884 resultados para Resultant
Resumo:
The sea ice edge presents a region of many feedback processes between the atmosphere, ocean, and sea ice (Maslowski et al.). Here the authors focus on the impact of on-ice atmospheric and oceanic flows at the sea ice edge. Mesoscale jet formation due to the Coriolis effect is well understood over sharp changes in surface roughness such as coastlines (Hunt et al.). This sharp change in surface roughness is experienced by the atmosphere and ocean encountering a compacted sea ice edge. This paper presents a study of a dynamic sea ice edge responding to prescribed atmospheric and oceanic jet formation. An idealized analytical model of sea ice drift is developed and compared to a sea ice climate model [the Los Alamos Sea Ice Model (CICE)] run on an idealized domain. The response of the CICE model to jet formation is tested at various resolutions. It is found that the formation of atmospheric jets at the sea ice edge increases the wind speed parallel to the sea ice edge and results in the formation of a sea ice drift jet in agreement with an observed sea ice drift jet (Johannessen et al.). The increase in ice drift speed is dependent upon the angle between the ice edge and wind and results in up to a 40% increase in ice transport along the sea ice edge. The possibility of oceanic jet formation and the resultant effect upon the sea ice edge is less conclusive. Observations and climate model data of the polar oceans have been analyzed to show areas of likely atmospheric jet formation, with the Fram Strait being of particular interest.
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With a rapidly increasing fraction of electricity generation being sourced from wind, extreme wind power generation events such as prolonged periods of low (or high) generation and ramps in generation, are a growing concern for the efficient and secure operation of national power systems. As extreme events occur infrequently, long and reliable meteorological records are required to accurately estimate their characteristics. Recent publications have begun to investigate the use of global meteorological “reanalysis” data sets for power system applications, many of which focus on long-term average statistics such as monthly-mean generation. Here we demonstrate that reanalysis data can also be used to estimate the frequency of relatively short-lived extreme events (including ramping on sub-daily time scales). Verification against 328 surface observation stations across the United Kingdom suggests that near-surface wind variability over spatiotemporal scales greater than around 300 km and 6 h can be faithfully reproduced using reanalysis, with no need for costly dynamical downscaling. A case study is presented in which a state-of-the-art, 33 year reanalysis data set (MERRA, from NASA-GMAO), is used to construct an hourly time series of nationally-aggregated wind power generation in Great Britain (GB), assuming a fixed, modern distribution of wind farms. The resultant generation estimates are highly correlated with recorded data from National Grid in the recent period, both for instantaneous hourly values and for variability over time intervals greater than around 6 h. This 33 year time series is then used to quantify the frequency with which different extreme GB-wide wind power generation events occur, as well as their seasonal and inter-annual variability. Several novel insights into the nature of extreme wind power generation events are described, including (i) that the number of prolonged low or high generation events is well approximated by a Poission-like random process, and (ii) whilst in general there is large seasonal variability, the magnitude of the most extreme ramps is similar in both summer and winter. An up-to-date version of the GB case study data as well as the underlying model are freely available for download from our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/.
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Particles with energies of tens to hundreds of keV provide a powerful diagnostic of the acceleration processes that characterise the Earth’s magnetosphere, in particular the highly dynamic nightside plasma sheet. Such energetic particles can be detected by the RAPID experiment, onboard the quartet of Cluster spacecraft. We present results from the study of a series of quasi-periodic, intense energetic electron signatures in the magnetotail revealed by RAPID Imaging Electron Spectrometer (IES) observations some 19 Earth radii (RE) downtail, associated with the passage of a highly geoeffective, high-speed solar wind stream. The RAPID-IES signatures – interpreted in combination with magnetic field and lower-energy electron measurements from the FGM and PEACE experiments on Cluster, respectively, and with reference to energetic electron observations from the CEPPAD-IES instrument on Polar – are understood in terms of repeated encounters of the Cluster spacecraft with the tail plasma sheet in response to the resultant tail reconfiguration in each of a series of substorms. We consider the Cluster response for two of these substorms (identified according to the conventional expansion phase onset indicators of particle injection at geosynchronous orbit and Pi2 pulsations at Earth) in terms of two possible tail configurations in which a Near-Earth Neutral Line forms either antisunward or sunward of the Cluster spacecraft. The latter scenario, in which the reconnection X-line is assumed to form sunward of Cluster and subsequently migrate downtail such that the spacecraft become engulfed in a tailward expanding plasma sheet, is shown to be more consistent with the observations.
