940 resultados para An eddy-resolving ocean model simulation
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Inflammatory bowel disease (IBD) is a chronic inflammation which affects the gastrointestinal tract (GIT). One of the best ways to study the immunological mechanisms involved during the disease is the T cell transfer model of colitis. In this model, immunodeficient mice (RAG-/-recipients) are reconstituted with naive CD4+ T cells from healthy wild type hosts. This model allows examination of the earliest immunological events leading to disease and chronic inflammation, when the gut inflammation perpetuates but does not depend on a defined antigen. To study the potential role of antigen presenting cells (APCs) in the disease process, it is helpful to have an antigen-driven disease model, in which a defined commensal-derived antigen leads to colitis. An antigen driven-colitis model has hence been developed. In this model OT-II CD4+ T cells, that can recognize only specific epitopes in the OVA protein, are transferred into RAG-/- hosts challenged with CFP-OVA-expressing E. coli. This model allows the examination of interactions between APCs and T cells in the lamina propria.
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I Medicane sono rari cicloni che si sviluppano sul Mar Mediterraneo e presentano caratteristiche dei cicloni tropicali, come la forma a spirale delle bande di nubi, un occhio privo di venti e nubi, venti intensi nella banda che circonda l’occhio e la presenza di un nucleo caldo. Nel presente lavoro, è stata compiuta un’analisi del Medicane Numa, verificatosi nel novembre del 2017, utilizzando gli output della simulazione del modello RAMS-ISAC. L’obiettivo di questa tesi è l’identificazione e la descrizione delle caratteristiche tropicali di Numa, focalizzandosi sulla descrizione dei diversi stadi di sviluppo del ciclone. Il sistema di bassa pressione è stato identificato utilizzando la pressione sul livello del mare, mentre l’anomalia termica e il vento orizzontale hanno permesso una descrizione della struttura del Medicane e del suo nucleo caldo. Un’illustrazione della struttura a spirale delle bande di nubi e dell’occhio è stata ottenuta con il grafico dei rapporti di mescolanza delle idrometeore di nubi e pioggia. Questi parametri hanno consentito di ricavare il diametro dell’occhio, pari a 75 km, mentre il diametro del Medicane è risultato 230 km. Numa ha registrato una velocità massima del vento in superficie di 20 m/s nella banda adiacente all’occhio del ciclone. Il diagramma di Hart dello spazio delle fasi del ciclone ha confermato la natura simil-tropicale di Numa e ne ha descritto l’evoluzione, identificando la transizione da sistema a caratteri tropicali a sistema ibrido. La traiettoria nello spazio delle fasi ha consentito l’identificazione delle sottofasi dell’evoluzione di Numa, confermate dai grafici dell’evoluzione temporale dei parametri menzionati in precedenza. L’analisi ha mostrato il ruolo cruciale della presenza di una struttura organizzata nel determinare l’intensità e la durata delle caratteristiche tropicali. Tutti i parametri hanno evidenziato la simmetria della struttura durante la persistente fase matura di Numa.
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Over the past 30 years, unhealthy diets and lifestyles have increased the incidence of noncommunicable diseases and are culprits of diffusion on world’s population of syndromes as obesity or other metabolic disorders, reaching pandemic proportions. In order to comply with such scenario, the food industry has tackled these challenges with different approaches, as the reformulation of foods, fortification of foods, substitution of ingredients and supplements with healthier ingredients, reduced animal protein, reduced fats and improved fibres applications. Although the technological quality of these emerging food products is known, the impact they have on the gut microbiota of consumers remains unclear. In the present PhD thesis, the recipient work was conducted to study different foods with the substitution of the industrial and market components to that of novel green oriented and sustainable ingredients. So far, this thesis included eight representative case studies of the most common substitutions/additions/fortifications in dairy, meat, and vegetable products. The products studied were: (i) a set of breads fortified with polyphenol-rich olive fiber, to replace synthetic antioxidant and preservatives, (ii) a set of Gluten-free breads fortified with algae powder, to fortify the protein content of standard GF products, (iii) different formulations of salami where nitrates were replaced by ascorbic acid and vegetal extract antioxidants and nitrate-reducers starter cultures, (iv) chocolate fiber plus D-Limonene food supplement, as a novel prebiotic formula, (v) hemp seed bran and its alkalase hydrolysate, to introduce as a supplement, (vi) milk with and without lactose, to evaluate the different impact on human colonic microbiota of healthy or lactose-intolerants, (vii) lactose-free whey fermented and/or with probiotics added, to be introduced as an alternative beverage, exploring its impact on human colonic microbiota from healthy or lactose-intolerants, and (viii) antibiotics, to assess whether maternal amoxicillin affects the colon microbiota of piglets.
