958 resultados para Extended Hubbard-model


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An analytical model is developed to predict the surface drag exerted by internal gravity waves on an isolated axisymmetric mountain over which there is a stratified flow with a velocity profile that varies relatively slowly with height. The model is linear with respect to the perturbations induced by the mountain, and solves the Taylor–Goldstein equation with variable coefficients using a Wentzel–Kramers–Brillouin (WKB) approximation, formally valid for high Richardson numbers, Ri. The WKB solution is extended to a higher order than in previous studies, enabling a rigorous treatment of the effects of shear and curvature of the wind profile on the surface drag. In the hydrostatic approximation, closed formulas for the drag are derived for generic wind profiles, where the relative magnitude of the corrections to the leading-order drag (valid for a constant wind profile) does not depend on the detailed shape of the orography. The drag is found to vary proportionally to Ri21, decreasing as Ri decreases for a wind that varies linearly with height, and increasing as Ri decreases for a wind that rotates with height maintaining its magnitude. In these two cases the surface drag is predicted to be aligned with the surface wind. When one of the wind components varies linearly with height and the other is constant, the surface drag is misaligned with the surface wind, especially for relatively small Ri. All these results are shown to be in fairly good agreement with numerical simulations of mesoscale nonhydrostatic models, for high and even moderate values of Ri.

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The realistic representation of rainfall on the local scale in climate models remains a key challenge. Realism encompasses the full spatial and temporal structure of rainfall, and is a key indicator of model skill in representing the underlying processes. In particular, if rainfall is more realistic in a climate model, there is greater confidence in its projections of future change. In this study, the realism of rainfall in a very high-resolution (1.5 km) regional climate model (RCM) is compared to a coarser-resolution 12-km RCM. This is the first time a convection-permitting model has been run for an extended period (1989–2008) over a region of the United Kingdom, allowing the characteristics of rainfall to be evaluated in a climatological sense. In particular, the duration and spatial extent of hourly rainfall across the southern United Kingdom is examined, with a key focus on heavy rainfall. Rainfall in the 1.5-km RCM is found to be much more realistic than in the 12-km RCM. In the 12-km RCM, heavy rain events are not heavy enough, and tend to be too persistent and widespread. While the 1.5-km model does have a tendency for heavy rain to be too intense, it still gives a much better representation of its duration and spatial extent. Long-standing problems in climate models, such as the tendency for too much persistent light rain and errors in the diurnal cycle, are also considerably reduced in the 1.5-km RCM. Biases in the 12-km RCM appear to be linked to deficiencies in the representation of convection.

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Simulations of the stratosphere from thirteen coupled chemistry-climate models (CCMs) are evaluated to provide guidance for the interpretation of ozone predictions made by the same CCMs. The focus of the evaluation is on how well the fields and processes that are important for determining the ozone distribution are represented in the simulations of the recent past. The core period of the evaluation is from 1980 to 1999 but long-term trends are compared for an extended period (1960–2004). Comparisons of polar high-latitude temperatures show that most CCMs have only small biases in the Northern Hemisphere in winter and spring, but still have cold biases in the Southern Hemisphere spring below 10 hPa. Most CCMs display the correct stratospheric response of polar temperatures to wave forcing in the Northern, but not in the Southern Hemisphere. Global long-term stratospheric temperature trends are in reasonable agreement with satellite and radiosonde observations. Comparisons of simulations of methane, mean age of air, and propagation of the annual cycle in water vapor show a wide spread in the results, indicating differences in transport. However, for around half the models there is reasonable agreement with observations. In these models the mean age of air and the water vapor tape recorder signal are generally better than reported in previous model intercomparisons. Comparisons of the water vapor and inorganic chlorine (Cly) fields also show a large intermodel spread. Differences in tropical water vapor mixing ratios in the lower stratosphere are primarily related to biases in the simulated tropical tropopause temperatures and not transport. The spread in Cly, which is largest in the polar lower stratosphere, appears to be primarily related to transport differences. In general the amplitude and phase of the annual cycle in total ozone is well simulated apart from the southern high latitudes. Most CCMs show reasonable agreement with observed total ozone trends and variability on a global scale, but a greater spread in the ozone trends in polar regions in spring, especially in the Arctic. In conclusion, despite the wide range of skills in representing different processes assessed here, there is sufficient agreement between the majority of the CCMs and the observations that some confidence can be placed in their predictions.