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The paper discusses how variations in the pattern of convective plasma flows should beincluded in self-consistent time-dependent models of the coupled ionosphere-thermosphere system. The author shows how these variations depend upon the mechanism by which the solar wind flow excites the convection. The modelling of these effects is not just of relevance to the polar ionosphere. This is because the influence of convection is not confined to high latitudes: the resultant heating and composition changes in the thermosphere are communicated to lower latitudes by the winds which are also greatly modified by the plasma convection. These thermospheric changes alter the global distribution of plasma by modulatingthe rates of the chemical reactions which areresponsible for the loss of plasma. Hence the modelling of these high-latitude processes is of relevanceto the design and operation of HF communication, radar and navigation systems worldwide.
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The Monte Carlo Independent Column Approximation (McICA) is a flexible method for representing subgrid-scale cloud inhomogeneity in radiative transfer schemes. It does, however, introduce conditional random errors but these have been shown to have little effect on climate simulations, where spatial and temporal scales of interest are large enough for effects of noise to be averaged out. This article considers the effect of McICA noise on a numerical weather prediction (NWP) model, where the time and spatial scales of interest are much closer to those at which the errors manifest themselves; this, as we show, means that noise is more significant. We suggest methods for efficiently reducing the magnitude of McICA noise and test these methods in a global NWP version of the UK Met Office Unified Model (MetUM). The resultant errors are put into context by comparison with errors due to the widely used assumption of maximum-random-overlap of plane-parallel homogeneous cloud. For a simple implementation of the McICA scheme, forecasts of near-surface temperature are found to be worse than those obtained using the plane-parallel, maximum-random-overlap representation of clouds. However, by applying the methods suggested in this article, we can reduce noise enough to give forecasts of near-surface temperature that are an improvement on the plane-parallel maximum-random-overlap forecasts. We conclude that the McICA scheme can be used to improve the representation of clouds in NWP models, with the provision that the associated noise is sufficiently small.
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In this work we construct reliable a posteriori estimates for some semi- (spatially) discrete discontinuous Galerkin schemes applied to nonlinear systems of hyperbolic conservation laws. We make use of appropriate reconstructions of the discrete solution together with the relative entropy stability framework, which leads to error control in the case of smooth solutions. The methodology we use is quite general and allows for a posteriori control of discontinuous Galerkin schemes with standard flux choices which appear in the approximation of conservation laws. In addition to the analysis, we conduct some numerical benchmarking to test the robustness of the resultant estimator.
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Parkinson is a neurodegenerative disease, in which tremor is the main symptom. This paper investigates the use of different classification methods to identify tremors experienced by Parkinsonian patients.Some previous research has focussed tremor analysis on external body signals (e.g., electromyography, accelerometer signals, etc.). Our advantage is that we have access to sub-cortical data, which facilitates the applicability of the obtained results into real medical devices since we are dealing with brain signals directly. Local field potentials (LFP) were recorded in the subthalamic nucleus of 7 Parkinsonian patients through the implanted electrodes of a deep brain stimulation (DBS) device prior to its internalization. Measured LFP signals were preprocessed by means of splinting, down sampling, filtering, normalization and rec-tification. Then, feature extraction was conducted through a multi-level decomposition via a wavelettrans form. Finally, artificial intelligence techniques were applied to feature selection, clustering of tremor types, and tremor detection.The key contribution of this paper is to present initial results which indicate, to a high degree of certainty, that there appear to be two distinct subgroups of patients within the group-1 of patients according to the Consensus Statement of the Movement Disorder Society on Tremor. Such results may well lead to different resultant treatments for the patients involved, depending on how their tremor has been classified. Moreover, we propose a new approach for demand driven stimulation, in which tremor detection is also based on the subtype of tremor the patient has. Applying this knowledge to the tremor detection problem, it can be concluded that the results improve when patient clustering is applied prior to detection.
