Decadal predictability of regional-scale peak winds over Europe using the Earth System Model of the Max-Planck-Institute for Meteorology

The predictability of high impact weather events on multiple time scales is a crucial issue both in scientific and socio-economic terms. In this study, a statistical-dynamical downscaling (SDD) approach is applied to an ensemble of decadal hindcasts obtained with the Max-Planck-Institute Earth System Model (MPI-ESM) to estimate the decadal predictability of peak wind speeds (as a proxy for gusts) over Europe. Yearly initialized decadal ensemble simulations with ten members are investigated for the period 1979–2005. The SDD approach is trained with COSMO-CLM regional climate model simulations and ERA-Interim reanalysis data and applied to the MPI-ESM hindcasts. The simulations for the period 1990–1993, which was characterized by several windstorm clusters, are analyzed in detail. The anomalies of the 95 % peak wind quantile of the MPI-ESM hindcasts are in line with the positive anomalies in reanalysis data for this period. To evaluate both the skill of the decadal predictability system and the added value of the downscaling approach, quantile verification skill scores are calculated for both the MPI-ESM large-scale wind speeds and the SDD simulated regional peak winds. Skill scores are predominantly positive for the decadal predictability system, with the highest values for short lead times and for (peak) wind speeds equal or above the 75 % quantile. This provides evidence that the analyzed hindcasts and the downscaling technique are suitable for estimating wind and peak wind speeds over Central Europe on decadal time scales. The skill scores for SDD simulated peak winds are slightly lower than those for large-scale wind speeds. This behavior can be largely attributed to the fact that peak winds are a proxy for gusts, and thus have a higher variability than wind speeds. The introduced cost-efficient downscaling technique has the advantage of estimating not only wind speeds but also estimates peak winds (a proxy for gusts) and can be easily applied to large ensemble datasets like operational decadal prediction systems.

Probabilistic wind power forecasts with an inverse power curve transformation and censored regression

Forecasting wind power is an important part of a successful integration of wind power into the power grid. Forecasts with lead times longer than 6 h are generally made by using statistical methods to post-process forecasts from numerical weather prediction systems. Two major problems that complicate this approach are the non-linear relationship between wind speed and power production and the limited range of power production between zero and nominal power of the turbine. In practice, these problems are often tackled by using non-linear non-parametric regression models. However, such an approach ignores valuable and readily available information: the power curve of the turbine's manufacturer. Much of the non-linearity can be directly accounted for by transforming the observed power production into wind speed via the inverse power curve so that simpler linear regression models can be used. Furthermore, the fact that the transformed power production has a limited range can be taken care of by employing censored regression models. In this study, we evaluate quantile forecasts from a range of methods: (i) using parametric and non-parametric models, (ii) with and without the proposed inverse power curve transformation and (iii) with and without censoring. The results show that with our inverse (power-to-wind) transformation, simpler linear regression models with censoring perform equally or better than non-linear models with or without the frequently used wind-to-power transformation.

Tests of sunspot number sequences: 3. Effects of regression procedures on the calibration of historic sunspot data

We use sunspot group observations from the Royal Greenwich Observatory (RGO) to investigate the effects of intercalibrating data from observers with different visual acuities. The tests are made by counting the number of groups RB above a variable cut-off threshold of observed total whole-spot area (uncorrected for foreshortening) to simulate what a lower acuity observer would have seen. The synthesised annual means of RB are then re-scaled to the full observed RGO group number RA using a variety of regression techniques. It is found that a very high correlation between RA and RB (rAB > 0.98) does not prevent large errors in the intercalibration (for example sunspot maximum values can be over 30 % too large even for such levels of rAB). In generating the backbone sunspot number (RBB), Svalgaard and Schatten (2015, this issue) force regression fits to pass through the scatter plot origin which generates unreliable fits (the residuals do not form a normal distribution) and causes sunspot cycle amplitudes to be exaggerated in the intercalibrated data. It is demonstrated that the use of Quantile-Quantile (“Q  Q”) plots to test for a normal distribution is a useful indicator of erroneous and misleading regression fits. Ordinary least squares linear fits, not forced to pass through the origin, are sometimes reliable (although the optimum method used is shown to be different when matching peak and average sunspot group numbers). However, other fits are only reliable if non-linear regression is used. From these results it is entirely possible that the inflation of solar cycle amplitudes in the backbone group sunspot number as one goes back in time, relative to related solar-terrestrial parameters, is entirely caused by the use of inappropriate and non-robust regression techniques to calibrate the sunspot data.

