Multi-site evaluation of an urban land-surface model: intra-urban heterogeneity, seasonality and parameter complexity requirements

An extensive off-line evaluation of the Noah/Single Layer Urban Canopy Model (Noah/SLUCM) urban land-surface model is presented using data from 15 sites to assess (1) the ability of the scheme to reproduce the surface energy balance observed in a range of urban environments, including seasonal changes, and (2) the impact of increasing complexity of input parameter information. Model performance is found to be most dependent on representation of vegetated surface area cover; refinement of other parameter values leads to smaller improvements. Model biases in net all-wave radiation and trade-offs between turbulent heat fluxes are highlighted using an optimization algorithm. Here we use the Urban Zones to characterize Energy partitioning (UZE) as the basis to assign default SLUCM parameter values. A methodology (FRAISE) to assign sites (or areas) to one of these categories based on surface characteristics is evaluated. Using three urban sites from the Basel Urban Boundary Layer Experiment (BUBBLE) dataset, an independent evaluation of the model performance with the parameter values representative of each class is performed. The scheme copes well with both seasonal changes in the surface characteristics and intra-urban heterogeneities in energy flux partitioning, with RMSE performance comparable to similar state-of-the-art models for all fluxes, sites and seasons. The potential of the methodology for high-resolution atmospheric modelling application using the Weather Research and Forecasting (WRF) model is highlighted. This analysis supports the recommendations that (1) three classes are appropriate to characterize the urban environment, and (2) that the parameter values identified should be adopted as default values in WRF.

The water balance of northern Africa during the mid-Holocene: an evaluation of the 6ka BP PMIP simulations

Runoff fields over northern Africa (10–25°N, 20°W–30°E) derived from 17 atmospheric general circulation models driven by identical 6 ka BP orbital forcing, sea surface temperatures, and CO2 concentration have been analyzed using a hydrological routing scheme (HYDRA) to simulate changes in lake area. The AGCM-simulated runoff produced six-fold differences in simulated lake area between models, although even the largest simulated changes considerably underestimate the observed changes in lake area during the mid-Holocene. The inter-model differences in simulated lake area are largely due to differences in simulated runoff (the squared correlation coefficient, R2, is 0.84). Most of these differences can be attributed to differences in the simulated precipitation (R2=0.83). The higher correlation between runoff and simulated lake area (R2=0.92) implies that simulated differences in evaporation have a contributory effect. When runoff is calculated using an offline land-surface scheme (BIOME3), the correlation between runoff and simulated lake area is (R2=0.94). Finally, the spatial distribution of simulated precipitation can exert an important control on the overall response.

A novel ensemble method for retrieving properties of warm cloud in 3-D using ground-based scanning radar and zenith radiances

We present a novel method for retrieving high-resolution, three-dimensional (3-D) nonprecipitating cloud fields in both overcast and broken-cloud situations. The method uses scanning cloud radar and multiwavelength zenith radiances to obtain gridded 3-D liquid water content (LWC) and effective radius (re) and 2-D column mean droplet number concentration (Nd). By using an adaption of the ensemble Kalman filter, radiances are used to constrain the optical properties of the clouds using a forward model that employs full 3-D radiative transfer while also providing full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from a challenging cumulus cloud field produced by a large-eddy simulation snapshot. Uncertainty due to measurement error in overhead clouds is estimated at 20% in LWC and 6% in re, but the true error can be greater due to uncertainties in the assumed droplet size distribution and radiative transfer. Over the entire domain, LWC and re are retrieved with average error 0.05–0.08 g m-3 and ~2 μm, respectively, depending on the number of radiance channels used. The method is then evaluated using real data from the Atmospheric Radiation Measurement program Mobile Facility at the Azores. Two case studies are considered, one stratocumulus and one cumulus. Where available, the liquid water path retrieved directly above the observation site was found to be in good agreement with independent values obtained from microwave radiometer measurements, with an error of 20 g m-2.

An aggregate resource efficiency perspective on sustainability: a Sustainable Value application to the EU-15 countries

The Sustainable Value approach integrates the efficiency with regard to environmental, social and economic resources into a monetary indicator. It gained significant popularity as evidenced by diverse applications at the corporate level. However, its introduction as a measure adhering to the strong sustainability paradigm sparked an ardent debate. This study explores its validity as a macroeconomic strong sustainability measure by applying the Sustainable Value approach to the EU-15 countries. Concretely, we assessed environmental, social and economic resources in combination with the GDP for all EU-15 countries from 1995 to 2006 for three benchmark alternatives. The results show that several countries manage to adequately delink resource use from GDP growth. Furthermore, the remarkable difference in outcome between the national and EU-15 benchmark indicates a possible inefficiency of the current allocation of national resource ceilings imposed by the European institutions. Additionally, by using an effects model we argue that the service degree of the economy and governmental expenditures on social protection and research and development are important determinants of overall resource efficiency. Finally, we sketch out three necessary conditions to link the Sustainable Value approach to the strong sustainability paradigm.

