The EU societal awareness of landscape indicator: a review of its meaning, utility and performance across different scales

There is increasing recognition that agricultural landscapes meet multiple societal needs and demands beyond provision of economic and environmental goods and services. Accordingly, there have been significant calls for the inclusion of societal, amenity and cultural values in agri-environmental landscape indicators to assist policy makers in monitoring the wider impacts of land-based policies. However, capturing the amenity and cultural values that rural agrarian areas provide, by use of such indicators, presents significant challenges. The EU social awareness of landscape indicator represents a new class of generalized social indicator using a top-down methodology to capture the social dimensions of landscape without reference to the specific structural and cultural characteristics of individual landscapes. This paper reviews this indicator in the context of existing agri-environmental indicators and their differing design concepts. Using a stakeholder consultation approach in five case study regions, the potential and limitations of the indicator are evaluated, with a particular focus on its perceived meaning, utility and performance in the context of different user groups and at different geographical scales. This analysis supplements previous EU-wide assessments, through regional scale assessment of the limitations and potentialities of the indicator and the need for further data collection. The evaluation finds that the perceived meaning of the indicator does not vary with scale, but in common with all mapped indicators, the usefulness of the indicator, to different user groups, does change with scale of presentation. This indicator is viewed as most useful when presented at the scale of governance at which end users operate. The relevance of the different sub-components of the indicator are also found to vary across regions.

Evaluation of two cloud parametrization schemes using ARM and Cloudnet observations

Ground-based remote-sensing observations from Atmospheric Radiation Measurement (ARM) and Cloud-Net sites are used to evaluate the clouds predicted by a weather forecasting and climate model. By evaluating the cloud predictions using separate measures for the errors in frequency of occurrence, amount when present, and timing, we provide a detailed assessment of the model performance, which is relevant to weather and climate time-scales. Importantly, this methodology will be of great use when attempting to develop a cloud parametrization scheme, as it provides a clearer picture of the current deficiencies in the predicted clouds. Using the Met Office Unified Model, it is shown that when cloud fractions produced by a diagnostic and a prognostic cloud scheme are compared, the prognostic cloud scheme shows improvements to the biases in frequency of occurrence of low, medium and high cloud and to the frequency distributions of cloud amount when cloud is present. The mean cloud profiles are generally improved, although it is shown that in some cases the diagnostic scheme produced misleadingly good mean profiles as a result of compensating errors in frequency of occurrence and amount when present. Some biases remain when using the prognostic scheme, notably the underprediction of mean ice cloud fraction due to the amount when present being too low, and the overprediction of mean liquid cloud fraction due to the frequency of occurrence being too high.

Fabrication and evaluation of a skutterudite-based thermoelectric module for high-temperature applications

We report a straightforward methodology for the fabrication of high-temperature thermoelectric (TE) modules using commercially available solder alloys and metal barriers. This methodology employs standard and accessible facilities that are simple to implement in any laboratory. A TE module formed by nine n-type Yb x Co4Sb12 and p-type Ce x Fe3CoSb12 state-of-the-art skutterudite material couples was fabricated. The physical properties of the synthesized skutterudites were determined, and the module power output, internal resistance, and thermocycling stability were evaluated in air. At a temperature difference of 365 K, the module provides more than 1.5 W cm−3 volume power density. However, thermocycling showed an increase of the internal module resistance and degradation in performance with the number of cycles when the device is operated at a hot-side temperature higher than 573 K. This may be attributed to oxidation of the skutterudite thermoelements.

Is it significant? Guidelines for reporting BCI performance

Recent growth in brain-computer interface (BCI) research has increased pressure to report improved performance. However, different research groups report performance in different ways. Hence, it is essential that evaluation procedures are valid and reported in sufficient detail. In this chapter we give an overview of available performance measures such as classification accuracy, cohen’s kappa, information transfer rate (ITR), and written symbol rate. We show how to distinguish results from chance level using confidence intervals for accuracy or kappa. Furthermore, we point out common pitfalls when moving from offline to online analysis and provide a guide on how to conduct statistical tests on (BCI) results.