Determinants of satisfaction amongst tenants of UK Offices

Purpose – Corporate Occupiers require offices and services which meet their business needs, whilst landlords must attract and retain occupiers in order to maximise occupancy and rental income. The purpose of this research is to help landlords and corporate occupiers understand each other better, in order to achieve a mutually beneficial relationship. Design/methodology/approach - This paper analyses interviews with 1334 office tenants in the UK, conducted over an 11-year period, to investigate determinants of occupier satisfaction, loyalty and advocacy. Structural equation modelling and regressions are performed using respondents’ ratings of satisfaction with many aspects of occupancy as explanatory variables. The dependent variables include satisfaction with property management, value for money, overall occupier satisfaction, lease renewal intentions and occupiers’ willingness to recommend their landlord. Findings - The aspects with most impact on occupiers’ satisfaction are the office building itself, its location and amenities, and also communication with their property manager, a belief that their business needs are understood and the property manager’s responsiveness to occupiers’ requests. Occupiers’ loyalty depends mainly upon feeling that their rent and service charges provide value for money, an amicable leasing process, the professionalism of their property manager and the Corporate Social Responsibility of the Landlord. ‘Empathy’ is crucial to occupiers’ willingness to recommend their landlord, and clear documentation and efficient legal process improve occupiers’ perception of receiving ‘Value for Money’. Research Limitations - The sample is skewed towards occupiers of prime office buildings in the UK, owned by landlords who care sufficiently about their tenants to commission studies into occupier satisfaction. Practical implications - This research should help to improve the landlord – tenant relationship, benefitting the businesses that rent property and helping building managers understand where to focus their efforts to achieve maximum effect on occupier satisfaction, loyalty and advocacy. Originality/value - There has been little academic research into the determinants of satisfaction of occupiers of UK commercial property. This large-scale study enables the most influential factors to be identified and prioritised.

Assessment and improvement of biotransfer models to cow’s milk and beef used in exposure assessment tools for organic pollutants

The aim of this study was to assess and improve the accuracy of biotransfer models for the organic pollutants (PCBs, PCDD/Fs, PBDEs, PFCAs, and pesticides) into cow’s milk and beef used in human exposure assessment. Metabolic rate in cattle is known as a key parameter for this biotransfer, however few experimental data and no simulation methods are currently available. In this research, metabolic rate was estimated using existing QSAR biodegradation models of microorganisms (BioWIN) and fish (EPI-HL and IFS-HL). This simulated metabolic rate was then incorporated into the mechanistic cattle biotransfer models (RAIDAR, ACC-HUMAN, OMEGA, and CKow). The goodness of fit tests showed that RAIDAR, ACC-HUMAN, OMEGA model performances were significantly improved using either of the QSARs when comparing the new model outputs to observed data. The CKow model is the only one that separates the processes in the gut and liver. This model showed the lowest residual error of all the models tested when the BioWIN model was used to represent the ruminant metabolic process in the gut and the two fish QSARs were used to represent the metabolic process in the liver. Our testing included EUSES and CalTOX which are KOW-regression models that are widely used in regulatory assessment. New regressions based on the simulated rate of the two metabolic processes are also proposed as an alternative to KOW-regression models for a screening risk assessment. The modified CKow model is more physiologically realistic, but has equivalent usability to existing KOW-regression models for estimating cattle biotransfer of organic pollutants.

Modelling the bioaccumulation of persistent organic pollutants in agricultural food chains for regulatory exposure assessment

New models for estimating bioaccumulation of persistent organic pollutants in the agricultural food chain were developed using recent improvements to plant uptake and cattle transfer models. One model named AgriSim was based on K OW regressions of bioaccumulation in plants and cattle, while the other was a steady-state mechanistic model, AgriCom. The two developed models and European Union System for the Evaluation of Substances (EUSES), as a benchmark, were applied to four reported food chain (soil/air-grass-cow-milk) scenarios to evaluate the performance of each model simulation against the observed data. The four scenarios considered were as follows: (1) polluted soil and air, (2) polluted soil, (3) highly polluted soil surface and polluted subsurface and (4) polluted soil and air at different mountain elevations. AgriCom reproduced observed milk bioaccumulation well for all four scenarios, as did AgriSim for scenarios 1 and 2, but EUSES only did this for scenario 1. The main causes of the deviation for EUSES and AgriSim were the lack of the soil-air-plant pathway and the ambient air-plant pathway, respectively. Based on the results, it is recommended that soil-air-plant and ambient air-plant pathway should be calculated separately and the K OW regression of transfer factor to milk used in EUSES be avoided. AgriCom satisfied the recommendations that led to the low residual errors between the simulated and the observed bioaccumulation in agricultural food chain for the four scenarios considered. It is therefore recommended that this model should be incorporated into regulatory exposure assessment tools. The model uncertainty of the three models should be noted since the simulated concentration in milk from 5th to 95th percentile of the uncertainty analysis often varied over two orders of magnitude. Using a measured value of soil organic carbon content was effective to reduce this uncertainty by one order of magnitude.