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We describe the creation of a data set describing changes related to the presence of ice sheets, including ice-sheet extent and height, ice-shelf extent, and the distribution and elevation of ice-free land at the Last Glacial Maximum (LGM), which were used in LGM experiments conducted as part of the fifth phase of the Coupled Modelling Intercomparison Project (CMIP5) and the third phase of the Palaeoclimate Modelling Intercomparison Project (PMIP3). The CMIP5/PMIP3 data sets were created from reconstructions made by three different groups, which were all obtained using a model-inversion approach but differ in the assumptions used in the modelling and in the type of data used as constraints. The ice-sheet extent in the Northern Hemisphere (NH) does not vary substantially between the three individual data sources. The difference in the topography of the NH ice sheets is also moderate, and smaller than the differences between these reconstructions (and the resultant composite reconstruction) and ice-sheet reconstructions used in previous generations of PMIP. Only two of the individual reconstructions provide information for Antarctica. The discrepancy between these two reconstructions is larger than the difference for the NH ice sheets, although still less than the difference between the composite reconstruction and previous PMIP ice-sheet reconstructions. Although largely confined to the ice-covered regions, differences between the climate response to the individual LGM reconstructions extend over the North Atlantic Ocean and Northern Hemisphere continents, partly through atmospheric stationary waves. Differences between the climate response to the CMIP5/PMIP3 composite and any individual ice-sheet reconstruction are smaller than those between the CMIP5/PMIP3 composite and the ice sheet used in the last phase of PMIP (PMIP2).
Resumo:
Since 2004, the satellite-borne Ozone Mapping Instrument (OMI) has observed sulphur dioxide (SO2) plumes during both quiescence and effusive eruptive activity at Soufrière Hills Volcano, Montserrat. On average, OMI detected a SO2 plume 4-6 times more frequently during effusive periods than during quiescence in the 2008-2010 period. The increased ability of OMI to detect SO2 during eruptive periods is mainly due to an increase in plume altitude rather than a higher SO2 emission rate. Three styles of eruptive activity cause thermal lofting of gases (Vulcanian explosions; pyroclastic flows; a hot lava dome) and the resultant plume altitudes are estimated from observations and models. Most lofting plumes from Soufrière Hills are derived from hot domes and pyroclastic flows. Although Vulcanian explosions produced the largest plumes, some produced only negligible SO2 signals detected by OMI. OMI is most valuable for monitoring purposes at this volcano during periods of lava dome growth and during explosive activity.
Resumo:
The first agricultural societies were established around 10 ka BP and had spread across much of Europe and southern Asia by 5.5 ka BP with resultant anthropogenic deforestation for crop and pasture land. Various studies (e.g. Joos et al., 2004; Kaplan et al., 2011; Mitchell et al., 2013) have attempted to assess the biogeochemical implications for Holocene climate in terms of increased carbon dioxide and methane emissions. However, less work has been done to examine the biogeophysical impacts of this early land use change. In this study, global climate model simulations with Hadley Centre Coupled Model version 3 (HadCM3) were used to examine the biogeophysical effects of Holocene land cover change on climate, both globally and regionally, from the early Holocene (8 ka BP) to the early industrial era (1850 CE). Two experiments were performed with alternative descriptions of past vegetation: (i) one in which potential natural vegetation was simulated by Top-down Representation of Interactive Foliage and Flora Including Dynamics (TRIFFID) but without land use changes and (ii) one where the anthropogenic land use model Kaplan and Krumhardt 2010 (KK10; Kaplan et al., 2009, 2011) was used to set the HadCM3 crop regions. Snapshot simulations were run at 1000-year intervals to examine when the first signature of anthropogenic climate change can be detected both regionally, in the areas of land use change, and globally. Results from our model simulations indicate that in regions of early land disturbance such as Europe and south-east Asia detectable temperature changes, outside the normal range of variability, are encountered in the model as early as 7 ka BP in the June–July–August (JJA) season and throughout the entire annual cycle by 2–3 ka BP. Areas outside the regions of land disturbance are also affected, with virtually the whole globe experiencing significant temperature changes (predominantly cooling) by the early industrial period. The global annual mean temperature anomalies found in our single model simulations were −0.22 at 1850 CE, −0.11 at 2 ka BP, and −0.03 °C at 7 ka BP. Regionally, the largest temperature changes were in Europe with anomalies of −0.83 at 1850 CE, −0.58 at 2 ka BP, and −0.24 °C at 7 ka BP. Large-scale precipitation features such as the Indian monsoon, the Intertropical Convergence Zone (ITCZ), and the North Atlantic storm track are also impacted by local land use and remote teleconnections. We investigated how advection by surface winds, mean sea level pressure (MSLP) anomalies, and tropospheric stationary wave train disturbances in the mid- to high latitudes led to remote teleconnections.
