O futuro das ideias: análise estrutural & incertezas-críticas prospectivas para think tanks

O objetivo deste trabalho é identificar as incertezas-críticas prospectivas para fhínk fanks, importante subsídio na elaboração de cenários prospectivos para essas organizações. O enfoque é qualitativo: os dados, coletados por bibliografia e em entrevistas com executivos estratégicos da Fundação Getulio Vargas e especialistas internacionais, foram tratados pelo método da Análise Estrutural. Para tanto, utilizouse o Modelo URCA (MARQUES, 1988). Acredita-se tratar de abordagem inédita na área, pois registro de Análises Prospectivas para thínk tanks não foram localizados. A base teórica analisa diversas definições e classificações de fhínk fanks, identifica atributos comuns a tais conceitos e, a partir deste referencial, apresenta a definição de thínk tank, objeto deste estudo. Em seguida, a partir dos dados coletados, são descritas 21 variáveis prospectivas. Essa lista inicial de variáveis é submetida ao Modelo URCA de Análise Estrutural, gerando, como resultado, oito incertezascríticas prospectivas para thínk fanks: Internacionalização de thínk fanks; Globalização da agenda; Projeção internacional das nações; Concorrência entre thínk tanks; Concorrência de organizações não-governamentais, consultorias, web e similares; Quadro técnico; Corpo dirigente; e Diversificação e sustentação financeiras.

The Tevatron Higgs exclusion limits and theoretical uncertainties: A critical appraisal

We examine the exclusion limits set by the CDF and D0 experiments on the Standard Model Higgs boson mass from their searches at the Tevatron in the light of large theoretical uncertainties on the signal and background cross sections. We show that when these uncertainties are consistently taken into account, the sensitivity of the experiments becomes significantly lower and the currently excluded mass range M-H = 158-175 GeV could be entirely reopened. The necessary luminosity required to recover the current sensitivity is found to be a factor of two higher than the present one. (C) 2011 Elsevier B.V. All rights reserved.

Identification of critical input variables for risk-based cost estimates for road maintenance and rehabilitation

An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.

Observation of the doubling of critical exponents in reentrant phase transitions

Electrical resistance (R) measurements are reported for ternary mixtures of 3-methylpyridine, water and heavy water as a function of temperature (T) and heavy water content in total water. These mixtures exhibit a limited two-phase region marked by a loop size (ΔT) that goes to zero as the double critical point (DCP) is approached. The measurements scanned the ΔT range 1.010°C less-than-or-equals, slant ΔT less-than-or-equals, slant 77.5°C. The critical exponent (θ), which signifies the divergence of ∂R/∂T, doubles within our experimental uncertainties as the DCP is reached very closely.

I Cannot Tell: Edward Thomas's Uncertainties

Poster, Jeremy, 'I Cannot Tell: Edward Thomas's Uncertainties', In: 'Branch-Lines: Edward Thomas and Contemporary Poetry', Guy Cuthbertson & Lucy Newlyn (eds), (London: Enitharmon Press), pp.264, 2007 RAE2008

Approaches to the Implementation of the Water Framework Directive: Targeting Mitigation Measures at Critical Source Areas of Diffuse Phosphorus in Irish Catchments

The Water Framework Directive (WFD) has initiated a shift towards a targeted approach to implementation through its focus on river basin districts as management units and the natural ecological characteristics of waterbodies. Due to its role in eutrophication, phosphorus (P) has received considerable attention, resulting in a significant body of research, which now forms the evidence base for the programme of measures (POMs) adopted in WFD River Basin Management Plans (RBMP). Targeting POMs at critical sources areas (CSAs) of P could significantly improve environmental efficiency and cost effectiveness of proposed mitigation strategies. This paper summarises the progress made towards targeting mitigation measures at CSAs in Irish catchments. A review of current research highlights that knowledge related to P export at field scale is relatively comprehensive however; the availability of site-specific data and tools limits widespread identification of CSA at this scale. Increasing complexity of hydrological processes at larger scales limits accurate identification of CSA at catchment scale. Implementation of a tiered approach, using catchment scale tools in conjunction with field-by-field surveys could decrease uncertainty and provide a more practical and cost effective method of delineating CSA in a range of catchments. Despite scientific and practical uncertainties, development of a tiered CSA-based approach to assist in the development of supplementary measures would provide a means of developing catchment-specific and cost-effective programmes of measures for diffuse P. The paper presents a conceptual framework for such an approach, which would have particular relevance for the development of supplementary measures in High Status Waterbodies (HSW). The cost and resources necessary for implementation are justified based on HSWs’ value as undisturbed reference condition ecosystems.

