimal interpolation (EnOI). EnOI is traditionally applied to ocean models for ocean forecasting or reanalysis, and usually uses an ensemble comprised of anomalies for only one spatiotemporal scale (e.g., mesoscale). Here, we implement EnOI using an ensemble that includes anomalies for multiple space- and time-scales: mesoscale, intraseasonal, seasonal, and interannual. The system produces high-quality analyses that produce mis-fits to observations that compare well to other observation-based products and ocean reanalyses. The accuracy of Blue Maps analyses is assessed by comparing background fields and analyses to observations, before and after each analysis is calculated. Blue Maps produces analyses of sea-level with accuracy of about 4 cm; and analyses of upper-ocean (deep) temperature and salinity with accuracy of about 0.45 (0.15) degrees and 0.1 (0.015) practical salinity units, respectively. We show that the system benefits from a diversity of ensemble members with multiple scales, with different types of ensemble members weighted accordingly in different dynamical regions.
    Type of Medium: Online Resource
    ISSN: 2296-6463
    URL: Article
    DOI: 10.3389/feart.2021.696985
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2741235-0
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  • 9
    Online Resource
    Online Resource
    Ceres lightcurve analysis—Period determination
    Elsevier BV ; 2007
    In:  Icarus Vol. 188, No. 2 ( 2007-6), p. 451-456
    Details
    In: Icarus, Elsevier BV, Vol. 188, No. 2 ( 2007-6), p. 451-456
    Type of Medium: Online Resource
    ISSN: 0019-1035
    URL: Article
    DOI: 10.1016/j.icarus.2006.11.025
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2007
    detail.hit.zdb_id: 1467991-7
    SSG: 16,12
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  • 10
    Online Resource
    Online Resource
    A multi-model CMIP6-PMIP4 study of Arctic sea ice at 127 ka: sea ice data compilation and model differences
    Copernicus GmbH ; 2021
    In:  Climate of the Past Vol. 17, No. 1 ( 2021-01-11), p. 37-62
    Details
    In: Climate of the Past, Copernicus GmbH, Vol. 17, No. 1 ( 2021-01-11), p. 37-62
    Abstract: Abstract. The Last Interglacial period (LIG) is a period with increased summer insolation at high northern latitudes, which results in strong changes in the terrestrial and marine cryosphere. Understanding the mechanisms for this response via climate modelling and comparing the models' representation of climate reconstructions is one of the objectives set up by the Paleoclimate Modelling Intercomparison Project for its contribution to the sixth phase of the Coupled Model Intercomparison Project. Here we analyse the results from 16 climate models in terms of Arctic sea ice. The multi-model mean reduction in minimum sea ice area from the pre industrial period (PI) to the LIG reaches 50 % (multi-model mean LIG area is 3.20×106 km2, compared to 6.46×106 km2 for the PI). On the other hand, there is little change for the maximum sea ice area (which is 15–16×106 km2 for both the PI and the LIG. To evaluate the model results we synthesise LIG sea ice data from marine cores collected in the Arctic Ocean, Nordic Seas and northern North Atlantic. The reconstructions for the northern North Atlantic show year-round ice-free conditions, and most models yield results in agreement with these reconstructions. Model–data disagreement appear for the sites in the Nordic Seas close to Greenland and at the edge of the Arctic Ocean. The northernmost site with good chronology, for which a sea ice concentration larger than 75 % is reconstructed even in summer, discriminates those models which simulate too little sea ice. However, the remaining models appear to simulate too much sea ice over the two sites south of the northernmost one, for which the reconstructed sea ice cover is seasonal. Hence models either underestimate or overestimate sea ice cover for the LIG, and their bias does not appear to be related to their bias for the pre-industrial period. Drivers for the inter-model differences are different phasing of the up and down short-wave anomalies over the Arctic Ocean, which are associated with differences in model albedo; possible cloud property differences, in terms of optical depth; and LIG ocean circulation changes which occur for some, but not all, LIG simulations. Finally, we note that inter-comparisons between the LIG simulations and simulations for future climate with moderate (1 % yr−1) CO2 increase show a relationship between LIG sea ice and sea ice simulated under CO2 increase around the years of doubling CO2. The LIG may therefore yield insight into likely 21st century Arctic sea ice changes using these LIG simulations.
    Type of Medium: Online Resource
    ISSN: 1814-9332
    URL: Article
    URL: Article
    DOI: 10.5194/cp-17-37-2021
    DOI: 10.5194/cp-17-37-2021-supplement
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2021
    detail.hit.zdb_id: 2217985-9
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