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Obstacles considerably influence boundary layer processes. Their influences have been included in mesoscale models (MeM) for a long time. Methods used to parameterise obstacle effects in a MeM are summarised in this paper using results of the mesoscale model METRAS as examples. Besides the parameterisation of obstacle influences it is also possible to use a joint modelling approach to describe obstacle induced and mesoscale changes. Three different methods may be used for joint modelling approaches: The first method is a time-slice approach, where steady basic state profiles are used in an obstacle resolving microscale model (MiM, example model MITRAS) and diurnal cycles are derived by joining steady-state MITRAS results. The second joint modelling approach is one-way nesting, where the MeM results are used to initialise the MiM and to drive the boundary values of the MiM dependent on time. The third joint modelling approach is to apply multi-scale models or two-way nesting approaches, which include feedbacks from the MiM to the MeM. The advantages and disadvantages of the different approaches and remaining problems with joint Reynolds-averaged Navier–Stokes modelling approaches are summarised in the paper.
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The coastal area along the Emilia-Romagna (ER), in the Italian side of the northern Adriatic Sea, is considered to implement an unstructured numerical ocean model with the aim to develop innovative tools for the coastal management and a forecasting system for the storm surge risk reduction. The Adriatic Sea has been the focus of several studies because of its peculiar dynamics driven by many forcings acting at basin and local scales. The ER coast is particularly exposed to storm surge events. In particular conditions, winds, tides and seicehs may combine and contribute to the flooding of the coastal area. The global sea level rise expected in the next decades will increase even more the hazard along the ER and Adriatic coast. Reliable Adriatic and Mediterranean scale numerical ocean models are now available to allow the dynamical downscaling of very high-resolution models in limited coastal areas. In this work the numerical ocean model SHYFEM is implemented in the Goro lagoon (named GOLFEM) and along the ER coast (ShyfER) to test innovative solutions against sea related coastal hazards. GOLFEM was succesfully applied to analyze the Goro lagoon dynamics and to assess the dynamical effects of human interventions through the analysis of what-if scenarios. The assessment of storm surge hazard in the Goro lagoon was carried out through the development of an ensemble storm surge forecasting system with GOLFEM using forcing from different operational meteorological and ocean models showing the fundamental importance of the boundary conditions. The ShyfER domain is used to investigate innovative solutions against storm surge related hazard along the ER coast. The seagrass is assessed as a nature-based solution (NBS) for coastal protection under present and future climate conditions. The results show negligible effects on sea level but sensible effects in reducing bottom current velocity.
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The Model for Prediction Across Scales (MPAS) is a novel set of Earth system simulation components and consists of an atmospheric model, an ocean model and a land-ice model. Its distinct features are the use of unstructured Voronoi meshes and C-grid discretisation to address shortcomings of global models on regular grids and the use of limited area models nested in a forcing data set, with respect to parallel scalability, numerical accuracy and physical consistency. This concept allows one to include the feedback of regional land use information on weather and climate at local and global scales in a consistent way, which is impossible to achieve with traditional limited area modelling approaches. Here, we present an in-depth evaluation of MPAS with regards to technical aspects of performing model runs and scalability for three medium-size meshes on four different high-performance computing (HPC) sites with different architectures and compilers. We uncover model limitations and identify new aspects for the model optimisation that are introduced by the use of unstructured Voronoi meshes. We further demonstrate the model performance of MPAS in terms of its capability to reproduce the dynamics of the West African monsoon (WAM) and its associated precipitation in a pilot study. Constrained by available computational resources, we compare 11-month runs for two meshes with observations and a reference simulation from the Weather Research and Forecasting (WRF) model. We show that MPAS can reproduce the atmospheric dynamics on global and local scales in this experiment, but identify a precipitation excess for the West African region. Finally, we conduct extreme scaling tests on a global 3?km mesh with more than 65 million horizontal grid cells on up to half a million cores. We discuss necessary modifications of the model code to improve its parallel performance in general and specific to the HPC environment. We confirm good scaling (70?% parallel efficiency or better) of the MPAS model and provide numbers on the computational requirements for experiments with the 3?km mesh. In doing so, we show that global, convection-resolving atmospheric simulations with MPAS are within reach of current and next generations of high-end computing facilities.
