90 resultados para Environments with time-varying ocean currents


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The DAPPLE (Dispersion of Air Pollutants and their Penetration into the Local Environment) project seeks to characterise near-field urban atmospheric dispersion using a multidisciplinary approach. In this paper we report on the first tracer dispersion experiment carried out in May 2003. Results of concurrent meteorological measurements are presented. Variations of receptor tracer concentration with time are presented. Meteorological observations suggest that in-street channelling and flow-switching at intersections take place. A comparison between roof top and surface measurements suggest that rapid vertical mixing occurs, and a comparison between a simple dispersion model and maximum concentrations observed are presented

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Scintillometry is an established technique for determining large areal average sensible heat fluxes. The scintillometer measurement is related to sensible heat flux via Monin–Obukhov similarity theory, which was developed for ideal homogeneous land surfaces. In this study it is shown that judicious application of scintillometry over heterogeneous mixed agriculture on undulating topography yields valid results when compared to eddy covariance (EC). A large aperture scintillometer (LAS) over a 2.4 km path was compared with four EC stations measuring sensible (H) and latent (LvE) heat fluxes over different vegetation (cereals and grass) which when aggregated were representative of the LAS source area. The partitioning of available energy into H and LvE varied strongly for different vegetation types, with H varying by a factor of three between senesced winter wheat and grass pasture. The LAS derived H agrees (one-to-one within the experimental uncertainty) with H aggregated from EC with a high coefficient of determination of 0.94. Chronological analysis shows individual fields may have a varying contribution to the areal average sensible heat flux on short (weekly) time scales due to phenological development and changing soil moisture conditions. Using spatially aggregated measurements of net radiation and soil heat flux with H from the LAS, the areal averaged latent heat flux (LvELAS) was calculated as the residual of the surface energy balance. The regression of LvELAS against aggregated LvE from the EC stations has a slope of 0.94, close to ideal, and demonstrates that this is an accurate method for the landscape-scale estimation of evaporation over heterogeneous complex topography.

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The evolution of the global orientation parameter for a series of aqueous hydroxypropylcellulose solutions both during and following the cessation of a steady-state shear flow is reported. Time-resolved orientation measurements were made in situ through a novel X-ray rheometer coupled with a two-dimensional electronic X-ray camera, and using an intense X-ray source at the LURE synchrotron. After the cessation of flow, the global orientation decreases from the steady-state orientation level to zero following shear flow at low shear rate or to a small but finite value after flow at a high shear rate. The decrease of orientation with time shows different behaviour, dependent upon the previously applied shear rate.

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This study describes the turbulent processes in the upper ocean boundary layer forced by a constant surface stress in the absence of the Coriolis force using large-eddy simulation. The boundary layer that develops has a two-layer structure, a well-mixed layer above a stratified shear layer. The depth of the mixed layer is approximately constant, whereas the depth of the shear layer increases with time. The turbulent momentum flux varies approximately linearly from the surface to the base of the shear layer. There is a maximum in the production of turbulence through shear at the base of the mixed layer. The magnitude of the shear production increases with time. The increase is mainly a result of the increase in the turbulent momentum flux at the base of the mixed layer due to the increase in the depth of the boundary layer. The length scale for the shear turbulence is the boundary layer depth. A simple scaling is proposed for the magnitude of the shear production that depends on the surface forcing and the average mixed layer current. The scaling can be interpreted in terms of the divergence of a mean kinetic energy flux. A simple bulk model of the boundary layer is developed to obtain equations describing the variation of the mixed layer and boundary layer depths with time. The model shows that the rate at which the boundary layer deepens does not depend on the stratification of the thermocline. The bulk model shows that the variation in the mixed layer depth is small as long as the surface buoyancy flux is small.

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The evaluation of investment fund performance has been one of the main developments of modern portfolio theory. Most studies employ the technique developed by Jensen (1968) that compares a particular fund's returns to a benchmark portfolio of equal risk. However, the standard measures of fund manager performance are known to suffer from a number of problems in practice. In particular previous studies implicitly assume that the risk level of the portfolio is stationary through the evaluation period. That is unconditional measures of performance do not account for the fact that risk and expected returns may vary with the state of the economy. Therefore many of the problems encountered in previous performance studies reflect the inability of traditional measures to handle the dynamic behaviour of returns. As a consequence Ferson and Schadt (1996) suggest an approach to performance evaluation called conditional performance evaluation which is designed to address this problem. This paper utilises such a conditional measure of performance on a sample of 27 UK property funds, over the period 1987-1998. The results of which suggest that once the time varying nature of the funds beta is corrected for, by the addition of the market indicators, the average fund performance show an improvement over that of the traditional methods of analysis.