Evidencing reflective practice in social work education: Theoretical uncertainties and practical challenges

Reflective practice has become an increasingly influential idea in social work education and, in the UK context, it has recently been acknowledged as key to ensuring that social workers are better equipped to engage in complex decision making and effective practice. However, there remains a lack of clarity about how this concept is defined and operationalised in teaching and learning and there has been little systematic empirical examination of its utility in facilitating professional development. Drawing on research with undergraduates at Queen's University Belfast, this paper aims to develop understanding of students' experience of reflective practice. The results suggest that agency systems that have become over-reliant on rules and procedures present formidable obstacles to learning both at an individual and at an organisational level. The paper argues that the relationship between how reflective practice is taught and how it is enacted in practice needs to be better understood if such obstacles are to be overcome. The paper concludes by considering the implications of the findings for developing reflective practice in social work education and practice and highlights the challenges that need to be addressed if reflection and critical thinking are to become more firmly embedded within agency systems and practice cultures.

Identifying the critical parameters of a cyanobacterial growth and movement model by using generalised sensitivity analysis

Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling of cyanobacteria in freshwaters is an important tool for understanding their population dynamics and predicting the location and timing of the bloom events in lakes and rivers. A new deterministic-mathematical model was developed, which simulates the growth and movement of cyanobacterial blooms in river systems. The model focuses on the mathematical description of the bloom formation, vertical migration and lateral transport of colonies within river environments by taking into account the major factors that affect the cyanobacterial bloom formation in rivers including, light, nutrients and temperature. A technique called generalised sensitivity analysis was applied to the model to identify the critical parameter uncertainties in the model and investigates the interaction between the chosen parameters of the model. The result of the analysis suggested that 8 out of 12 parameters were significant in obtaining the observed cyanobacterial behaviour in a simulation. It was found that there was a high degree of correlation between the half-saturation rate constants used in the model.

Quantifying uncertainty in critical loads: (A) literature review

Critical loads are the basis for policies controlling emissions of acidic substances in Europe. The implementation of these policies involves large expenditures, and it is reasonable for policymakers to ask what degree of certainty can be attached to the underlying critical load and exceedance estimates. This paper is a literature review of studies which attempt to estimate the uncertainty attached to critical loads. Critical load models and uncertainty analysis are briefly outlined. Most studies have used Monte Carlo analysis of some form to investigate the propagation of uncertainties in the definition of the input parameters through to uncertainties in critical loads. Though the input parameters are often poorly known, the critical load uncertainties are typically surprisingly small because of a "compensation of errors" mechanism. These results depend on the quality of the uncertainty estimates of the input parameters, and a "pedigree" classification for these is proposed. Sensitivity analysis shows that some input parameters are more important in influencing critical load uncertainty than others, but there have not been enough studies to form a general picture. Methods used for dealing with spatial variation are briefly discussed. Application of alternative models to the same site or modifications of existing models can lead to widely differing critical loads, indicating that research into the underlying science needs to continue.