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Toxicokinetic modeling is a useful tool to describe or predict the behavior of a chemical agent in the human or animal organism. A general model based on four compartments was developed in a previous study in order to quantify the effect of human variability on a wide range of biological exposure indicators. The aim of this study was to adapt this existing general toxicokinetic model to three organic solvents, which were methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1,-trichloroethane, and to take into account sex differences. We assessed in a previous human volunteer study the impact of sex on different biomarkers of exposure corresponding to the three organic solvents mentioned above. Results from that study suggested that not only physiological differences between men and women but also differences due to sex hormones levels could influence the toxicokinetics of the solvents. In fact the use of hormonal contraceptive had an effect on the urinary levels of several biomarkers, suggesting that exogenous sex hormones could influence CYP2E1 enzyme activity. These experimental data were used to calibrate the toxicokinetic models developed in this study. Our results showed that it was possible to use an existing general toxicokinetic model for other compounds. In fact, most of the simulation results showed good agreement with the experimental data obtained for the studied solvents, with a percentage of model predictions that lies within the 95% confidence interval varying from 44.4 to 90%. Results pointed out that for same exposure conditions, men and women can show important differences in urinary levels of biological indicators of exposure. Moreover, when running the models by simulating industrial working conditions, these differences could even be more pronounced. In conclusion, a general and simple toxicokinetic model, adapted for three well known organic solvents, allowed us to show that metabolic parameters can have an important impact on the urinary levels of the corresponding biomarkers. These observations give evidence of an interindividual variablity, an aspect that should have its place in the approaches for setting limits of occupational exposure.
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This paper presents a model of the Stokes emission vector from the ocean surface. The ocean surface is described as an ensemble of facets with Cox and Munk's (1954) Gram-Charlier slope distribution. The study discusses the impact of different up-wind and cross-wind rms slopes, skewness, peakedness, foam cover models and atmospheric effects on the azimuthal variation of the Stokes vector, as well as the limitations of the model. Simulation results compare favorably, both in mean value and azimuthal dependence, with SSM/I data at 53° incidence angle and with JPL's WINDRAD measurements at incidence angles from 30° to 65°, and at wind speeds from 2.5 to 11 m/s.
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The commonly held view of the conditions in the North Atlantic at the last glacial maximum, based on the interpretation of proxy records, is of large-scale cooling compared to today, limited deep convection, and extensive sea ice, all associated with a southward displaced and weakened overturning thermohaline circulation (THC) in the North Atlantic. Not all studies support that view; in particular, the "strength of the overturning circulation" is contentious and is a quantity that is difficult to determine even for the present day. Quasi-equilibrium simulations with coupled climate models forced by glacial boundary conditions have produced differing results, as have inferences made from proxy records. Most studies suggest the weaker circulation, some suggest little or no change, and a few suggest a stronger circulation. Here results are presented from a three-dimensional climate model, the Hadley Centre Coupled Model version 3 (HadCM3), of the coupled atmosphere - ocean - sea ice system suggesting, in a qualitative sense, that these diverging views could all have occurred at different times during the last glacial period, with different modes existing at different times. One mode might have been characterized by an active THC associated with moderate temperatures in the North Atlantic and a modest expanse of sea ice. The other mode, perhaps forced by large inputs of meltwater from the continental ice sheets into the northern North Atlantic, might have been characterized by a sluggish THC associated with very cold conditions around the North Atlantic and a large areal cover of sea ice. The authors' model simulation of such a mode, forced by a large input of freshwater, bears several of the characteristics of the Climate: Long-range Investigation, Mapping, and Prediction (CLIMAP) Project's reconstruction of glacial sea surface temperature and sea ice extent.