The relationship between size of living space and subjective well-being

Against a background of shrinking new homes and forebodings of “rabbit hutch Britain”, the relationship between size of living space and subjective well-being has never been more topical in the UK. Using the British Household Panel Survey (BHPS) and fixed effects regressions, this paper is the first to examine this relationship comprehensively. Two pathways are proposed between space and subjective well-being. First, space facilitates values and activities. Second, space signals wealth which in turn influences social status. It is proposed that wealth is a more important determinant of status for men than women, and that pathway two is therefore gendered. Part one of the paper examines the effect of a change in number of rooms per person on housing satisfaction and subjective well-being in the BHPS as a whole. Despite having a similar effect on the housing satisfaction of both genders, an increase in living space has only a (weak) positive linear effect on the life satisfaction and mental health of men. This suggests that space affects subjective well-being through pathway two, status. Part two of the paper tracks the housing satisfaction and subjective well-being over time of those individuals who move for “larger accommodation”. Consistent with various theories of adaptation, housing satisfaction increases in the year of the move; then decreases slightly before levelling out. Moving for “larger accommodation” has no positive impact on subjective well-being. Overall the results imply a weak positive relationship between size of living space and subjective well-being, but only for men.

Effects of rain shelter or simulated rain during grain filling and maturation on subsequent wheat grain quality in the UK

The effects of simulated additional rain (ear wetting, 25 mm) or of rain shelter imposed at different periods after anthesis on grain quality at maturity and the dynamics of grain filling and desiccation were investigated in UK field-grown crops of wheat (Triticum aestivum L., cvar Tybalt) in 2011 and in 2012 when June–August rainfall was 255.0 and 214.6 mm, respectively, and above the decadal mean (157.4 mm). Grain filling and desiccation were quantified well by broken-stick regressions and Gompertz curves, respectively. Rain shelter for 56 (2011) or 70 d (2012) after anthesis, and to a lesser extent during late maturation only, resulted in more rapid desiccation and hence progress to harvest maturity whereas ear wetting had negligible effects, even when applied four times. Grain-filling duration was also affected as above in 2011, but with no significant effect in 2012. In both years, there were strong positive associations between final grain dry weight and duration of filling. The treatments affected all grain quality traits in 2011: nitrogen (N) and sulphur (S) concentrations, N:S ratio, sodium dodecyl sulphate (SDS) sedimentation volume, Hagberg Falling Number (HFN), and the incidence of blackpoint. Only N concentration and blackpoint were affected significantly by treatments in 2012. Rain shelter throughout grain filling reduced N concentration, whereas rain shelter reduced the incidence of blackpoint and ear wetting increased it. In 2011, rain shelter throughout reduced S concentration, increased N:S ratio and reduced SDS. Treatment effects on HFN were not consistent within or between years. Nevertheless, a comparison between the extreme treatment means in 2012 indicated damage from late rain combined with ear wetting resulted in a reduction of c. 0.7 s in HFN/mm August rainfall, whilst that between samples taken immediately after ear wetting at harvest maturity or 7 d later suggested recovery from damage to HFN upon re-drying in planta. Hence, the incidence of blackpoint was the only grain quality trait affected consistently by the diverse treatments. The remaining aspects of grain quality were comparatively resilient to rain incident upon developing and maturing ears of cvar Tybalt. No consistent temporal patterns of sensitivity to shelter or ear wetting were detected for any aspect of grain quality.