Quantifying uncertainty in critical loads: (B) acidity mass balance critical loads on a sensitive site

This paper reports an uncertainty analysis of critical loads for acid deposition for a site in southern England, using the Steady State Mass Balance Model. The uncertainty bounds, distribution type and correlation structure for each of the 18 input parameters was considered explicitly, and overall uncertainty estimated by Monte Carlo methods. Estimates of deposition uncertainty were made from measured data and an atmospheric dispersion model, and hence the uncertainty in exceedance could also be calculated. The uncertainties of the calculated critical loads were generally much lower than those of the input parameters due to a "compensation of errors" mechanism - coefficients of variation ranged from 13% for CLmaxN to 37% for CL(A). With 1990 deposition, the probability that the critical load was exceeded was > 0.99; to reduce this probability to 0.50, a 63% reduction in deposition is required; to 0.05, an 82% reduction. With 1997 deposition, which was lower than that in 1990, exceedance probabilities declined and uncertainties in exceedance narrowed as deposition uncertainty had less effect. The parameters contributing most to the uncertainty in critical loads were weathering rates, base cation uptake rates, and choice of critical chemical value, indicating possible research priorities. However, the different critical load parameters were to some extent sensitive to different input parameters. The application of such probabilistic results to environmental regulation is discussed.

Estimating uncertainty in terrestrial critical loads and their exceedances at four sites in the UK

Critical loads are the basis for policies controlling emissions of acidic substances in Europe and elsewhere. They are assessed by several elaborate and ingenious models, each of which requires many parameters, and have to be applied on a spatially-distributed basis. Often the values of the input parameters are poorly known, calling into question the validity of the calculated critical loads. This paper attempts to quantify the uncertainty in the critical loads due to this "parameter uncertainty", using examples from the UK. Models used for calculating critical loads for deposition of acidity and nitrogen in forest and heathland ecosystems were tested at four contrasting sites. Uncertainty was assessed by Monte Carlo methods. Each input parameter or variable was assigned a value, range and distribution in an objective a fashion as possible. Each model was run 5000 times at each site using parameters sampled from these input distributions. Output distributions of various critical load parameters were calculated. The results were surprising. Confidence limits of the calculated critical loads were typically considerably narrower than those of most of the input parameters. This may be due to a "compensation of errors" mechanism. The range of possible critical load values at a given site is however rather wide, and the tails of the distributions are typically long. The deposition reductions required for a high level of confidence that the critical load is not exceeded are thus likely to be large. The implication for pollutant regulation is that requiring a high probability of non-exceedance is likely to carry high costs. The relative contribution of the input variables to critical load uncertainty varied from site to site: any input variable could be important, and thus it was not possible to identify variables as likely targets for research into narrowing uncertainties. Sites where a number of good measurements of input parameters were available had lower uncertainties, so use of in situ measurement could be a valuable way of reducing critical load uncertainty at particularly valuable or disputed sites. From a restricted number of samples, uncertainties in heathland critical loads appear comparable to those of coniferous forest, and nutrient nitrogen critical loads to those of acidity. It was important to include correlations between input variables in the Monte Carlo analysis, but choice of statistical distribution type was of lesser importance. Overall, the analysis provided objective support for the continued use of critical loads in policy development. (c) 2007 Elsevier B.V. All rights reserved.

The futures of construction: A critical review of construction future studies

Anticipating the future is increasingly being seen as a useful way to align, direct and improve current organizational strategy. Several such 'future studies' have been produced which envision various construction industry scenarios which result from technological and socio-economic trends and influences. Thirteen construction-related future studies are critically reviewed. Most studies fail to address the complexities and uncertainties of both the present and the future, and fail to explore the connections between global, local, construction-specific and more widespread factors. The methodological approaches used in these studies do not generate any significantly different advice or recommendations for the industry than those emerging from the much larger canon of non-future oriented construction research. As such, these reports are less about the future than the present. If future studies are to make a worthwhile contribution to construction, it is critical that they develop our appreciation of the practical ability of stakeholders to influence some aspects of the future and not others, and an awareness of the competing agendas and the relative benefits and disadvantages of specific futures within the construction sector. Only then can future studies provide insights and help in preparing for the opportunities and threats the future may bring.

