913 resultados para Relative errors
Resumo:
A number of studies have investigated the benefits of sector versus regional diversification within a real estate portfolio without explicitly quantify the relative benefits of one against the other. This paper corrects this omission by adopting the approach of Heston and Rouwenhorst (1994) and Beckers, Connor and Curds (1996) on a sample of 187 property data points using annual data over the period 1981-1995. The general conclusion of which is the sector diversification explains on average 22% of the variability of property returns compared with 8% for administratively defined regions. A result in line with previous work. Implying that sector diversification should be the first level of analysis in constructing and managing the real estate portfolio. However, unlike previous work functionally defined regions provide less of an explanation of regional diversification than administrative regions. Which may be down to the weak definition of economic regions employed in this study.
Resumo:
A stylised fact in the real estate portfolio diversification literature is that sector (property-type) effects are relatively more important than regional (geographical) factors in determining property returns. Thus, for those portfolio managers who follow a top-down approach to portfolio management, they should first choose in which sectors to invest and then select the best properties in each market. However, the question arises as to whether the dominance of the sector effects relative to regional effects is constant. If not property fund managers will need to take account of regional effects in developing their portfolio strategy. We find the results show that the sector-specific factors dominate the regional-specific factors for the vast majority of the time. Nonetheless, there are periods when the regional factors are of equal or greater importance than the sector effects. In particular, the sector effects tend to dominate during volatile periods of the real estate cycle; however, during calmer periods the sector and regional effects are of equal importance. These findings suggest that the sector effects are still the most important aspect in the development of an active portfolio strategy.
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The solid-state transformation of carbamazepine from form III to form I was examined by Fourier Transform Raman spectroscopy. Using a novel environmental chamber, the isothermal conversion was monitored in situ at 130◦C, 138◦C, 140◦C and 150◦C. The rate of transformation was monitored by taking the relative intensities of peaks arising from two C H bending modes; this approach minimised errors due to thermal artefacts and variations in power intensities or scattering efficiencies from the samples in which crystal habit changed from a characteristic prism morphology (form III) to whiskers (form I). The solid-state transformation at the different temperatures was fitted to various solid-state kinetic models of which four gave good fits, thus indicating the complexity of the process which is known to occur via a solid–gas–solid mechanism. Arrhenius plots from the kinetic models yielded activation energies from 344 kJ mol−1 to 368 kJ mol−1 for the transformation. The study demonstrates the value of a rapid in situ analysis of drug polymorphic type which can be of value for at-line in-process control.
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Current state-of-the-art climate models fail to capture accurately the path of the Gulf Stream and North Atlantic Current. This leads to a warm bias near the North American coast, where the modelled Gulf Stream separates from the coast further north, and a cold anomaly to the east of the Grand Banks of Newfoundland, where the North Atlantic Current remains too zonal in this region. Using an atmosphere-only model forced with the sea surface temperature (SST) biases in the North Atlantic, we consider the impact they have on the mean state and the variability in the North Atlantic European region in winter. Our results show that the SST errors produce a mean sea-level pressure response that is similar in magnitude and pattern to the atmospheric circulation errors in the coupled climate model. The work also suggests that errors in the coupled model storm tracks and North Atlantic Oscillation, compared to reanalysis data, can also be explained partly by these SST errors. Our results suggest that both the error in the Gulf Stream separation location and the path of the North Atlantic Current around the Grand Banks play important roles in affecting the atmospheric circulation. Reducing these coupled model errors could improve significantly the representation of the large-scale atmospheric circulation of the North Atlantic and European region.
Resumo:
For data assimilation in numerical weather prediction, the initial forecast-error covariance matrix Pf is required. For variational assimilation it is particularly important to prescribe an accurate initial matrix Pf, since Pf is either static (in the 3D-Var case) or constant at the beginning of each assimilation window (in the 4D-Var case). At large scales the atmospheric flow is well approximated by hydrostatic balance and this balance is strongly enforced in the initial matrix Pf used in operational variational assimilation systems such as that of the Met Office. However, at convective scales this balance does not necessarily hold any more. Here we examine the extent to which hydrostatic balance is valid in the vertical forecast-error covariances for high-resolution models in order to determine whether there is a need to relax this balance constraint in convective-scale data assimilation. We use the Met Office Global and Regional Ensemble Prediction System (MOGREPS) and a 1.5 km resolution version of the Unified Model for a case study characterized by the presence of convective activity. An ensemble of high-resolution forecasts valid up to three hours after the onset of convection is produced. We show that at 1.5 km resolution hydrostatic balance does not hold for forecast errors in regions of convection. This indicates that in the presence of convection hydrostatic balance should not be enforced in the covariance matrix used for variational data assimilation at this scale. The results show the need to investigate covariance models that may be better suited for convective-scale data assimilation. Finally, we give a measure of the balance present in the forecast perturbations as a function of the horizontal scale (from 3–90 km) using a set of diagnostics. Copyright © 2012 Royal Meteorological Society and British Crown Copyright, the Met Office
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ABSTRACT Non-Gaussian/non-linear data assimilation is becoming an increasingly important area of research in the Geosciences as the resolution and non-linearity of models are increased and more and more non-linear observation operators are being used. In this study, we look at the effect of relaxing the assumption of a Gaussian prior on the impact of observations within the data assimilation system. Three different measures of observation impact are studied: the sensitivity of the posterior mean to the observations, mutual information and relative entropy. The sensitivity of the posterior mean is derived analytically when the prior is modelled by a simplified Gaussian mixture and the observation errors are Gaussian. It is found that the sensitivity is a strong function of the value of the observation and proportional to the posterior variance. Similarly, relative entropy is found to be a strong function of the value of the observation. However, the errors in estimating these two measures using a Gaussian approximation to the prior can differ significantly. This hampers conclusions about the effect of the non-Gaussian prior on observation impact. Mutual information does not depend on the value of the observation and is seen to be close to its Gaussian approximation. These findings are illustrated with the particle filter applied to the Lorenz ’63 system. This article is concluded with a discussion of the appropriateness of these measures of observation impact for different situations.