Downward longwave radiation estimates for clear and all-sky conditions in the Sertozinho region of So Paulo, Brazil

The accurate estimate of the surface longwave fluxes contribution is important for the calculation of the surface radiation budget, which in turn controls all the components of the surface energy budget, such as evaporation and the sensible heat fluxes. This study evaluates the performance of the various downward longwave radiation parameterizations for clear and all-sky days applied to the Sertozinho region in So Paulo, Brazil. Equations have been adjusted to the observations of longwave radiation. The adjusted equations were evaluated for every hour throughout the day and the results showed good fits for most of the day, except near dawn and sunset, followed by nighttime. The seasonal variation was studied by comparing the dry period against the rainy period in the dataset. The least square linear regressions resulted in coefficients equal to the coefficients found for the complete period, both in the dry period and in the rainy period. It is expected that the best fit equation to the observed data for this site be used to produce estimates in other regions of the State of So Paulo, where such information is not available.

Effects of detectability on estimates of geographic range size in bignonieae

Extinction risk has not been evaluated for 96% of all described plant species. Given that the Global Strategy for Plant Conservation proposes preliminary conservation assessments of all described plant species by 2010, herbarium specimens (i.e., primary occurrence data) are increasingly being used to infer threat components from estimates of geographic range size. Nevertheless, estimates of range size based on herbarium data may be inaccurate due to collection bias associated with interspecific variation in detectability. We used data on 377 species of Bignonieae to test the hypothesis that there is a positive relationship between detectability and estimates of geographic range size derived from herbarium specimens. This relationship is expected if the proportion of the true geographic range size of a species that is documented by herbarium specimens is given by the product of the true geographic range size and the detectability of the species, assuming no relationship between true geographic range size and detectability. We developed 4 measures of detectability that can be estimated from herbarium data and examined the relationship between detectability and 2 types of estimates of geographic range size: area of occupancy and extent of occurrence. Our results from regressing estimates of extent of occurrence and area of occupancy on detectability across genera provided no support for this hypothesis. The same was true for regressions of estimated extent of occurrence on detectability across species within genera. Nevertheless, regressions of estimated area of occupancy on detectability across species within genera provided partial support for our hypothesis. We considered 3 possible explanations for this mixed outcome: violation of the assumption of no relationship between true geographic range size and detectability; the relationships between estimated geographic range size and detectability may be an artifact of a negative relationship between estimated area of occupancy and the sampling variance of detectability; detectability may have had 2 opposite effects on estimated species range sizes: one determines the proportion of the true range of a species documented by herbarium specimens and the other determines the distribution of true range size for the species actually observed with herbarium data. Our findings should help improve understanding of the potential biases incurred with the use of herbarium data.

Nutrition in Transition: Dietary Patterns of Rural Amazonian Women During a Period of Economic Change

Objectives: The goal of this study was to understand the relationship between economic change (wage labor, retirement, and the Bolsa Familia program) and dietary patterns in the rural Amazon and to determine the extent to which these changes followed the pattern of the nutrition transition. Methods: The study was longitudinal. The weighed-inventory method and economic interviews were used to collect data on dietary intake and household economics in a sample of 30 and 52 women in 2002 and 2009, respectively. Twenty of the women participated in both years and make-up the longitudinal sub-sample. Comparative statistics were used to identify changes in dietary patterns over time and multiple linear regressions were used to explore the relationship between economics, subsistence strategies, and diet. Results: There was a significant decline in kcal (P < 0.01) and carbohydrate (P < 0.01) but no change in protein intake over time in both the larger and smaller, longitudinal subsample. The percent of energy, carbohydrate, protein, and fat purchased increased in the larger and longitudinal samples (P <= 0.02) and there was an increase in refined carbohydrate and processed, fatty-meat consumption over time. The abandonment of manioc gardens was associated with increased dependence on purchased food (P = 0.03) while receipt of the Bolsa Familia was associated with increased protein intake and adequacy (P = 0.02). Conclusions: The dietary changes observed are only in partial agreement with predictions of the nutrition transition literature. The relationship between the economic and diet changes was shaped by the local context which should be considered when implementing CCT programs, like the Bolsa Familia. Am. J. Hum. Biol. 23:458-469, 2011. (C) 2011 Wiley-Liss, Inc.