The atmospheric impact of uncertainties in recent Arctic Sea ice reconstructions

There are significant discrepancies between observational datasets of Arctic sea ice concentrations covering the last three decades, which result in differences of over 20% in Arctic summer sea ice extent/area and 5%–10% in winter. Previous modeling studies have shown that idealized sea ice anomalies have the potential for making a substantial impact on climate. In this paper, this theory is further developed by performing a set of simulations using the third Hadley Centre Coupled Atmospheric Model (HadAM3). The model was driven with monthly climatologies of sea ice fractions derived from three of these records to investigate potential implications of sea ice inaccuracies for climate simulations. The standard sea ice climatology from the Met Office provided a control. This study focuses on the effects of actual inaccuracies of concentration retrievals, which vary spatially and are larger in summer than winter. The smaller sea ice discrepancies in winter have a much larger influence on climate than the much greater summer sea ice differences. High sensitivity to sea ice prescription was observed, even though no SST feedbacks were included. Significant effects on surface fields were observed in the Arctic, North Atlantic, and North Pacific. Arctic average surface air temperature anomalies in winter vary by 2.5°C, and locally exceed 12°C. Arctic mean sea level pressure varies by up to 5 mb locally. Anomalies extend to 45°N over North America and Eurasia but not to lower latitudes, and with limited changes in circulation above the boundary layer. No statistically significant impact on climate variability was simulated, in terms of the North Atlantic Oscillation. Results suggest that the uncertainty in summer sea ice prescription is not critical but that winter values require greater accuracy, with the caveats that the influences of ocean–sea ice feedbacks were not included in this study.

Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment

Increasing concentrations of greenhouse gases in the atmosphere are expected to modify the global water cycle with significant consequences for terrestrial hydrology. We assess the impact of climate change on hydrological droughts in a multimodel experiment including seven global impact models (GIMs) driven by bias-corrected climate from five global climate models under four representative concentration pathways (RCPs). Drought severity is defined as the fraction of land under drought conditions. Results show a likely increase in the global severity of hydrological drought at the end of the 21st century, with systematically greater increases for RCPs describing stronger radiative forcings. Under RCP8.5, droughts exceeding 40% of analyzed land area are projected by nearly half of the simulations. This increase in drought severity has a strong signal-to-noise ratio at the global scale, and Southern Europe, the Middle East, the Southeast United States, Chile, and South West Australia are identified as possible hotspots for future water security issues. The uncertainty due to GIMs is greater than that from global climate models, particularly if including a GIM that accounts for the dynamic response of plants to CO2 and climate, as this model simulates little or no increase in drought frequency. Our study demonstrates that different representations of terrestrial water-cycle processes in GIMs are responsible for a much larger uncertainty in the response of hydrological drought to climate change than previously thought. When assessing the impact of climate change on hydrology, it is therefore critical to consider a diverse range of GIMs to better capture the uncertainty.

A critical evaluation of the ability of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) thermal infrared red-green-blue rendering to identify dust events: theoretical analysis

Using a combination of idealized radiative transfer simulations and a case study from the first field campaign of the Saharan Mineral Dust Experiment (SAMUM) in southern Morocco, this paper provides a systematic assessment of the limitations of the widely used Spinning Enhanced Visible and Infrared Imager (SEVIRI) red-green-blue (RGB) thermal infrared dust product. Both analyses indicate that the ability of the product to identify dust, via its characteristic pink coloring, is strongly dependent on the column water vapor, the lower tropospheric lapse rate, and dust altitude. In particular, when column water vapor exceeds ∼20–25 mm, dust presence, even for visible optical depths of the order 0.8, is effectively masked. Variability in dust optical properties also has a marked impact on the imagery, primarily as a result of variability in dust composition. There is a moderate sensitivity to the satellite viewing geometry, particularly in moist conditions. The underlying surface can act to confound the signal seen through variations in spectral emissivity, which are predominantly manifested in the 8.7μm SEVIRI channel. In addition, if a temperature inversion is present, typical of early morning conditions over the Sahara and Sahel, an increased dust loading can actually reduce the pink coloring of the RGB image compared to pristine conditions. Attempts to match specific SEVIRI observations to simulations using SAMUM measurements are challenging because of high uncertainties in surface skin temperature and emissivity. Recommendations concerning the use and interpretation of the SEVIRI RGB imagery are provided on the basis of these findings.