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The recovery of the Arctic polar vortex following stratospheric sudden warmings is found to take upward of 3 months in a particular subset of cases, termed here polar-night jet oscillation (PJO) events. The anomalous zonal-mean circulation above the pole during this recovery is characterized by a persistently warm lower stratosphere, and above this a cold midstratosphere and anomalously high stratopause, which descends as the event unfolds. Composites of these events in the Canadian Middle Atmosphere Model show the persistence of the lower-stratospheric anomaly is a result of strongly suppressed wave driving and weak radiative cooling at these heights. The upper-stratospheric and lower-mesospheric anomalies are driven immediately following the warming by anomalous planetary-scale eddies, following which, anomalous parameterized nonorographic and orographic gravity waves play an important role. These details are found to be robust for PJO events (as opposed to sudden warmings in general) in that many details of individual PJO events match the composite mean. Azonal-mean quasigeostrophic model on the sphere is shown to reproduce the response to the thermal and mechanical forcings produced during a PJO event. The former is well approximated by Newtonian cooling. The response can thus be considered as a transient approach to the steady-state, downward control limit. In this context, the time scale of the lower-stratospheric anomaly is determined by the transient, radiative response to the extended absence of wave driving. The extent to which the dynamics of the wave-driven descent of the stratopause can be considered analogous to the descending phases of the quasi-biennial oscillation (QBO) is also discussed.

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A mesoscale meteorological model (FOOT3DK) is coupled with a gas exchange model to simulate surface fluxes of CO2 and H2O under field conditions. The gas exchange model consists of a C3 single leaf photosynthesis sub-model and an extended big leaf (sun/shade) sub-model that divides the canopy into sunlit and shaded fractions. Simulated CO2 fluxes of the stand-alone version of the gas exchange model correspond well to eddy-covariance measurements at a test site in a rural area in the west of Germany. The coupled FOOT3DK/gas exchange model is validated for the diurnal cycle at singular grid points, and delivers realistic fluxes with respect to their order of magnitude and to the general daily course. Compared to the Jarvis-based big leaf scheme, simulations of latent heat fluxes with a photosynthesis-based scheme for stomatal conductance are more realistic. As expected, flux averages are strongly influenced by the underlying land cover. While the simulated net ecosystem exchange is highly correlated with leaf area index, this correlation is much weaker for the latent heat flux. Photosynthetic CO2 uptake is associated with transpirational water loss via the stomata, and the resulting opposing surface fluxes of CO2 and H2O are reproduced with the model approach. Over vegetated surfaces it is shown that the coupling of a photosynthesis-based gas exchange model with the land-surface scheme of a mesoscale model results in more realistic simulated latent heat fluxes.

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A version of the Canadian Middle Atmosphere Model (CMAM) that is nudged toward reanalysis data up to 1 hPa is used to examine the impacts of parameterized orographic and non-orographic gravity wave drag (OGWD and NGWD) on the zonal-mean circulation of the mesosphere during the extended northern winters of 2006 and 2009 when there were two large stratospheric sudden warmings. The simulations are compared to Aura Microwave Limb Sounder (MLS) observations of mesospheric temperature, carbon monoxide (CO) and derived zonal winds. The control simulation, which uses both OGWD and NGWD, is shown to be in good agreement with MLS. The impacts of OGWD and NGWD are assessed using simulations in which those sources of wave drag are removed. In the absence of OGWD the mesospheric zonal winds in the months preceding the warmings are too strong, causing increased mesospheric NGWD, which drives excessive downwelling, resulting in overly large lower mesospheric values of CO prior to the warming. NGWD is found to be most important following the warmings when the underlying westerlies are too weak to allow much vertical propagation of the orographic gravity waves to the mesosphere. NGWD is primarily responsible for driving the circulation that results in the descent of CO from the thermosphere following the warmings. Zonal mean mesospheric winds and temperatures in all simulations are shown to be strongly constrained by (i.e. slaved to) the stratosphere. Finally, it is demonstrated that the responses to OGWD and NGWD are non-additive due to their dependence and influence on the background winds and temperatures.

