Spatial variability of flow statistics within regular building arrays

Turbulence statistics obtained by direct numerical simulations are analysed to investigate spatial heterogeneity within regular arrays of building-like cubical obstacles. Two different array layouts are studied, staggered and square, both at a packing density of λp=0.25 . The flow statistics analysed are mean streamwise velocity ( u− ), shear stress ( u′w′−−−− ), turbulent kinetic energy (k) and dispersive stress fraction ( u˜w˜ ). The spatial flow patterns and spatial distribution of these statistics in the two arrays are found to be very different. Local regions of high spatial variability are identified. The overall spatial variances of the statistics are shown to be generally very significant in comparison with their spatial averages within the arrays. Above the arrays the spatial variances as well as dispersive stresses decay rapidly to zero. The heterogeneity is explored further by separately considering six different flow regimes identified within the arrays, described here as: channelling region, constricted region, intersection region, building wake region, canyon region and front-recirculation region. It is found that the flow in the first three regions is relatively homogeneous, but that spatial variances in the latter three regions are large, especially in the building wake and canyon regions. The implication is that, in general, the flow immediately behind (and, to a lesser extent, in front of) a building is much more heterogeneous than elsewhere, even in the relatively dense arrays considered here. Most of the dispersive stress is concentrated in these regions. Considering the experimental difficulties of obtaining enough point measurements to form a representative spatial average, the error incurred by degrading the sampling resolution is investigated. It is found that a good estimate for both area and line averages can be obtained using a relatively small number of strategically located sampling points.

A singular vector perspective of 4DVAR: The spatial structure and evolution of baroclinic weather systems

The extent to which the four-dimensional variational data assimilation (4DVAR) is able to use information about the time evolution of the atmosphere to infer the vertical spatial structure of baroclinic weather systems is investigated. The singular value decomposition (SVD) of the 4DVAR observability matrix is introduced as a novel technique to examine the spatial structure of analysis increments. Specific results are illustrated using 4DVAR analyses and SVD within an idealized 2D Eady model setting. Three different aspects are investigated. The first aspect considers correcting errors that result in normal-mode growth or decay. The results show that 4DVAR performs well at correcting growing errors but not decaying errors. Although it is possible for 4DVAR to correct decaying errors, the assimilation of observations can be detrimental to a forecast because 4DVAR is likely to add growing errors instead of correcting decaying errors. The second aspect shows that the singular values of the observability matrix are a useful tool to identify the optimal spatial and temporal locations for the observations. The results show that the ability to extract the time-evolution information can be maximized by placing the observations far apart in time. The third aspect considers correcting errors that result in nonmodal rapid growth. 4DVAR is able to use the model dynamics to infer some of the vertical structure. However, the specification of the case-dependent background error variances plays a crucial role.

The spatial and temporal shape of oculomotor inhibition

Selecting a stimulus as the target for a goal-directed movement involves inhibiting other competing possible responses. Inhibition has generally proved hard to study behaviorally, because it results in no measurable output. The effect of distractors on the shape of oculomotor and manual trajectories provide evidence of such inhibition. Individual saccades may deviate initially either towards, or away from, a competing distractor - the direction and extent of this deviation depends upon saccade latency, target predictability and the target to distractor separation. The experiment reported here used these effects to show how inhibition of distractor locations develops over time. Distractors could be presented at various distances from unpredictable and predictable targets in two separate experiments. The deviation of saccade trajectories was compared between trials with and without distractors. Inhibition was measured by saccade trajectory deviation. Inhibition was found to increase as the distractor distance from target decreased but was found to increase with saccade latency at all distractor distances (albeit to different peaks). Surprisingly, no differences were found between unpredictable and predictable targets perhaps because our saccade latencies were generally long (similar to 260-280 ms.). We conclude that oculomotor inhibition of saccades to possible target objects involves the same mechanisms for all distractor distances and target types. (C) 2009 Elsevier Ltd. All rights reserved.

Spatial representation and attention in toddlers with Williams syndrome and Down syndrome

The nature of the spatial representations that underlie simple visually guided actions early in life was investigated in toddlers with Williams syndrome (WS), Down syndrome (DS), and healthy chronological age- and mental age-matched controls, through the use of a "double-step" saccade paradigm. The experiment tested the hypothesis that, compared to typically developing infants and toddlers, and toddlers with DS, those with WS display a deficit in using spatial representations to guide actions. Levels of sustained attention were also measured within these groups, to establish whether differences in levels of engagement influenced performance on the double-step saccade task. The results showed that toddlers with WS were unable to combine extra-retinal information with retinal information to the same extent as the other groups, and displayed evidence of other deficits in saccade planning, suggesting a greater reliance on sub-cortical mechanisms than the other populations. Results also indicated that their exploration of the visual environment is less developed. The sustained attention task revealed shorter and fewer periods of sustained attention in toddlers with DS, but not those with WS, suggesting that WS performance on the double-step saccade task is not explained by poorer engagement. The findings are also discussed in relation to a possible attention disengagement deficit in WS toddlers. Our study highlights the importance of studying genetic disorders early in development. (C) 2002 Elsevier Science Ltd. All rights reserved.

