64 resultados para Reduced model


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We give an a priori analysis of a semi-discrete discontinuous Galerkin scheme approximating solutions to a model of multiphase elastodynamics which involves an energy density depending not only on the strain but also the strain gradient. A key component in the analysis is the reduced relative entropy stability framework developed in Giesselmann (SIAM J Math Anal 46(5):3518–3539, 2014). The estimate we derive is optimal in the L∞(0,T;dG) norm for the strain and the L2(0,T;dG) norm for the velocity, where dG is an appropriate mesh dependent H1-like space.

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With the development of convection-permitting numerical weather prediction the efficient use of high resolution observations in data assimilation is becoming increasingly important. The operational assimilation of these observations, such as Dopplerradar radial winds, is now common, though to avoid violating the assumption of un- correlated observation errors the observation density is severely reduced. To improve the quantity of observations used and the impact that they have on the forecast will require the introduction of the full, potentially correlated, error statistics. In this work, observation error statistics are calculated for the Doppler radar radial winds that are assimilated into the Met Office high resolution UK model using a diagnostic that makes use of statistical averages of observation-minus-background and observation-minus-analysis residuals. This is the first in-depth study using the diagnostic to estimate both horizontal and along-beam correlated observation errors. By considering the new results obtained it is found that the Doppler radar radial wind error standard deviations are similar to those used operationally and increase as the observation height increases. Surprisingly the estimated observation error correlation length scales are longer than the operational thinning distance. They are dependent on both the height of the observation and on the distance of the observation away from the radar. Further tests show that the long correlations cannot be attributed to the use of superobservations or the background error covariance matrix used in the assimilation. The large horizontal correlation length scales are, however, in part, a result of using a simplified observation operator.

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Introducing a parameterization of the interactions between wind-driven snow depth changes and melt pond evolution allows us to improve large scale models. In this paper we have implemented an explicit melt pond scheme and, for the first time, a wind dependant snow redistribution model and new snow thermophysics into a coupled ocean–sea ice model. The comparison of long-term mean statistics of melt pond fractions against observations demonstrates realistic melt pond cover on average over Arctic sea ice, but a clear underestimation of the pond coverage on the multi-year ice (MYI) of the western Arctic Ocean. The latter shortcoming originates from the concealing effect of persistent snow on forming ponds, impeding their growth. Analyzing a second simulation with intensified snow drift enables the identification of two distinct modes of sensitivity in the melt pond formation process. First, the larger proportion of wind-transported snow that is lost in leads directly curtails the late spring snow volume on sea ice and facilitates the early development of melt ponds on MYI. In contrast, a combination of higher air temperatures and thinner snow prior to the onset of melting sometimes make the snow cover switch to a regime where it melts entirely and rapidly. In the latter situation, seemingly more frequent on first-year ice (FYI), a smaller snow volume directly relates to a reduced melt pond cover. Notwithstanding, changes in snow and water accumulation on seasonal sea ice is naturally limited, which lessens the impacts of wind-blown snow redistribution on FYI, as compared to those on MYI. At the basin scale, the overall increased melt pond cover results in decreased ice volume via the ice-albedo feedback in summer, which is experienced almost exclusively by MYI.

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Common cold is one of the most frequent human inflammatory diseases caused by viruses and can facilitate bacterial super-infections resulting in sinusitis or pneumonia. The active ingredient of the drug Soledum, 1,8-cineole, is commonly applied for treating inflammatory diseases of the respiratory tract. However, the potential of 1,8-cineole for treating primary viral infections of the respiratory tract remains unclear. In the present study, we demonstrate for the first time that 1,8-cineole potentiates Poly(I:C)-induced activity of the anti-viral transcription factor Interferon Regulatory Factor 3, while simultaneously reducing pro-inflammatory NF-κB-activity in human cell lines, inferior turbinate stem cells (ITSCs) and ex vivo cultivated human nasal mucosa. Co-treatment of cell lines with Poly(I:C) and 1,8-cineole resulted in significantly increased IRF3 reporter gene activity compared to Poly(I:C) alone, whereas NF-κB-activity was reduced. Accordingly, 1,8-cineole- and Poly(I:C)-treatment led to increased nuclear translocation of IRF3 in ITSCs and a human ex vivo model of rhinosinusitis compared to the Poly(I:C)-treated approach. Nuclear translocation of IRF3 was significantly increased in ITSCs and slice cultures treated with LPS and 1,8-cineole compared to the LPS-treated cells mimicking bacterial infection. Our findings strongly suggest that 1,8-cineole potentiates the antiviral activity of IRF3 in addition to its inhibitory effect on pro-inflammatory NF-κB-signalling and may thus broaden its field of application.