Towards improving the framework for probabilistic forecast evaluation

The evaluation of forecast performance plays a central role both in the interpretation and use of forecast systems and in their development. Different evaluation measures (scores) are available, often quantifying different characteristics of forecast performance. The properties of several proper scores for probabilistic forecast evaluation are contrasted and then used to interpret decadal probability hindcasts of global mean temperature. The Continuous Ranked Probability Score (CRPS), Proper Linear (PL) score, and IJ Good’s logarithmic score (also referred to as Ignorance) are compared; although information from all three may be useful, the logarithmic score has an immediate interpretation and is not insensitive to forecast busts. Neither CRPS nor PL is local; this is shown to produce counter intuitive evaluations by CRPS. Benchmark forecasts from empirical models like Dynamic Climatology place the scores in context. Comparing scores for forecast systems based on physical models (in this case HadCM3, from the CMIP5 decadal archive) against such benchmarks is more informative than internal comparison systems based on similar physical simulation models with each other. It is shown that a forecast system based on HadCM3 out performs Dynamic Climatology in decadal global mean temperature hindcasts; Dynamic Climatology previously outperformed a forecast system based upon HadGEM2 and reasons for these results are suggested. Forecasts of aggregate data (5-year means of global mean temperature) are, of course, narrower than forecasts of annual averages due to the suppression of variance; while the average “distance” between the forecasts and a target may be expected to decrease, little if any discernible improvement in probabilistic skill is achieved.

An evaluation of the pedestrian classification in a multi-domain multi-modality setup

The objective of this article is to study the problem of pedestrian classification across different light spectrum domains (visible and far-infrared (FIR)) and modalities (intensity, depth and motion). In recent years, there has been a number of approaches for classifying and detecting pedestrians in both FIR and visible images, but the methods are difficult to compare, because either the datasets are not publicly available or they do not offer a comparison between the two domains. Our two primary contributions are the following: (1) we propose a public dataset, named RIFIR , containing both FIR and visible images collected in an urban environment from a moving vehicle during daytime; and (2) we compare the state-of-the-art features in a multi-modality setup: intensity, depth and flow, in far-infrared over visible domains. The experiments show that features families, intensity self-similarity (ISS), local binary patterns (LBP), local gradient patterns (LGP) and histogram of oriented gradients (HOG), computed from FIR and visible domains are highly complementary, but their relative performance varies across different modalities. In our experiments, the FIR domain has proven superior to the visible one for the task of pedestrian classification, but the overall best results are obtained by a multi-domain multi-modality multi-feature fusion.

The blended approach to real estate allocations: performance implications of combining an exposure to German Spezialfonds with Global Listed Real Estate Securities

This paper seeks to increase the understanding of the performance implications for investors who choose to combine an unlisted real estate portfolio (in this case German Spezialfonds) with a (global) listed real estate element. We call this a “blended” approach to real estate allocations. For the avoidance of doubt, in this paper we are dealing purely with real estate equity (listed and unlisted) allocations, and do not incorporate real estate debt (listed or unlisted) or direct property into the process. A previous paper (Moss and Farrelly 2014) showed the benefits of the blended approach as it applied to UK Defined Contribution Pension Schemes. The catalyst for this paper has been the recent attention focused on German pension fund allocations, which have a relatively low (real estate) equity content, and a high bond content. We have used the MSCI Spezialfonds Index as a proxy for domestic German institutional real estate allocations, and the EPRA Global Developed Index as a proxy for a global listed real estate allocation. We also examine whether a rules based trading strategy, in this case Trend Following, can improve the risk adjusted returns above those of a simple buy and hold strategy for our sample period 2004-2015. Our findings are that by blending a 30% global listed portfolio with a 70% allocation (as opposed to a typical 100% weighting) to Spezialfonds, the real estate allocation returns increase from 2.88% p.a. to 5.42% pa. Volatility increases, but only to 6.53%., but there is a noticeable impact on maximum drawdown which increases to 19.4%. By using a Trend Following strategy raw returns are improved from 2.88% to 6.94% p.a. , The Sharpe Ratio increases from 1.05 to 1.49 and the Maximum Drawdown ratio is now only 1.83% compared to 19.4% using a buy and hold strategy . Finally, adding this (9%) real estate allocation to a mixed asset portfolio allocation typical for German pension funds there is an improvement in both the raw return (from 7.66% to 8.28%) and the Sharpe Ratio (from 0.91 to 0.98).