Spatial concentration in institutional investment in the UK: some comparisons between the retail and office sectors

Geographic diversity is a fundamental tenet in portfolio management. Yet there is evidence from the US that institutional investors prefer to concentrate their real estate investments in favoured and specific areas as primary locations for the properties that occupy their portfolios. The little work done in the UK draws similar conclusions, but has so far focused only on the office sector; no work has examined this issue for the retail sector. This paper therefore examines the extent of real estate investment concentration in institutional Retail portfolios in the UK at two points in time; 1998 and 2003, and presents some comparisons with equivalent concentrations in the office sector. The findings indicate that retail investment correlates more closely with the UK urban hierarchy than that for offices when measured against employment, and is focused on urban areas with high populations and large population densities which have larger numbers of retail units in which to invest.

Engaging in European spatial planning: a central and Eastern European perspective on the territorial cohesion debate

The following paper sets out to determine the differential extent of the engagement of Central and Eastern European (CEE) member states with the European spatial planning (ESP) debate over territorial cohesion. It focuses on the written statements submitted in response to the European Commission “Green Paper on Territorial Cohesion” consultation in 2009. The geographical distribution of the respondents is analysed, before CEE member states’ responses are examined in detail, to explore the diverse interpretations of the concept of “territorial cohesion” among CEE actors. While the data collection for this paper has been restricted empirically to the consultation process, it reflects its findings in consideration of member states’ engagement with the debate as it manifested before and after the Green Paper. The debate over the exact conceptual and operational “framing” of territorial cohesion, launched by the European Commission's Green Paper, constitutes one of the many arenas through which ESP currently evolves, together with the transnational initiatives developed in the framework of the European Territorial Cooperation objective, the European Observation Network for Territorial Development and Cohesion (ESPON) and the process that recently led to the publication of the Territorial Agenda of the European Union 2020. The paper concludes that the overall level of engagement of CEE actors in ESP is proportionally lower in comparison with that of their northwestern European counterparts. The increasing involvement of some CEE member states within the ESPON 2013 Programme, as well as the activities undertaken by the Hungarian and Polish EU Presidencies in 2011, suggests that this level of CEE engagement is growing albeit differentially.

The engagement of territorial knowledge communities with European spatial planning and the territorial cohesion debate: a Baltic perspective

Recent, dramatic spatial development trends have contributed to the consolidation of a unique territorial governance landscape in the Baltic States. The paper examines the transformation of this evolving institutional landscape for planning practice and knowledge, which has been marked by the disintegration of Soviet institutions and networks, the transition to a market-based economy and the process of accession to the EU. It explores the evolution of territorial knowledge channels in the Baltic States, and the extent and nature of the engagement of actors' communities with the main knowledge arenas and resources of European spatial planning (ESP). The paper concludes that recent shifts in the evolution of these channels suggest the engagement of ESP has concentrated among epistemic communities at State and trans-national levels of territorial governance. The limited policy coordination across a broader spectrum of diverse actors is compounded by institutionally weak and fragmented professional communities of practice, fragmented government structures and marginalized advocacy coalitions.

Dietary levels of pure flavonoids improve spatial memory performance and increase hippocampal brain-derived neurotrophic factor.

Evidence suggests that flavonoid-rich foods are capable of inducing improvements in memory and cognition in animals and humans. However, there is a lack of clarity concerning whether flavonoids are the causal agents in inducing such behavioral responses. Here we show that supplementation with pure anthocyanins or pure flavanols for 6 weeks, at levels similar to that found in blueberry (2% w/w), results in an enhancement of spatial memory in 18 month old rats. Pure flavanols and pure anthocyanins were observed to induce significant improvements in spatial working memory (p = 0.002 and p = 0.006 respectively), to a similar extent to that following blueberry supplementation (p = 0.002). These behavioral changes were paralleled by increases in hippocampal brain-derived neurotrophic factor (R = 0.46, p<0.01), suggesting a common mechanism for the enhancement of memory. However, unlike protein levels of BDNF, the regional enhancement of BDNF mRNA expression in the hippocampus appeared to be predominantly enhanced by anthocyanins. Our data support the claim that flavonoids are likely causal agents in mediating the cognitive effects of flavonoid-rich foods.

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

How large is congressional dependence in agriculture. Bayesian inference about ‘scale’ and ‘scope’ in measuring a spatial externality

The political economy literature on agriculture emphasizes influence over political outcomes via lobbying conduits in general, political action committee contributions in particular and the pervasive view that political preferences with respect to agricultural issues are inherently geographic. In this context, ‘interdependence’ in Congressional vote behaviour manifests itself in two dimensions. One dimension is the intensity by which neighboring vote propensities influence one another and the second is the geographic extent of voter influence. We estimate these facets of dependence using data on a Congressional vote on the 2001 Farm Bill using routine Markov chain Monte Carlo procedures and Bayesian model averaging, in particular. In so doing, we develop a novel procedure to examine both the reliability and the consequences of different model representations for measuring both the ‘scale’ and the ‘scope’ of spatial (geographic) co-relations in voting behaviour.