Easterly wave disturbances over Northeast Brazil: an observational analysis

This paper aims to identify the circulation associated with Easterly Wave Disturbances (EWDs) that propagate toward the Eastern Northeast Brazil (ENEB) and their impact on the rainfall over ENEB during 2006 and 2007 rainy seasons (April–July). The EWDs identification and trajectory are analyzed using an automatic tracking technique (TracKH). The EWDs circulation patterns and their main features were obtained using the composite technique. To evaluate the TracKH efficiency, a validation was done by comparing the EWDs number tracked against observed cases obtained from an observational analysis. The mean characteristics of EWDs are 5.5-day period, propagation speed of ~9.5 m·s−1, and a 4500 km wavelength. A synoptic analysis shows that between days −2 d and 0 d, the low level winds presented cyclonic relative vorticity and convergence anomalies both in 2006 and 2007. The EWDs signals are strongest at low levels. The EWDs propagation is associated with relative humidity and precipitation positive anomalies and OLR and omega negative anomalies. The EWDs tracks are seen over all ENEB and their lysis occurs between the ENEB and marginally inside the continent. The tracking captured 71% of EWDs in all periods, indicating that an objective analysis is a promising method for EWDs detection.

Theoretical insight into diagnosing observation error correlations using observation-minus-background and observation-minus-analysis statistics

To improve the quantity and impact of observations used in data assimilation it is necessary to take into account the full, potentially correlated, observation error statistics. A number of methods for estimating correlated observation errors exist, but a popular method is a diagnostic that makes use of statistical averages of observation-minus-background and observation-minus-analysis residuals. The accuracy of the results it yields is unknown as the diagnostic is sensitive to the difference between the exact background and exact observation error covariances and those that are chosen for use within the assimilation. It has often been stated in the literature that the results using this diagnostic are only valid when the background and observation error correlation length scales are well separated. Here we develop new theory relating to the diagnostic. For observations on a 1D periodic domain we are able to the show the effect of changes in the assumed error statistics used in the assimilation on the estimated observation error covariance matrix. We also provide bounds for the estimated observation error variance and eigenvalues of the estimated observation error correlation matrix. We demonstrate that it is still possible to obtain useful results from the diagnostic when the background and observation error length scales are similar. In general, our results suggest that when correlated observation errors are treated as uncorrelated in the assimilation, the diagnostic will underestimate the correlation length scale. We support our theoretical results with simple illustrative examples. These results have potential use for interpreting the derived covariances estimated using an operational system.

Testosterone is associated with self-employment among Australian men

Testosterone has pronounced effects on men’s physiological development and smaller, more nuanced, impacts on their economic behavior. In this study of 1199 Australian adult males, we investigate the relationship between the self-employed and their serum testosterone levels. Because prior studies have identified that testosterone is a hormone that is responsive to external factors (e.g. competition, risk-taking), we explicitly control for omitted variable bias and reverse causality by using an instrumental variable approach. We use insulin as our primary instrument to account for endogeneity between testosterone and self-employment. This is because prior research has identified a relationship between insulin and testosterone but not between insulin and self-employment. Our results show that there is a positive association between total testosterone and self-employment. Robustness checks using bioavailable testosterone and another similar instrument (daily alcohol consumption) confirm this positive finding.

Analysis and clustering of residential customers energy behavioral demand using smart meter data

Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.

Students’ perception of privacy risks in using social networking sites for learning: a study of Uganda Christian University

Although social networking sites (SNSs) present a great deal of opportunities to support learning, the privacy risk is perceived by learners as a friction point that affects their full use for learning. Privacy risks in SNSs can be divided into risks that are posed by the SNS provider itself and risks that result from user’s social interactions. Using an online survey questionnaire, this study explored the students’ perception of the benefits in using social networking sites for learning purposes and their perceived privacy risks. A sample of 214 students from Uganda Christian University in Africa was studied. The results show that although 88 % of participants indicated the usefulness of SNSs for learning, they are also aware of the risks associated with these sites. Most of the participants are concerned with privacy risks such as identity theft, cyber bullying, and impersonation that might influence their online learning participation in SNSs.

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.

An idealized study of coupled atmosphere-ocean 4D-Var in the presence of model error

Atmosphere only and ocean only variational data assimilation (DA) schemes are able to use window lengths that are optimal for the error growth rate, non-linearity and observation density of the respective systems. Typical window lengths are 6-12 hours for the atmosphere and 2-10 days for the ocean. However, in the implementation of coupled DA schemes it has been necessary to match the window length of the ocean to that of the atmosphere, which may potentially sacrifice the accuracy of the ocean analysis in order to provide a more balanced coupled state. This paper investigates how extending the window length in the presence of model error affects both the analysis of the coupled state and the initialized forecast when using coupled DA with differing degrees of coupling. Results are illustrated using an idealized single column model of the coupled atmosphere-ocean system. It is found that the analysis error from an uncoupled DA scheme can be smaller than that from a coupled analysis at the initial time, due to faster error growth in the coupled system. However, this does not necessarily lead to a more accurate forecast due to imbalances in the coupled state. Instead coupled DA is more able to update the initial state to reduce the impact of the model error on the accuracy of the forecast. The effect of model error is potentially most detrimental in the weakly coupled formulation due to the inconsistency between the coupled model used in the outer loop and uncoupled models used in the inner loop.