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It is well known that there is a dynamic relationship between cerebral blood flow (CBF) and cerebral blood volume (CBV). With increasing applications of functional MRI, where the blood oxygen-level-dependent signals are recorded, the understanding and accurate modeling of the hemodynamic relationship between CBF and CBV becomes increasingly important. This study presents an empirical and data-based modeling framework for model identification from CBF and CBV experimental data. It is shown that the relationship between the changes in CBF and CBV can be described using a parsimonious autoregressive with exogenous input model structure. It is observed that neither the ordinary least-squares (LS) method nor the classical total least-squares (TLS) method can produce accurate estimates from the original noisy CBF and CBV data. A regularized total least-squares (RTLS) method is thus introduced and extended to solve such an error-in-the-variables problem. Quantitative results show that the RTLS method works very well on the noisy CBF and CBV data. Finally, a combination of RTLS with a filtering method can lead to a parsimonious but very effective model that can characterize the relationship between the changes in CBF and CBV.

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The temporal relationship between changes in cerebral blood flow (CBF) and cerebral blood volume (CBV) is important in the biophysical modeling and interpretation of the hemodynamic response to activation, particularly in the context of magnetic resonance imaging and the blood oxygen level-dependent signal. Grubb et al. (1974) measured the steady state relationship between changes in CBV and CBF after hypercapnic challenge. The relationship CBV proportional to CBFPhi has been used extensively in the literature. Two similar models, the Balloon (Buxton et al., 1998) and the Windkessel (Mandeville et al., 1999), have been proposed to describe the temporal dynamics of changes in CBV with respect to changes in CBF. In this study, a dynamic model extending the Windkessel model by incorporating delayed compliance is presented. The extended model is better able to capture the dynamics of CBV changes after changes in CBF, particularly in the return-to-baseline stages of the response.

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A recent nonlinear system by Friston et al. (2000. NeuroImage 12: 466–477) links the changes in BOLD response to changes in neural activity. The system consists of five subsystems, linking: (1) neural activity to flow changes; (2) flow changes to oxygen delivery to tissue; (3) flow changes to changes in blood volume and venous outflow; (4) changes in flow, volume, and oxygen extraction fraction to deoxyhemoglobin changes; and finally (5) volume and deoxyhemoglobin changes to the BOLD response. Friston et al. exploit, in subsystem 2, a model by Buxton and Frank coupling flow changes to changes in oxygen metabolism which assumes tissue oxygen concentration to be close to zero. We describe below a model of the coupling between flow and oxygen delivery which takes into account the modulatory effect of changes in tissue oxygen concentration. The major development has been to extend the original Buxton and Frank model for oxygen transport to a full dynamic capillary model making the model applicable to both transient and steady state conditions. Furthermore our modification enables us to determine the time series of CMRO2 changes under different conditions, including CO2 challenges. We compare the differences in the performance of the “Friston system” using the original model of Buxton and Frank and that of our model. We also compare the data predicted by our model (with appropriate parameters) to data from a series of OIS studies. The qualitative differences in the behaviour of the models are exposed by different experimental simulations and by comparison with the results of OIS data from brief and extended stimulation protocols and from experiments using hypercapnia.

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Initial results are presented from a middle atmosphere extension to a version of the European Centre For Medium Range Weather Forecasting tropospheric model. The extended version of the model has been developed as part of the UK Universities Global Atmospheric Modelling Project and extends from the ground to approximately 90 km. A comprehensive solar radiation scheme is included which uses monthly averaged climatological ozone values. A linearised infrared cooling scheme is employed. The basic climatology of the model is described; the parametrization of drag due to orographically forced gravity waves is shown to have a dramatic effect on the simulations of the winter hemisphere.