Sunlit fractions on urban facets: impact of spatial resolution and approach

The extent of the surface area sunlit is critical for radiative energy exchanges and therefore for a wide range of applications that require urban land surface models (ULSM), ranging from human comfort to weather forecasting. Here a computational demanding shadow casting algorithm is used to assess the capability of a simple single-layer urban canopy model, which assumes an infinitely long rotating canyon (ILC), to reproduce sunlit areas on roof and roads over central London. Results indicate that the sunlit roads areas are well-represented but somewhat smaller using an ILC, while sunlit roofs areas are consistently larger, especially for dense urban areas. The largest deviations from real world sunlit areas are found for roofs during mornings and evenings. Indications that sunlit fractions on walls are overestimated using an ILC during mornings and evenings are found. The implications of these errors are dependent on the application targeted. For example, (independent of albedo) ULSMs used in numerical weather prediction applying ILC representation of the urban form will overestimate outgoing shortwave radiation from roofs due to the overestimation of sunlit fraction of the roofs. Complications of deriving height to width ratios from real world data are also discussed.

Spatial evaluation of volcanic ash forecasts using satellite observations

The decision to close airspace in the event of a volcanic eruption is based on hazard maps of predicted ash extent. These are produced using output from volcanic ash transport and dispersion (VATD)models. In this paper an objectivemetric to evaluate the spatial accuracy of VATD simulations relative to satellite retrievals of volcanic ash is presented. The 5 metric is based on the fractions skill score (FSS). Thismeasure of skill provides more information than traditional point-bypoint metrics, such as success index and Pearson correlation coefficient, as it takes into the account spatial scale overwhich skill is being assessed. The FSS determines the scale overwhich a simulation has skill and can differentiate between a "near miss" and a forecast that is badly misplaced. The 10 idealised scenarios presented show that even simulations with considerable displacement errors have useful skill when evaluated over neighbourhood scales of 200–700km2. This method could be used to compare forecasts produced by different VATDs or using different model parameters, assess the impact of assimilating satellite retrieved ash data and evaluate VATD forecasts over a long time period.

Increase in Hippocampal Theta Oscillations during Spatial Decision Making

The processing of spatial and mnemonic information is believed to depend on hippocampal theta oscillations (5–12 Hz). However, in rats both the power and the frequency of the theta rhythm are modulated by locomotor activity, which is a major confounding factor when estimating its cognitive correlates. Previous studies have suggested that hippocampal theta oscillations support decision-making processes. In this study, we investigated to what extent spatial decision making modulates hippocampal theta oscillations when controlling for variations in locomotion speed. We recorded local field potentials from the CA1 region of rats while animals had to choose one arm to enter for reward (goal) in a four-arm radial maze. We observed prominent theta oscillations during the decision-making period of the task, which occurred in the center of the maze before animals deliberately ran through an arm toward goal location. In speed-controlled analyses, theta power and frequency were higher during the decision period when compared to either an intertrial delay period (also at the maze center), or to the period of running toward goal location. In addition, theta activity was higher during decision periods preceding correct choices than during decision periods preceding incorrect choices. Altogether, our data support a cognitive function for the hippocampal theta rhythm in spatial decision making

Modeling the spatial dynamics of economic models

The advances that have been characterizing spatial econometrics in recent years are mostly theoretical and have not found an extensive empirical application yet. In this work we aim at supplying a review of the main tools of spatial econometrics and to show an empirical application for one of the most recently introduced estimators. Despite the numerous alternatives that the econometric theory provides for the treatment of spatial (and spatiotemporal) data, empirical analyses are still limited by the lack of availability of the correspondent routines in statistical and econometric software. Spatiotemporal modeling represents one of the most recent developments in spatial econometric theory and the finite sample properties of the estimators that have been proposed are currently being tested in the literature. We provide a comparison between some estimators (a quasi-maximum likelihood, QML, estimator and some GMM-type estimators) for a fixed effects dynamic panel data model under certain conditions, by means of a Monte Carlo simulation analysis. We focus on different settings, which are characterized either by fully stable or quasi-unit root series. We also investigate the extent of the bias that is caused by a non-spatial estimation of a model when the data are characterized by different degrees of spatial dependence. Finally, we provide an empirical application of a QML estimator for a time-space dynamic model which includes a temporal, a spatial and a spatiotemporal lag of the dependent variable. This is done by choosing a relevant and prolific field of analysis, in which spatial econometrics has only found limited space so far, in order to explore the value-added of considering the spatial dimension of the data. In particular, we study the determinants of cropland value in Midwestern U.S.A. in the years 1971-2009, by taking the present value model (PVM) as the theoretical framework of analysis.