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The multidecadal variability of El Niño–Southern Oscillation (ENSO)–South Asian monsoon relationship is elucidated in a 1000 year control simulation of a coupled general circulation model. The results indicate that the Atlantic Multidecadal Oscillation (AMO), resulting from the natural fluctuation of the Atlantic Meridional Overturning Circulation (AMOC), plays an important role in modulating the multidecadal variation of the ENSO-monsoon relationship. The sea surface temperature anomalies associated with the AMO induce not only significant climate impact in the Atlantic but also the coupled feedbacks in the tropical Pacific regions. The remote responses in the Pacific Ocean to a positive phase of the AMO which is resulted from enhanced AMOC in the model simulation and are characterized by statistically significant warming in the North Pacific and in the western tropical Pacific, a relaxation of tropical easterly trades in the central and eastern tropical Pacific, and a deeper thermocline in the eastern tropical Pacific. These changes in mean states lead to a reduction of ENSO variability and therefore a weakening of the ENSO-monsoon relationship. This study suggests a nonlocal mechanism for the low-frequency fluctuation of the ENSO-monsoon relationship, although the AMO explains only a fraction of the ENSO–South Asian monsoon variation on decadal-multidecadal timescale. Given the multidecadal variation of the AMOC and therefore of the AMO exhibit decadal predictability, this study highlights the possibility that a part of the change of climate variability in the Pacific Ocean and its teleconnection may be predictable.
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The role of air–sea coupling in the simulation of the Madden–Julian oscillation (MJO) is explored using two configurations of the Hadley Centre atmospheric model (AGCM), GA3.0, which differ only in F, a parameter controlling convective entrainment and detrainment. Increasing F considerably improves deficient MJO-like variability in the Indian and Pacific Oceans, but variability in and propagation through the Maritime Continent remains weak. By coupling GA3.0 in the tropical Indo-Pacific to a boundary-layer ocean model, KPP, and employing climatological temperature corrections, well resolved air–sea interactions are simulated with limited alterations to the mean state. At default F, when GA3.0 has a poor MJO, coupling produces a stronger MJO with some eastward propagation, although both aspects remain deficient. These results agree with previous sensitivity studies using AGCMs with poor variability. At higher F, coupling does not affect MJO amplitude but enhances propagation through the Maritime Continent, resulting in an MJO that resembles observations. A sensitivity experiment with coupling in only the Indian Ocean reverses these improvements, suggesting coupling in the Maritime Continent and West Pacific is critical for propagation. We hypothesise that for AGCMs with a poor MJO, coupling provides a “crutch” to artificially augment MJO-like activity through high-frequency SST anomalies. In related experiments, we employ the KPP framework to analyse the impact of air–sea interactions in the fully coupled GA3.0, which at default F shows a similar MJO to uncoupled GA3.0. This is due to compensating effects: an improvement from coupling and a degradation from mean-state errors. Future studies on the role of coupling should carefully separate these effects.
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Instrumental observations, palaeo-proxies, and climate models suggest significant decadal variability within the North Atlantic subpolar gyre (NASPG). However, a poorly sampled observational record and a diversity of model behaviours mean that the precise nature and mechanisms of this variability are unclear. Here, we analyse an exceptionally large multi-model ensemble of 42 present-generation climate models to test whether NASPG mean state biases systematically affect the representation of decadal variability. Temperature and salinity biases in the Labrador Sea co-vary and influence whether density variability is controlled by temperature or salinity variations. Ocean horizontal resolution is a good predictor of the biases and the location of the dominant dynamical feedbacks within the NASPG. However, we find no link to the spectral characteristics of the variability. Our results suggest that the mean state and mechanisms of variability within the NASPG are not independent. This represents an important caveat for decadal predictions using anomaly-assimilation methods.