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14C-dated pollen and lake-level data from Europe are used to assess the spatial patterns of climate change between 6000 yr BP and present, as simulated by the NCAR CCM1 (National Center for Atmospheric Research, Community Climate Model, version 1) in response to the change in the Earth’s orbital parameters during this perod. First, reconstructed 6000 yr BP values of bioclimate variables obtained from pollen and lake-level data with the constrained-analogue technique are compared with simulated values. Then a 6000 yr BP biome map obtained from pollen data with an objective biome reconstruction (biomization) technique is compared with BIOME model results derived from the same simulation. Data and simulations agree in some features: warmer-than-present growing seasons in N and C Europe allowed forests to extend further north and to higher elevations than today, and warmer winters in C and E Europe prevented boreal conifers from spreading west. More generally, however, the agreement is poor. Predominantly deciduous forest types in Fennoscandia imply warmer winters than the model allows. The model fails to simulate winters cold enough, or summers wet enough, to allow temperate deciduous forests their former extended distribution in S Europe, and it incorrectly simulates a much expanded area of steppe vegetation in SE Europe. Similar errors have also been noted in numerous 6000 yr BP simulations with prescribed modern sea surface temperatures. These errors are evidently not resolved by the inclusion of interactive sea-surface conditions in the CCM1. Accurate representation of mid-Holocene climates in Europe may require the inclusion of dynamical ocean–atmosphere and/or vegetation–atmosphere interactions that most palaeoclimate model simulations have so far disregarded.

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A data insertion method, where a dispersion model is initialized from ash properties derived from a series of satellite observations, is used to model the 8 May 2010 Eyjafjallajökull volcanic ash cloud which extended from Iceland to northern Spain. We also briefly discuss the application of this method to the April 2010 phase of the Eyjafjallajökull eruption and the May 2011 Grímsvötn eruption. An advantage of this method is that very little knowledge about the eruption itself is required because some of the usual eruption source parameters are not used. The method may therefore be useful for remote volcanoes where good satellite observations of the erupted material are available, but little is known about the properties of the actual eruption. It does, however, have a number of limitations related to the quality and availability of the observations. We demonstrate that, using certain configurations, the data insertion method is able to capture the structure of a thin filament of ash extending over northern Spain that is not fully captured by other modeling methods. It also verifies well against the satellite observations according to the quantitative object-based quality metric, SAL—structure, amplitude, location, and the spatial coverage metric, Figure of Merit in Space.

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In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the exponentiated Weibull distribution is proposed for modeling interval-censored data. We show that the proposed log-exponentiated Weibull regression model for interval-censored data represents a parametric family of models that include other regression models that are broadly used in lifetime data analysis. Assuming the use of interval-censored data, we employ a frequentist analysis, a jackknife estimator, a parametric bootstrap and a Bayesian analysis for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Furthermore, for different parameter settings, sample sizes and censoring percentages, various simulations are performed; in addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to a modified deviance residual in log-exponentiated Weibull regression models for interval-censored data. (C) 2009 Elsevier B.V. All rights reserved.

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Localization and Mapping are two of the most important capabilities for autonomous mobile robots and have been receiving considerable attention from the scientific computing community over the last 10 years. One of the most efficient methods to address these problems is based on the use of the Extended Kalman Filter (EKF). The EKF simultaneously estimates a model of the environment (map) and the position of the robot based on odometric and exteroceptive sensor information. As this algorithm demands a considerable amount of computation, it is usually executed on high end PCs coupled to the robot. In this work we present an FPGA-based architecture for the EKF algorithm that is capable of processing two-dimensional maps containing up to 1.8 k features at real time (14 Hz), a three-fold improvement over a Pentium M 1.6 GHz, and a 13-fold improvement over an ARM920T 200 MHz. The proposed architecture also consumes only 1.3% of the Pentium and 12.3% of the ARM energy per feature.

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We construct static soliton solutions with non-zero Hopf topological charges to a theory which is the extended Skyrme-Faddeev model with a further quartic term in derivatives. We use an axially symmetric ansatz based on toroidal coordinates, and solve the resulting two coupled nonlinear partial differential equations in two variables by a successive over-relaxation method. We construct numerical solutions with the Hopf charge up to 4. The solutions present an interesting behavior under the changes of a special combination of the coupling constants of the quartic terms.