Time-lag in biological responses to landscape changes in a highly dynamic Atlantic forest region

Time-lagged responses of biological variables to landscape modifications are widely recognized, but rarely considered in ecological studies. In order to test for the existence of time-lags in the response of trees, small mammals, birds and frogs to changes in fragment area and connectivity, we studied a fragmented and highly dynamic landscape in the Atlantic forest region. We also investigated the biological correlates associated with differential responses among taxonomic groups. Species richness and abundance for four taxonomic groups were measured in 21 secondary forest fragments during the same period (2000-2002), following a standardized protocol. Data analyses were based on power regressions and model selection procedures. The model inputs included present (2000) and past (1962, 1981) fragment areas and connectivity, as well as observed changes in these parameters. Although past landscape structure was particularly relevant for trees, all taxonomic groups (except small mammals) were affected by landscape dynamics, exhibiting a time-lagged response. Furthermore, fragment area was more important for species groups with lower dispersal capacity, while species with higher dispersal ability had stronger responses to connectivity measures. Although these secondary forest fragments still maintain a large fraction of their original biodiversity, the delay in biological response combined with high rates of deforestation and fast forest regeneration imply in a reduction in the average age of the forest. This also indicates that future species losses are likely, especially those that are more strictly-forest dwellers. Conservation actions should be implemented to reduce species extinction, to maintain old-growth forests and to favour the regeneration process. Our results demonstrate that landscape history can strongly affect the present distribution pattern of species in fragmented landscapes, and should be considered in conservation planning. (C) 2009 Elsevier Ltd. All rights reserved.

Birnbaum-Saunders nonlinear regression models

We introduce, for the first time, a new class of Birnbaum-Saunders nonlinear regression models potentially useful in lifetime data analysis. The class generalizes the regression model described by Rieck and Nedelman [Rieck, J.R., Nedelman, J.R., 1991. A log-linear model for the Birnbaum-Saunders distribution. Technometrics 33, 51-60]. We discuss maximum-likelihood estimation for the parameters of the model, and derive closed-form expressions for the second-order biases of these estimates. Our formulae are easily computed as ordinary linear regressions and are then used to define bias corrected maximum-likelihood estimates. Some simulation results show that the bias correction scheme yields nearly unbiased estimates without increasing the mean squared errors. Two empirical applications are analysed and discussed. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

Bias correction in a multivariate normal regression model with general parameterization

This paper derives the second-order biases Of maximum likelihood estimates from a multivariate normal model where the mean vector and the covariance matrix have parameters in common. We show that the second order bias can always be obtained by means of ordinary weighted least-squares regressions. We conduct simulation studies which indicate that the bias correction scheme yields nearly unbiased estimators. (C) 2009 Elsevier B.V. All rights reserved.

Determination of the susceptibility of Rhipicephalus (Boophilus) microplus (Acari: Ixodidae) to ivermectin and fipronil by Larval Immersion Test (LIT) in Uruguay

Rhipicephalus (Boophilus) microplus is an important cattle pest in Uruguay, and the law regulates its control. It is resistant to organophosphates, synthetic pyrethroids and, as recently discovered, to fipronil. Resistance to macrocyclic lactones (MLs) and amitraz have not been documented; however, veterinarians and farmers have reported treatment failures. The objective of the present work was to study the susceptibility of cattle tick strains from different Uruguayan counties to ivermectin (IVM) and fipronil by using the Larval Immersion Test (LIT). The Mozo strain was used as the susceptible reference strain. From 2007 to 2009, twenty-eight tick populations were collected from different cattle farms with and without history of IVM or fipronil use. A probit analysis estimated dose-mortality regressions, lethal concentrations (LC), and confidence intervals. The resistance ratio (RR) was determined at the LC(50) and LC(90) estimates. To classify a tick population in relation to resistance, three categories based on a statistical analysis of LC and RR between field populations and Mozo strains were defined: susceptible (no differences), incipient resistance (differences and RR(50) < 2) and resistant (differences and RR(50) >= 2). Eighteen field populations were tested with IVM and five of them presented a RR(50) range between 1.35 and 1.98 and the LC(50/90), which is statistically different from the Mozo strain (incipient resistance). However, the RR(90) increases >= 2 in four of the populations, confirming that tick resistance to IVM is emergent. The low RR values obtained could be a result of a low frequency of treatments with IVM. Twenty-seven tick populations were tested with fipronil and six were diagnosed as resistant according to the LIT. Cross-resistance was not observed between fipronil and IVM on these tick populations. The current study presents different R. (B.) microplus populations with an incipient resistance to IVM, and indicates that the fipronil tick resistance is restricted to certain areas in Uruguay. (c) 2011 Elsevier B.V. All rights reserved.