137 resultados para Convection terms


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Transpolar voltages observed during traversals of the polar cap by the Defense Meteorological Satellite Program (DMSP) F-13 spacecraft during 2001 are analyzed using the expanding-contracting polar cap model of ionospheric convection. Each of the 10,216 passes is classified by its substorm phase or as a steady convection event (SCE) by inspection of the AE indices. For all phases, we detect a contribution to the transpolar voltage by reconnection in both the dayside magnetopause and in the crosstail current sheet. Detection of the IMF influence is 97% certain during quiet intervals and >99% certain during substorm/SCE growth phases but falls to 75% in substorm expansion phases: It is only 27% during SCEs. Detection of the influence of the nightside voltage is only 19% certain during growth phases, rising during expansion phases to a peak of 96% in recovery phases: During SCEs, it is >99%. The voltage during SCEs is dominated by the nightside, not the dayside, reconnection. On average, substorm expansion phases halt the growth phase rise in polar cap flux rather than reversing it. The main destruction of the excess open flux takes place during the 6- to 10-hour interval after the recovery phase (as seen in AE) and at a rate which is relatively independent of polar cap flux because the NENL has by then retreated to the far tail. The best estimate of the voltage associated with viscous-like transfer of closed field lines into the tail is around 10 kV.

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The definitions of the base units of the international system of units have been revised many times since the idea of such an international system was first conceived at the time of the French revolution. The objective today is to define all our units in terms of 'invariants of nature', i.e. by referencing our units to the fundamental constants of physics, or the properties of atoms, rather than the characteristics of our planet or of artefacts. This situation is reviewed, particularly in regard to finding a new definition of the kilogram to replace its present definition in terms of a prototype material artefact.

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Atmospheric factors Governing Banded Orographic Convection The three-dimensional structure of shallow orographic convection is investigated through simulations performed with a cloud-resolving numerical model. In moist flows that overcome a given topographic barrier to form statically unstable cap clouds, the organization of the convection depends on both the atmospheric structure and the mechanism by which the convection is initiated. Convection initiated by background thermal fluctuations embedded in the flow over a smooth mountain (without any small-scale topographic features) tends to be cellular and disorganized except that shear-parallel bands may form in flows with strong unidirectional vertical shear. The development of well-organized bands is favored when there is weak static instability inside the cloud and when the dry air surrounding the cloud is strongly stable. These bands move with the flow and distribute their cumulative precipitation evenly over the mountain upslope. Similar shear-parallel bands also develop in flows where convection is initiated by small-scale topographic noise superimposed onto the main mountain profile, but in this case stronger circulations are also triggered that create stationary rainbands parallel to the low-level flow. This second dominant mode, which is less sensitive to the atmospheric structure and the strength of forcing, is triggered by lee waves that form over small-scale topographic bumps near the upstream edge of the main orographic cloud. Due to their stationarity, these flow-parallel bands can produce locally heavy precipitation amounts.

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Radar images and numerical simulations of three shallow convective precipitation events over the Coastal Range in western Oregon are presented. In one of these events, unusually well-defined quasi-stationary banded formations produced large precipitation enhancements in favored locations, while varying degrees of band organization and lighter precipitation accumulations occurred in the other two cases. The difference between the more banded and cellular cases appeared to depend on the vertical shear within the orographic cap cloud and the susceptibility of the flow to convection upstream of the mountain. Numerical simulations showed that the rainbands, which appeared to be shear-parallel convective roll circulations that formed within the unstable orographic cap cloud, developed even over smooth mountains. However, these banded structures were better organized, more stationary, and produced greater precipitation enhancement over mountains with small-scale topographic obstacles. Low-amplitude random topographic roughness elements were found to be just as effective as more prominent subrange-scale peaks at organizing and fixing the location of the orographic rainbands.

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The development of shallow cellular convection in warm orographic clouds is investigated through idealized numerical simulations of moist flow over topography using a cloud-resolving numerical model. Buoyant instability, a necessary element for moist convection, is found to be diagnosed most accurately through analysis of the moist Brunt–Väisälä frequency (N_m) rather than the vertical profile of θ_e. In statically unstable orographic clouds (N_m^2) < 0), additional environmental and terrain-related factors are shown to have major effects on the amount of cellularity that occurs in 2D simulations. One of these factors, the basic-state wind shear, may suppress convection in 2D yet allow for longitudinal convective roll circulations in 3D. The presence of convective structures within an orographic cloud substantially enhanced the maximum rainfall rates, precipitation efficiencies, and precipitation accumulations in all simulations.

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Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

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Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

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The definitions of the base units of the international system of units have been revised many times since the idea of such an international system was first conceived at the time of the French revolution. The objective today is to define all our units in terms of 'invariants of nature', i.e. by referencing our units to the fundamental constants of physics, or the properties of atoms, rather than the characteristics of our planet or of artefacts. This situation is reviewed, particularly in regard to finding a new definition of the kilogram to replace its present definition in terms of a prototype material artefact.

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The high thermal storage capacity of phase change material (PCM) can reduce energy consumption in buildings through energy storage and release when combined with renewable energy sources, night cooling, etc. PCM boards can be used to absorb heat gains during daytime and release heat at night. In this paper, the thermal performance of an environmental chamber fitted with phase change material boards has been investigated. During a full-cycle experiment, i.e. charging–releasing cycle, the PCM boards on a wall can reduce the interior wall surface temperature during the charging process, whereas the PCM wall surface temperature is higher than that of the other walls during the heat releasing process. It is found that the heat flux density of the PCM wall in the melting zone is almost twice as large as that of ordinary wall. Also, the heat-insulation performance of a PCM wall is better than that of an ordinary wall during the charging process, while during the heat discharging process, the PCM wall releases more heat energy. The convective heat transfer coefficient of PCM wall surface calculated using equations for a normal wall material produces an underestimation of this coefficient. The high convective heat transfer coefficient for a PCM wall is due to the increased energy exchange between the wall and indoor air.

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Objectives: To examine doctors' (Experiment 1) and doctors' and lay people's (Experiment 2) interpretations of two sets of recommended verbal labels for conveying information about side effects incidence rates. Method: Both studies used a controlled empirical methodology in which participants were presented with a hypothetical, but realistic, scenario involving a prescribed medication that was said to be associated with either mild or severe side effects. The probability of each side effect was described using one of the five descriptors advocated by the European Union (Experiment 1) or one of the six descriptors advocated in Calman's risk scale (Experiment 2), and study participants were required to estimate (numerically) the probability of each side effect occurring. Key findings: Experiment 1 showed that the doctors significantly overestimated the risk of side effects occurring when interpreting the five EU descriptors, compared with the assigned probability ranges. Experiment 2 showed that both groups significantly overestimated risk when given the six Calman descriptors, although the degree of overestimation was not as great for the doctors as for the lay people. Conclusion: On the basis of our findings, we argue that we are still a long way from achieving a standardised language of risk for use by both professionals and the general public, although there might be more potential for use of standardised terms among professionals. In the meantime, the EU and other regulatory bodies and health professionals should be very cautious about advocating the use of particular verbal labels for describing medication side effects.

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A second order accurate, characteristic-based, finite difference scheme is developed for scalar conservation laws with source terms. The scheme is an extension of well-known second order scalar schemes for homogeneous conservation laws. Such schemes have proved immensely powerful when applied to homogeneous systems of conservation laws using flux-difference splitting. Many application areas, however, involve inhomogeneous systems of conservation laws with source terms, and the scheme presented here is applied to such systems in a subsequent paper.