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  • 1
    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
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2020
    detail.hit.zdb_id: 2456725-5
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  • 2
    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
    RVK:
    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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  • 3
    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
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
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    detail.hit.zdb_id: 1143556-2
    detail.hit.zdb_id: 605570-9
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  • 4
    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
    RVK:
    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
    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
    RVK:
    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
    Copernicus GmbH ; 2021
    In:  Earth System Science Data Vol. 13, No. 12 ( 2021-12-07), p. 5663-5688
    In: Earth System Science Data, Copernicus GmbH, Vol. 13, No. 12 ( 2021-12-07), p. 5663-5688
    Abstract: Abstract. BRAN2020 (2020 version of the Bluelink ReANalysis) is an ocean reanalysis that combines observations with an eddy-resolving, near-global ocean general circulation model to produce a four-dimensional estimate of the ocean state. The data assimilation system employed is ensemble optimal interpolation, implemented with a new multiscale approach that constrains the broad-scale ocean properties and the mesoscale circulation in two steps. There is a separation in the scales that are corrected in the two steps: the high-resolution step corrects the mesoscale dynamics in the same way as previous versions of BRAN, while the extra coarse step is effective at correcting biases that develop at large scales. The reanalysis currently spans January 1993 to December 2019 and assimilates observations of in situ temperature and salinity, as well as of satellite sea-level anomaly and sea surface temperature. BRAN2020 is planned to be updated to within months of real time after this initial release, until an updated version of BRAN is available. Reanalysed fields from BRAN2020 generally show much closer agreement to observations than all previous versions with misfits between reanalysed and observed fields reduced by over 30 % for some variables, for subsurface temperature and salinity in particular. The BRAN2020 dataset is comprised of daily averaged fields of temperature, salinity, velocity, mixed-layer depth and sea level. Reanalysed fields realistically represent all of the major current systems within 75∘ S and 75∘ N, excluding processes relating to sea ice but including boundary currents, equatorial circulation, Southern Ocean variability and mesoscale eddies. BRAN2020 is publicly available at https://doi.org/10.25914/6009627c7af03 (Chamberlain et al., 2021b) and is intended for use by the research community.
    Type of Medium: Online Resource
    ISSN: 1866-3516
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2021
    detail.hit.zdb_id: 2475469-9
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  • 7
    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
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
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    detail.hit.zdb_id: 1143556-2
    detail.hit.zdb_id: 605570-9
    SSG: 12
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  • 8
    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
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2020
    detail.hit.zdb_id: 2158181-2
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  • 9
    Online Resource
    Online Resource
    Elsevier BV ; 2007
    In:  Icarus Vol. 188, No. 2 ( 2007-6), p. 451-456
    In: Icarus, Elsevier BV, Vol. 188, No. 2 ( 2007-6), p. 451-456
    Type of Medium: Online Resource
    ISSN: 0019-1035
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2007
    detail.hit.zdb_id: 1467991-7
    SSG: 16,12
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  • 10
    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
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2741235-0
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