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Advances in weather and climate research have demonstrated the role of the stratosphere in the Earth system across a wide range of temporal and spatial scales. Stratospheric ozone loss has been identified as a key driver of Southern Hemisphere tropospheric circulation trends, affecting ocean currents and carbon uptake, sea ice, and possibly even the Antarctic ice sheets. Stratospheric variability has also been shown to affect short term and seasonal forecasts, connecting the tropics and midlatitudes and guiding storm track dynamics. The two-way interactions between the stratosphere and the Earth system have motivated the World Climate Research Programme's (WCRP) Stratospheric Processes and Their Role in Climate (SPARC) DynVar activity to investigate the impact of stratospheric dynamics and variability on climate. This assessment will be made possible by two new multi-model datasets. First, roughly 10 models with a well resolved stratosphere are participating in the Coupled Model Intercomparison Project 5 (CMIP5), providing the first multi-model ensemble of climate simulations coupled from the stratopause to the sea floor. Second, the Stratosphere Historical Forecasting Project (SHFP) of WCRP's Climate Variability and predictability (CLIVAR) program is forming a multi-model set of seasonal hindcasts with stratosphere resolving models, revealing the impact of both stratospheric initial conditions and dynamics on intraseasonal prediction. The CMIP5 and SHFP model-data sets will offer an unprecedented opportunity to understand the role of the stratosphere in the natural and forced variability of the Earth system and to determine whether incorporating knowledge of the middle atmosphere improves seasonal forecasts and climate projections. Capsule New modeling efforts will provide unprecedented opportunities to harness our knowledge of the stratosphere to improve weather and climate prediction.

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Aircraft systems are highly nonlinear and time varying. High-performance aircraft at high angles of incidence experience undesired coupling of the lateral and longitudinal variables, resulting in departure from normal controlled � ight. The construction of a robust closed-loop control that extends the stable and decoupled � ight envelope as far as possible is pursued. For the study of these systems, nonlinear analysis methods are needed. Previously, bifurcation techniques have been used mainly to analyze open-loop nonlinear aircraft models and to investigate control effects on dynamic behavior. Linear feedback control designs constructed by eigenstructure assignment methods at a � xed � ight condition are investigated for a simple nonlinear aircraft model. Bifurcation analysis, in conjunction with linear control design methods, is shown to aid control law design for the nonlinear system.

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Aircraft systems are highly nonlinear and time varying. High-performance aircraft at high angles of incidence experience undesired coupling of the lateral and longitudinal variables, resulting in departure from normal controlled flight. The aim of this work is to construct a robust closed-loop control that optimally extends the stable and decoupled flight envelope. For the study of these systems nonlinear analysis methods are needed. Previously, bifurcation techniques have been used mainly to analyze open-loop nonlinear aircraft models and investigate control effects on dynamic behavior. In this work linear feedback control designs calculated by eigenstructure assignment methods are investigated for a simple aircraft model at a fixed flight condition. Bifurcation analysis in conjunction with linear control design methods is shown to aid control law design for the nonlinear system.

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Large-scale ocean transports of heat and freshwater have not been well monitored, and yet the regional budgets of these quantities are important to understanding the role of the oceans in climate and climate change. In contrast, atmospheric heat and freshwater transports are commonly assessed from atmospheric reanalysis products, despite the presence of non-conserving data assimilation based on the wealth of distributed atmospheric observations as constraints. The ability to carry out ocean reanalyses globally at eddy-permitting resolutions of 1/4 ° or better, along with new global ocean observation programs, now makes a similar approach viable for the ocean. In this paper we examine the budgets and transports within a global high resolution ocean model constrained by ocean data assimilation, and compare them with independent oceanic and atmospheric estimates.

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An analysis of observational data in the Barents Sea along a meridian at 33°30' E between 70°30' and 72°30' N has reported a negative correlation between El Niño/La Niña Southern Oscillation (ENSO) events and water temperature in the top 200 m: the temperature drops about 0.5 °C during warm ENSO events while during cold ENSO events the top 200 m layer of the Barents Sea is warmer. Results from 1 and 1/4-degree global NEMO models show a similar response for the whole Barents Sea. During the strong warm ENSO event in 1997–1998 an anomalous anticyclonic atmospheric circulation over the Barents Sea enhances heat loses, as well as substantially influencing the Barents Sea inflow from the North Atlantic, via changes in ocean currents. Under normal conditions along the Scandinavian peninsula there is a warm current entering the Barents Sea from the North Atlantic, however after the 1997–1998 event this current is weakened. During 1997–1998 the model annual mean temperature in the Barents Sea is decreased by about 0.8 °C, also resulting in a higher sea ice volume. In contrast during the cold ENSO events in 1999–2000 and 2007–2008, the model shows a lower sea ice volume, and higher annual mean temperatures in the upper layer of the Barents Sea of about 0.7 °C. An analysis of model data shows that the strength of the Atlantic inflow in the Barents Sea is the main cause of heat content variability, and is forced by changing pressure and winds in the North Atlantic. However, surface heat-exchange with the atmosphere provides the means by which the Barents sea heat budget relaxes to normal in the subsequent year after the ENSO events.