Can institutional investors bias real estate portfolio appraisals? Evidence from the market downturn

This paper investigates the extent to which institutional investors may have influenced independent real estate appraisals during the financial crisis. A conceptual model of the determinants of client influence on real estate appraisals is proposed. It is suggested that the extent of clients’ ability and willingness to bias appraisal outputs is contingent upon market and regulatory environments (ethical norms and legal and institutional frameworks), the salience of the appraisal(s) to the client, financial incentives for the appraiser to respond to client pressure, organisational culture, the level of moral reasoning of both individual clients and appraisers, client knowledge and the degree of appraisal uncertainty. The potential of client influence to bias ostensibly independent real estate appraisals is examined using the opportunity afforded by the market downturn commencing in 2007 in the UK. During the market turbulence at the end of 2007, the motivations of different types of owners to bias appraisals diverged clearly and temporarily provided a unique opportunity to assess potential appraisal bias. We use appraisal-based performance data for individual real estate assets to test whether there were significant ownership effects on performance during this period. The results support the hypothesis that real estate appraisals in this period reflected the differing needs of clients.

Economic experiments used for the evaluation of building users’ energy-saving behavior

Different treatments that could be implemented in the home environ-ment are evaluated with the objective of reaching a more rational and efficient use of energy. We consider that a detailed knowledge of energy-consuming behaviour is paramount for the development and implementation of new technologies, services and even policies that could result in more rational energy use. The proposed evaluation methodology is based on the development of economic experiments implemented in an experimental economics laboratory, where the behaviour of individuals when making decisions related to energy use in the domestic environment can be tested.

Evaluation of CMIP5 palaeo-simulations to improve climate projections

Structural differences among models account for much of the uncertainty in projected climate changes, at least until the mid-twenty-first century. Recent observations encompass too limited a range of climate variability to provide a robust test of the ability to simulate climate changes. Past climate changes provide a unique opportunity for out-of-sample evaluation of model performance. Palaeo-evaluation has shown that the large-scale changes seen in twenty-first-century projections, including enhanced land–sea temperature contrast, latitudinal amplification, changes in temperature seasonality and scaling of precipitation with temperature, are likely to be realistic. Although models generally simulate changes in large-scale circulation sufficiently well to shift regional climates in the right direction, they often do not predict the correct magnitude of these changes. Differences in performance are only weakly related to modern-day biases or climate sensitivity, and more sophisticated models are not better at simulating climate changes. Although models correctly capture the broad patterns of climate change, improvements are required to produce reliable regional projections.

Evaluation of a modern-analogue methodology for reconstructing Australian palaeoclimate from pollen

Quantitative palaeoclimate reconstructions are widely used to evaluate climatemodel performance. Here, as part of an effort to provide such a data set for Australia, we examine the impact of analytical decisions and sampling assumptions on modern-analogue reconstructions using a continent-wide pollen data set. There is a high degree of correlation between temperature variables in the modern climate of Australia, but there is sufficient orthogonality in the variations of precipitation, summer and winter temperature and plant–available moisture to allow independent reconstructions of these four variables to be made. The method of analogue selection does not affect the reconstructions, although bootstrap resampling provides a more reliable technique for obtaining robust measures of uncertainty. The number of analogues used affects the quality of the reconstructions: the most robust reconstructions are obtained using 5 analogues. The quality of reconstructions based on post-1850 CE pollen samples differ little from those using samples from between 1450 and 1849 CE, showing that European post settlement modification of vegetation has no impact on the fidelity of the reconstructions although it substantially increases the availability of potential analogues. Reconstructions based on core top samples are more realistic than those using surface samples, but only using core top samples would substantially reduce the number of available analogues and therefore increases the uncertainty of the reconstructions. Spatial and/or temporal averaging of pollen assemblages prior to analysis negatively affects the subsequent reconstructions for some variables and increases the associated uncertainties. In addition, the quality of the reconstructions is affected by the degree of spatial smoothing of the original climate data, with the best reconstructions obtained using climate data froma 0.5° resolution grid, which corresponds to the typical size of the pollen catchment. This study provides a methodology that can be used to provide reliable palaeoclimate reconstructions for Australia, which will fill in a major gap in the data sets used to evaluate climate models.

Using developmental evaluation methods with communities of practice

Purpose This research explored the use of developmental evaluation methods with community of practice programmes experiencing change or transition to better understand how to target support resources. Design / methodology / approach The practical use of a number of developmental evaluation methods was explored in three organisations over a nine month period using an action research design. The research was a collaborative process involving all the company participants and the academic (the author) with the intention of developing the practices of the participants as well as contributing to scholarship. Findings The developmental evaluation activities achieved the objectives of the knowledge managers concerned: they developed a better understanding of the contribution and performance of their communities of practice, allowing support resources to be better targeted. Three methods (fundamental evaluative thinking, actual-ideal comparative method and focus on strengths and assets) were found to be useful. Cross-case analysis led to the proposition that developmental evaluation methods act as a structural mechanism that develops the discourse of the organisation in ways that enhance the climate for learning, potentially helping develop a learning organization. Practical implications Developmental evaluation methods add to the options available to evaluate community of practice programmes. These supplement the commonly used activity indicators and impact story methods. 2 Originality / value Developmental evaluation methods are often used in social change initiatives, informing public policy and funding decisions. The contribution here is to extend their use to organisational community of practice programmes.