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CO, O3, and H2O data in the upper troposphere/lower stratosphere (UTLS) measured by the Atmospheric Chemistry Experiment Fourier Transform Spectrometer(ACE-FTS) on Canada’s SCISAT-1 satellite are validated using aircraft and ozonesonde measurements. In the UTLS, validation of chemical trace gas measurements is a challenging task due to small-scale variability in the tracer fields, strong gradients of the tracers across the tropopause, and scarcity of measurements suitable for validation purposes. Validation based on coincidences therefore suffers from geophysical noise. Two alternative methods for the validation of satellite data are introduced, which avoid the usual need for coincident measurements: tracer-tracer correlations, and vertical tracer profiles relative to tropopause height. Both are increasingly being used for model validation as they strongly suppress geophysical variability and thereby provide an “instantaneous climatology”. This allows comparison of measurements between non-coincident data sets which yields information about the precision and a statistically meaningful error-assessment of the ACE-FTS satellite data in the UTLS. By defining a trade-off factor, we show that the measurement errors can be reduced by including more measurements obtained over a wider longitude range into the comparison, despite the increased geophysical variability. Applying the methods then yields the following upper bounds to the relative differences in the mean found between the ACE-FTS and SPURT aircraft measurements in the upper troposphere (UT) and lower stratosphere (LS), respectively: for CO ±9% and ±12%, for H2O ±30% and ±18%, and for O3 ±25% and ±19%. The relative differences for O3 can be narrowed down by using a larger dataset obtained from ozonesondes, yielding a high bias in the ACEFTS measurements of 18% in the UT and relative differences of ±8% for measurements in the LS. When taking into account the smearing effect of the vertically limited spacing between measurements of the ACE-FTS instrument, the relative differences decrease by 5–15% around the tropopause, suggesting a vertical resolution of the ACE-FTS in the UTLS of around 1 km. The ACE-FTS hence offers unprecedented precision and vertical resolution for a satellite instrument, which will allow a new global perspective on UTLS tracer distributions.
Resumo:
Environmental cues influence the development of stomata on the leaf epidermis, and allow plants to exert plasticity in leaf stomatal abundance in response to the prevailing growing conditions. It is reported that Arabidopsis thaliana ‘Landsberg erecta’ plants grown under low relative humidity have a reduced stomatal index and that two genes in the stomatal development pathway, SPEECHLESS and FAMA, become de novo cytosine methylated and transcriptionally repressed. These environmentally-induced epigenetic responses were abolished in mutants lacking the capacity for de novo DNA methylation, for the maintenance of CG methylation, and in mutants for the production of short-interfering non-coding RNAs (siRNAs) in the RNA-directed DNA methylation pathway. Induction of methylation was quantitatively related to the induction of local siRNAs under low relative humidity. Our results indicate the involvement of both transcriptional and post-transcriptional gene suppression at these loci in response to environmental stress. Thus, in a physiologically important pathway, a targeted epigenetic response to a specific environmental stress is reported and several of its molecular, mechanistic components are described, providing a tractable platform for future epigenetics experiments. Our findings suggest epigenetic regulation of stomatal development that allows for anatomical and phenotypic plasticity, and may help to explain at least some of the plant’s resilience to fluctuating relative humidity.