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Pocket Data Mining (PDM) is our new term describing collaborative mining of streaming data in mobile and distributed computing environments. With sheer amounts of data streams are now available for subscription on our smart mobile phones, the potential of using this data for decision making using data stream mining techniques has now been achievable owing to the increasing power of these handheld devices. Wireless communication among these devices using Bluetooth and WiFi technologies has opened the door wide for collaborative mining among the mobile devices within the same range that are running data mining techniques targeting the same application. This paper proposes a new architecture that we have prototyped for realizing the significant applications in this area. We have proposed using mobile software agents in this application for several reasons. Most importantly the autonomic intelligent behaviour of the agent technology has been the driving force for using it in this application. Other efficiency reasons are discussed in details in this paper. Experimental results showing the feasibility of the proposed architecture are presented and discussed.

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In this paper, we examine the temporal stability of the evidence for two commodity futures pricing theories. We investigate whether the forecast power of commodity futures can be attributed to the extent to which they exhibit seasonality and we also consider whether there are time varying parameters or structural breaks in these pricing relationships. Compared to previous studies, we find stronger evidence of seasonality in the basis, which supports the theory of storage. The power of the basis to forecast subsequent price changes is also strengthened, while results on the presence of a risk premium are inconclusive. In addition, we show that the forecasting power of commodity futures cannot be attributed to the extent to which they exhibit seasonality. We find that in most cases where structural breaks occur, only changes in the intercepts and not the slopes are detected, illustrating that the forecast power of the basis is stable over different economic environments.

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A fingerprint method for detecting anthropogenic climate change is applied to new simulations with a coupled ocean-atmosphere general circulation model (CGCM) forced by increasing concentrations of greenhouse gases and aerosols covering the years 1880 to 2050. In addition to the anthropogenic climate change signal, the space-time structure of the natural climate variability for near-surface temperatures is estimated from instrumental data over the last 134 years and two 1000 year simulations with CGCMs. The estimates are compared with paleoclimate data over 570 years. The space-time information on both the signal and the noise is used to maximize the signal-to-noise ratio of a detection variable obtained by applying an optimal filter (fingerprint) to the observed data. The inclusion of aerosols slows the predicted future warming. The probability that the observed increase in near-surface temperatures in recent decades is of natural origin is estimated to be less than 5%. However, this number is dependent on the estimated natural variability level, which is still subject to some uncertainty.

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We investigate the role of the anthropogenic heat flux on the urban heat island of London. To do this, the time-varying anthropogenic heat flux is added to an urban surface-energy balance parametrization, the Met Office–Reading Urban Surface Exchange Scheme (MORUSES), implemented in a 1 km resolution version of the UK Met Office Unified Model. The anthropogenic heat flux is derived from energy-demand data for London and is specified on the model's 1 km grid; it includes variations on diurnal and seasonal time-scales. We contrast a spring case with a winter case, to illustrate the effects of the larger anthropogenic heat flux in winter and the different roles played by thermodynamics in the different seasons. The surface-energy balance channels the anthropogenic heat into heating the urban surface, which warms slowly because of the large heat capacity of the urban surface. About one third of this additional warming goes into increasing the outgoing long-wave radiation and only about two thirds goes into increasing the sensible heat flux that warms the atmosphere. The anthropogenic heat flux has a larger effect on screen-level temperatures in the winter case, partly because the anthropogenic flux is larger then and partly because the boundary layer is shallower in winter. For the specific winter case studied here, the anthropogenic heat flux maintains a well-mixed boundary layer through the whole night over London, whereas the surrounding rural boundary layer becomes strongly stably stratified. This finding is likely to have important implications for air quality in winter. On the whole, inclusion of the anthropogenic heat flux improves the comparison between model simulations and measurements of screen-level temperature slightly and indicates that the anthropogenic heat flux is beginning to be an important factor in the London urban heat island.

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Rafting is one of the important deformation mechanisms of sea ice. This process is widespread in the north Caspian Sea, where multiple rafting produces thick sea ice features, which are a hazard to offshore operations. Here we present a one-dimensional, thermal consolidation model for rafted sea ice. We consider the consolidation between the layers of both a two-layer and a three-layer section of rafted sea ice. The rafted ice is assumed to be composed of layers of sea ice of equal thickness, separated by thin layers of ocean water. Results show that the thickness of the liquid layer reduced asymptotically with time, such that there always remained a thin saline liquid layer. We propose that when the liquid layer is equal to the surface roughness the adjacent layers can be considered consolidated. Using parameters representative of the north Caspian, the Arctic, and the Antarctic, our results show that for a choice of standard parameters it took under 15 h for two layers of rafted sea ice to consolidate. Sensitivity studies showed that the consolidation model is highly sensitive to the initial thickness of the liquid layer, the fraction of salt release during freezing, and the height of the surface asperities. We believe that further investigation of these parameters is needed before any concrete conclusions can be drawn about rate of consolidation of rafted sea ice features.