Cool roofs for passive cooling: performance in different climates and for different insulation levels in Italy

Roofs are severely hit by solar radiation in summer; hence the use of cool materials on the finishing layer provides a significant reduction in the heat flow entering the building, with sensible attenuation in the building cooling load. In this paper, a case study is presented, based on the dynamic simulation of an existing office building in Catania (southern Italy). Here, a part of the roof has been recently treated with a commercial cool paint, with the aim of improving thermal comfort in summer. Hence, the simulations represent a preliminary study that will allow assessing the expected effectiveness of the intervention. More in detail, the results of the simulations will be discussed in terms of both thermal comfort and energy savings, through the evaluation of parameters such as the roof surface temperature, the operative temperature and the cooling load for both conditions, i.e. with and without the cool paint. The paper also discusses the potential increase in the energy needs for winter heating, and looks at the overall annual balance in terms of primary energy; this is made by considering different climatic conditions and envelope characteristics. These aspects are usually not well highlighted in the current scientific literature.

Proper evaluation of the external convective heat transfer for the thermal analysis of cool roofs

Cool materials are characterized by high solar reflectance and high thermal emittance; when applied to the external surface of a roof, they make it possible to limit the amount of solar irradiance absorbed by the roof, and to increase the rate of heat flux emitted by irradiation to the environment, especially during nighttime. However, a roof also releases heat by convection on its external surface; this mechanism is not negligible, and an incorrect evaluation of its entity might introduce significant inaccuracy in the assessment of the thermal performance of a cool roof, in terms of surface temperature and rate of heat flux transferred to the indoors. This issue is particularly relevant in numerical simulations, which are essential in the design stage, therefore it deserves adequate attention. In the present paper, a review of the most common algorithms used for the calculation of the convective heat transfer coefficient due to wind on horizontal building surfaces is presented. Then, with reference to a case study in Italy, the simulated results are compared to the outcomes of a measurement campaign. Hence, the most appropriate algorithms for the convective coefficient are identified, and the errors deriving by an incorrect selection of this coefficient are discussed.

A process-based evaluation of dust-emitting winds in the CMIP5 simulation of HadGEM2-ES

Despite the importance of dust aerosol in the Earth system, state-of-the-art models show a large variety for North African dust emission. This study presents a systematic evaluation of dust emitting-winds in 30 years of the historical model simulation with the UK Met Office Earth-system model HadGEM2-ES for the Coupled Model Intercomparison Project Phase 5. Isolating the effect of winds on dust emission and using an automated detection for nocturnal low-level jets (NLLJs) allow an in-depth evaluation of the model performance for dust emission from a meteorological perspective. The findings highlight that NLLJs are a key driver for dust emission in HadGEM2-ES in terms of occurrence frequency and strength. The annually and spatially averaged occurrence frequency of NLLJs is similar in HadGEM2-ES and ERA-Interim from the European Centre for Medium-Range Weather Forecasts. Compared to ERA-Interim, a stronger pressure ridge over northern Africa in winter and the southward displaced heat low in summer result in differences in location and strength of NLLJs. Particularly the larger geostrophic winds associated with the stronger ridge have a strengthening effect on NLLJs over parts of West Africa in winter. Stronger NLLJs in summer may rather result from an artificially increased mixing coefficient under stable stratification that is weaker in HadGEM2-ES. NLLJs in the Bodélé Depression are affected by stronger synoptic-scale pressure gradients in HadGEM2-ES. Wintertime geostrophic winds can even be so strong that the associated vertical wind shear prevents the formation of NLLJs. These results call for further model improvements in the synoptic-scale dynamics and the physical parametrization of the nocturnal stable boundary layer to better represent dust-emitting processes in the atmospheric model. The new approach could be used for identifying systematic behavior in other models with respect to meteorological processes for dust emission. This would help to improve dust emission simulations and contribute to decreasing the currently large uncertainty in climate change projections with respect to dust aerosol.