Resumo:
This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.
Resumo:
Camarea is a South-American endemic genus comprising eight species. In the present work leaf flavonoids of seven species of Camarea were identified, aiming to evaluate the usefulness of their distribution as a taxonomic aid. A total of 12 flavonoids were isolated and identified. Free aglycones, such as apigenin, chrysoeriol, kaempferol and quercetin, as well as 7-O-glycosides of apigenin and luteolin, 3-O-glycosides of kaempferol and quercetin were identified. Flavonoid distribution in Camarea species, taking into account aglycones and aglycone moieties of glycosides, was used to obtain a phenogram of chemical affinities. Apigenin, chrysoeriol and kaempferol were the main discriminating characters for links establishment. The resultant tree suggests the links: 1) Camarea hirsuta, Camarea affinis and C. affinis x C. hirsuta; 2) Camarea elongata and Camarea axillaris; 3) Camarea sericea and Camarea humifusa. The results are in agreement with morphological similarities and disagree with several points of n-alkane evidence. The results support the recognition of Camarea triphylla as synonymy of C axillaris. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
A 2D steady model for the annular two-phase flow of water and steam in the steam-generating boiler pipes of a liquid metal fast breeder reactor is proposed The model is based on thin-layer lubrication theory and thin aerofoil theory. The exchange of mass between the vapour core and the liquid film due to evaporation of the liquid film is accounted for using some simple thermodynamics models, and the resultant change of phase is modelled by proposing a suitable Stefan problem Appropriate boundary conditions for the now are discussed The resulting non-lineal singular integro-differential equation for the shape of the liquid film free surface is solved both asymptotically and numerically (using some regularization techniques) Predictions for the length to the dryout point from the entry of the annular regime are made The influence of both the traction tau provided by the fast-flowing vapour core on the liquid layer and the mass transfer parameter eta on the dryout length is investigated
Resumo:
Periodic first-principles calculations based on density functional theory at the B3LYP level has been carried out to investigate the photoluminescence (PL) emission of BaZrO(3) assembled nanoparticles at room temperature. The defect created in the nanocrystals and their resultant electronic features lead to a diversification of electronic recombination within the BaZrO(3) band gap. Its optical phenomena are discussed in the light of photoluminescence emission at the green-yellow region around 570 nm. The theoretical model for displaced atoms and/or angular changes leads to the breaking of the local symmetry, which is based on the refined structure provided by Rietveld methodology. For each situation a band structure, charge mapping, and density of states were built and analyzed. X-ray diffraction (XRD) patterns, UV-vis measurements, and field emission scanning electron microscopy (FE-SEM) images are essential for a full evaluation of the crystal structure and morphology.
Resumo:
Ilha Comprida is a regressive barrier island located in southeastern Brazil that was formed essentially by Quaternary sandy sediments. Ilha Comprida sediments were analyzed to assess heavy mineral indices and grain size variables. The spatial variation of heavy minerals and grain size was interpreted in terms of the present barrier dynamics and the barrier`s evolution since the Middle Holocene. These analyses allowed for the identification of the main factors and processes that control the variation of heavy minerals and grain size on the barrier. Rutile and zircon (RZi) and tourmaline and hornblende (THi) are significantly sensitive to provenance and exhibit the contributions of the Ribeira de Iguape River sediments, which reach the coast next to the northeastern end of Ilha Comprida. In addition to the influence of provenance, TZi responds mainly to hydraulic sorting processes. This agrees with a sediment transport pattern characterized by a divergence of two resultant net alongshore drifts southwest of the barrier. The sediments from the Ribeira de Iguape River reach the barrier directly through the river mouth and indirectly after temporary storage in the inner shelf. The combination of grain size and heavy mineral analyses is a reliable method for determining sediment transport patterns and provenance. (C) 2010 Elsevier Ltd. All rights reserved.