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A set of four eddy-permitting global ocean reanalyses produced in the framework of the MyOcean project have been compared over the altimetry period 1993–2011. The main differences among the reanalyses used here come from the data assimilation scheme implemented to control the ocean state by inserting reprocessed observations of sea surface temperature (SST), in situ temperature and salinity profiles, sea level anomaly and sea-ice concentration. A first objective of this work includes assessing the interannual variability and trends for a series of parameters, usually considered in the community as essential ocean variables: SST, sea surface salinity, temperature and salinity averaged over meaningful layers of the water column, sea level, transports across pre-defined sections, and sea ice parameters. The eddy-permitting nature of the global reanalyses allows also to estimate eddy kinetic energy. The results show that in general there is a good consistency between the different reanalyses. An intercomparison against experiments without data assimilation was done during the MyOcean project and we conclude that data assimilation is crucial for correctly simulating some quantities such as regional trends of sea level as well as the eddy kinetic energy. A second objective is to show that the ensemble mean of reanalyses can be evaluated as one single system regarding its reliability in reproducing the climate signals, where both variability and uncertainties are assessed through the ensemble spread and signal-to-noise ratio. The main advantage of having access to several reanalyses differing in the way data assimilation is performed is that it becomes possible to assess part of the total uncertainty. Given the fact that we use very similar ocean models and atmospheric forcing, we can conclude that the spread of the ensemble of reanalyses is mainly representative of our ability to gauge uncertainty in the assimilation methods. This uncertainty changes a lot from one ocean parameter to another, especially in global indices. However, despite several caveats in the design of the multi-system ensemble, the main conclusion from this study is that an eddy-permitting multi-system ensemble approach has become mature and our results provide a first step towards a systematic comparison of eddy-permitting global ocean reanalyses aimed at providing robust conclusions on the recent evolution of the oceanic state.
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Atmosphere only and ocean only variational data assimilation (DA) schemes are able to use window lengths that are optimal for the error growth rate, non-linearity and observation density of the respective systems. Typical window lengths are 6-12 hours for the atmosphere and 2-10 days for the ocean. However, in the implementation of coupled DA schemes it has been necessary to match the window length of the ocean to that of the atmosphere, which may potentially sacrifice the accuracy of the ocean analysis in order to provide a more balanced coupled state. This paper investigates how extending the window length in the presence of model error affects both the analysis of the coupled state and the initialized forecast when using coupled DA with differing degrees of coupling. Results are illustrated using an idealized single column model of the coupled atmosphere-ocean system. It is found that the analysis error from an uncoupled DA scheme can be smaller than that from a coupled analysis at the initial time, due to faster error growth in the coupled system. However, this does not necessarily lead to a more accurate forecast due to imbalances in the coupled state. Instead coupled DA is more able to update the initial state to reduce the impact of the model error on the accuracy of the forecast. The effect of model error is potentially most detrimental in the weakly coupled formulation due to the inconsistency between the coupled model used in the outer loop and uncoupled models used in the inner loop.
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A detailed climatology of the cyclogenesis over the Southern Atlantic Ocean (SAO) from 1990 to 1999 and how it is simulated by the RegCM3 (Regional Climate Model) is presented here. The simulation used as initial and boundary conditions the National Centers for Environmental Prediction-Department of Energy (NCEP/DOE) reanalysis. The cyclones were identified with an automatic scheme that searches for cyclonic relative vorticity (zeta(10)) obtained from a 10-m height wind field. All the systems with zeta(10) a parts per thousand currency sign -1.5 x 10(-5) s(-1) and lifetime equal or larger than 24 h were considered in the climatology. Over SAO, in 10 years were detected 2,760 and 2,787 cyclogeneses in the simulation and NCEP, respectively, with an annual mean of 276.0 +/- A 11.2 and 278.7 +/- A 11.1. This result suggests that the RegCM3 has a good skill to simulate the cyclogenesis climatology. However, the larger model underestimations (-9.8%) are found for the initially stronger systems (zeta(10) a parts per thousand currency sign -2.5 x 10(-5) s(-1)). It was noted that over the SAO the annual cycle of the cyclogenesis depends of its initial intensity. Considering the systems initiate with zeta(10) a parts per thousand currency sign -1.5 x 10(-5) s(-1), the annual cycle is not well defined and the higher frequency occurs in the autumn (summer) in the NCEP (RegCM3). The stronger systems (zeta(10) a parts per thousand currency sign -2.5 x 10(-5) s(-1)) have a well-characterized high frequency of cyclogenesis during the winter in both NCEP and RegCM3. This work confirms the existence of three cyclogenetic regions in the west sector of the SAO, near the South America east coast and shows that RegCM3 is able to reproduce the main features of these cyclogenetic areas.