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This paper revisits the debate over the importance of absolute vs. relative income as a correlate of subjective well-being using data from Bangladesh, one of the poorest countries in the world with high levels of corruption and poor governance. We do so by combining household data with population census and village survey records. Our results show that conditional on own household income, respondents report higher satisfaction levels when they experience an increase in their income over the past years. More importantly, individuals who report their income to be lower than their neighbours in the village also report less satisfaction with life. At the same time, our evidence suggests that relative wealth effect is stronger for the rich. Similarly, in villages with higher inequality, individuals report less satisfaction with life. However, when compared to the effect of absolute income, these effects (i.e. relative income and local inequality) are modest. Amongst other factors, we study the influence of institutional quality. Institutional quality, measured in terms of confidence in police, matters for well-being: it enters with a positive and significant coefficient in the well-being function.
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Using functional magnetic resonance imaging, we found that when bilinguals named pictures or read words aloud, in their native or nonnative language, activation was higher relative to monolinguals in 5 left hemisphere regions: dorsal precentral gyrus, pars triangularis, pars opercularis, superior temporal gyrus, and planum temporale. We further demonstrate that these areas are sensitive to increasing demands on speech production in monolinguals. This suggests that the advantage of being bilingual comes at the expense of increased work in brain areas that support monolingual word processing. By comparing the effect of bilingualism across a range of tasks, we argue that activation is higher in bilinguals compared with monolinguals because word retrieval is more demanding; articulation of each word is less rehearsed; and speech output needs careful monitoring to avoid errors when competition for word selection occurs between, as well as within,language.
Landscape, regional and global estimates of nitrogen flux from land to sea: errors and uncertainties
Resumo:
Regional to global scale modelling of N flux from land to ocean has progressed to date through the development of simple empirical models representing bulk N flux rates from large watersheds, regions, or continents on the basis of a limited selection of model parameters. Watershed scale N flux modelling has developed a range of physically-based approaches ranging from models where N flux rates are predicted through a physical representation of the processes involved, through to catchment scale models which provide a simplified representation of true systems behaviour. Generally, these watershed scale models describe within their structure the dominant process controls on N flux at the catchment or watershed scale, and take into account variations in the extent to which these processes control N flux rates as a function of landscape sensitivity to N cycling and export. This paper addresses the nature of the errors and uncertainties inherent in existing regional to global scale models, and the nature of error propagation associated with upscaling from small catchment to regional scale through a suite of spatial aggregation and conceptual lumping experiments conducted on a validated watershed scale model, the export coefficient model. Results from the analysis support the findings of other researchers developing macroscale models in allied research fields. Conclusions from the study confirm that reliable and accurate regional scale N flux modelling needs to take account of the heterogeneity of landscapes and the impact that this has on N cycling processes within homogenous landscape units.
Resumo:
To investigate the relative importance of instream nutrient spiralling and wetland transformation processes on surface water quality, total nitrogen (TN) and total phosphorus (TP) concentrations in a 200 m reach of the River Lambourn in the south-east of England were monitored over a 2-year period. In addition, the soil pore water nutrient dynamics in a riparian ecosystem adjacent to the river were investigated. Analysis of variance indicated that TN, TP and suspended sediment concentrations recorded upstream of the wetland were statistically significantly higher (P<0.05) than those downstream of the site. Such results suggest that the wetland was performing a nutrient retention function. Indeed, analysis of soil pore waters within the site show that up to 85% of TN and 70% of TP was removed from water flowing through the wetland during baseflow conditions, thus supporting the theory that the wetland played an important role in the regulation of surface water quality at the site. However, the small variations observed (0.034 mg TN l-1 and 0.031 mg P l-1) are consistent with the theory of nutrient spiralling suggesting that both instream and wetland retention processes have a causal effect on surface water quality.
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We perform a multimodel detection and attribution study with climate model simulation output and satellite-based measurements of tropospheric and stratospheric temperature change. We use simulation output from 20 climate models participating in phase 5 of the Coupled Model Intercomparison Project. This multimodel archive provides estimates of the signal pattern in response to combined anthropogenic and natural external forcing (the finger-print) and the noise of internally generated variability. Using these estimates, we calculate signal-to-noise (S/N) ratios to quantify the strength of the fingerprint in the observations relative to fingerprint strength in natural climate noise. For changes in lower stratospheric temperature between 1979 and 2011, S/N ratios vary from 26 to 36, depending on the choice of observational dataset. In the lower troposphere, the fingerprint strength in observations is smaller, but S/N ratios are still significant at the 1% level or better, and range from three to eight. We find no evidence that these ratios are spuriously inflated by model variability errors. After removing all global mean signals, model fingerprints remain identifiable in 70% of the tests involving tropospheric temperature changes. Despite such agreement in the large-scale features of model and observed geographical patterns of atmospheric temperature change, most models do not replicate the size of the observed changes. On average, the models analyzed underestimate the observed cooling of the lower stratosphere and overestimate the warming of the troposphere. Although the precise causes of such differences are unclear, model biases in lower stratospheric temperature trends are likely to be reduced by more realistic treatment of stratospheric ozone depletion and volcanic aerosol forcing.