90 resultados para Data and Information Technology


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Svalgaard and Cliver (2010) recently reported a consensus between the various reconstructions of the heliospheric field over recent centuries. This is a significant development because, individually, each has uncertainties introduced by instrument calibration drifts, limited numbers of observatories, and the strength of the correlations employed. However, taken collectively, a consistent picture is emerging. We here show that this consensus extends to more data sets and methods than reported by Svalgaard and Cliver, including that used by Lockwood et al. (1999), when their algorithm is used to predict the heliospheric field rather than the open solar flux. One area where there is still some debate relates to the existence and meaning of a floor value to the heliospheric field. From cosmogenic isotope abundances, Steinhilber et al. (2010) have recently deduced that the near-Earth IMF at the end of the Maunder minimum was 1.80 ± 0.59 nT which is considerably lower than the revised floor of 4nT proposed by Svalgaard and Cliver. We here combine cosmogenic and geomagnetic reconstructions and modern observations (with allowance for the effect of solar wind speed and structure on the near-Earth data) to derive an estimate for the open solar flux of (0.48 ± 0.29) × 1014 Wb at the end of the Maunder minimum. By way of comparison, the largest and smallest annual means recorded by instruments in space between 1965 and 2010 are 5.75 × 1014 Wb and 1.37 × 1014 Wb, respectively, set in 1982 and 2009, and the maximum of the 11 year running means was 4.38 × 1014 Wb in 1986. Hence the average open solar flux during the Maunder minimum is found to have been 11% of its peak value during the recent grand solar maximum.

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Satellite measurements and numerical forecast model reanalysis data are used to compute an updated estimate of the cloud radiative effect on the global multi-annual mean radiative energy budget of the atmosphere and surface. The cloud radiative cooling effect through reflection of shortwave radiation dominates over the longwave heating effect, resulting in a net cooling of the climate system of –21 Wm-2. The shortwave radiative effect of cloud is primarily manifest as a reduction in the solar radiation absorbed at the surface of -53 Wm-2. Clouds impact longwave radiation by heating the moist tropical atmosphere (up to around 40 Wm-2 for global annual means) while enhancing the radiative cooling of the atmosphere over other regions, in particular higher latitudes and sub-tropical marine stratocumulus regimes. While clouds act to cool the climate system during the daytime, the cloud greenhouse effect heats the climate system at night. The influence of cloud radiative effect on determining cloud feedbacks and changes in the water cycle are discussed.

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It is indisputable that climate is an important factor in many livestock diseases. Nevertheless, our knowledge of the impact of climate change on livestock infectious diseases is much less certain.Therefore, the aim of the article is to conduct a systematic review of the literature on the topic utilizing available retrospective data and information. Across a corpus of 175 formal publications,limited empirical evidence was offered to underpin many of the main arguments. The literature reviewed was highly polarized and often inconsistent regarding what the future may hold. Historical explorations were rare. However, identifying past drivers to livestock disease may not fully capture the extent that new and unknown drivers will influence future change. As such, our current predictive capacity is low. We offer a number of recommendations to strengthen this capacity in the coming years. We conclude that our current approach to research on the topic is limiting and unlikely to yield sufficient, actionable evidence to inform future praxis. Therefore, we argue for the creation of a reflexive, knowledge-based system, underpinned by a collective intelligence framework to support the drawing of inferences across the literature.

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This paper investigates the effect of choices of model structure and scale in development viability appraisal. The paper addresses two questions concerning the application of development appraisal techniques to viability modelling within the UK planning system. The first relates to the extent to which, given intrinsic input uncertainty, the choice of model structure significantly affects model outputs. The second concerns the extent to which, given intrinsic input uncertainty, the level of model complexity significantly affects model outputs. Monte Carlo simulation procedures are applied to a hypothetical development scheme in order to measure the effects of model aggregation and structure on model output variance. It is concluded that, given the particular scheme modelled and unavoidably subjective assumptions of input variance, simple and simplistic models may produce similar outputs to more robust and disaggregated models.

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This paper summarizes and analyses available data on the surface energy balance of Arctic tundra and boreal forest. The complex interactions between ecosystems and their surface energy balance are also examined, including climatically induced shifts in ecosystem type that might amplify or reduce the effects of potential climatic change. High latitudes are characterized by large annual changes in solar input. Albedo decreases strongly from winter, when the surface is snow-covered, to summer, especially in nonforested regions such as Arctic tundra and boreal wetlands. Evapotranspiration (QE) of high-latitude ecosystems is less than from a freely evaporating surface and decreases late in the season, when soil moisture declines, indicating stomatal control over QE, particularly in evergreen forests. Evergreen conifer forests have a canopy conductance half that of deciduous forests and consequently lower QE and higher sensible heat flux (QH). There is a broad overlap in energy partitioning between Arctic and boreal ecosystems, although Arctic ecosystems and light taiga generally have higher ground heat flux because there is less leaf and stem area to shade the ground surface, and the thermal gradient from the surface to permafrost is steeper. Permafrost creates a strong heat sink in summer that reduces surface temperature and therefore heat flux to the atmosphere. Loss of permafrost would therefore amplify climatic warming. If warming caused an increase in productivity and leaf area, or fire caused a shift from evergreen to deciduous forest, this would increase QE and reduce QH. Potential future shifts in vegetation would have varying climate feedbacks, with largest effects caused by shifts from boreal conifer to shrubland or deciduous forest (or vice versa) and from Arctic coastal to wet tundra. An increase of logging activity in the boreal forests appears to reduce QE by roughly 50% with little change in QH, while the ground heat flux is strongly enhanced.

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