Validation of three new measure-correlate-predict models for the long-term prospection of the wind resource

The estimation of the long-term wind resource at a prospective site based on a relatively short on-site measurement campaign is an indispensable task in the development of a commercial wind farm. The typical industry approach is based on the measure-correlate-predict �MCP� method where a relational model between the site wind velocity data and the data obtained from a suitable reference site is built from concurrent records. In a subsequent step, a long-term prediction for the prospective site is obtained from a combination of the relational model and the historic reference data. In the present paper, a systematic study is presented where three new MCP models, together with two published reference models �a simple linear regression and the variance ratio method�, have been evaluated based on concurrent synthetic wind speed time series for two sites, simulating the prospective and the reference site. The synthetic method has the advantage of generating time series with the desired statistical properties, including Weibull scale and shape factors, required to evaluate the five methods under all plausible conditions. In this work, first a systematic discussion of the statistical fundamentals behind MCP methods is provided and three new models, one based on a nonlinear regression and two �termed kernel methods� derived from the use of conditional probability density functions, are proposed. All models are evaluated by using five metrics under a wide range of values of the correlation coefficient, the Weibull scale, and the Weibull shape factor. Only one of all models, a kernel method based on bivariate Weibull probability functions, is capable of accurately predicting all performance metrics studied.

A simple variance formula for population size estimators by conditioning

This note considers the variance estimation for population size estimators based on capture–recapture experiments. Whereas a diversity of estimators of the population size has been suggested, the question of estimating the associated variances is less frequently addressed. This note points out that the technique of conditioning can be applied here successfully which also allows us to identify sources of variation: the variance due to estimation of the model parameters and the binomial variance due to sampling n units from a population of size N. It is applied to estimators typically used in capture–recapture experiments in continuous time including the estimators of Zelterman and Chao and improves upon previously used variance estimators. In addition, knowledge of the variances associated with the estimators by Zelterman and Chao allows the suggestion of a new estimator as the weighted sum of the two. The decomposition of the variance into the two sources allows also a new understanding of how resampling techniques like the Bootstrap could be used appropriately. Finally, the sample size question for capture–recapture experiments is addressed. Since the variance of population size estimators increases with the sample size, it is suggested to use relative measures such as the observed-to-hidden ratio or the completeness of identification proportion for approaching the question of sample size choice.

A simple variance formula for population size estimators by conditioning

This note considers the variance estimation for population size estimators based on capture–recapture experiments. Whereas a diversity of estimators of the population size has been suggested, the question of estimating the associated variances is less frequently addressed. This note points out that the technique of conditioning can be applied here successfully which also allows us to identify sources of variation: the variance due to estimation of the model parameters and the binomial variance due to sampling n units from a population of size N. It is applied to estimators typically used in capture–recapture experiments in continuous time including the estimators of Zelterman and Chao and improves upon previously used variance estimators. In addition, knowledge of the variances associated with the estimators by Zelterman and Chao allows the suggestion of a new estimator as the weighted sum of the two. The decomposition of the variance into the two sources allows also a new understanding of how resampling techniques like the Bootstrap could be used appropriately. Finally, the sample size question for capture–recapture experiments is addressed. Since the variance of population size estimators increases with the sample size, it is suggested to use relative measures such as the observed-to-hidden ratio or the completeness of identification proportion for approaching the question of sample size choice.

Kernel classifier construction using orthogonal forward selection and boosting with Fisher ratio class separability measure

A greedy technique is proposed to construct parsimonious kernel classifiers using the orthogonal forward selection method and boosting based on Fisher ratio for class separability measure. Unlike most kernel classification methods, which restrict kernel means to the training input data and use a fixed common variance for all the kernel terms, the proposed technique can tune both the mean vector and diagonal covariance matrix of individual kernel by incrementally maximizing Fisher ratio for class separability measure. An efficient weighted optimization method is developed based on boosting to append kernels one by one in an orthogonal forward selection procedure. Experimental results obtained using this construction technique demonstrate that it offers a viable alternative to the existing state-of-the-art kernel modeling methods for constructing sparse Gaussian radial basis function network classifiers. that generalize well.

Land/sea warming ratio in response to climate change: IPCC AR4 model results and comparison with observations

Climate model simulations consistently show that in response to greenhouse gas forcing surface temperatures over land increase more rapidly than over sea. The enhanced warming over land is not simply a transient effect, since it is also present in equilibrium conditions. We examine 20 models from the IPCC AR4 database. The global land/sea warming ratio varies in the range 1.36–1.84, independent of global mean temperature change. In the presence of increasing radiative forcing, the warming ratio for a single model is fairly constant in time, implying that the land/sea temperature difference increases with time. The warming ratio varies with latitude, with a minimum in equatorial latitudes, and maxima in the subtropics. A simple explanation for these findings is provided, and comparisons are made with observations. For the low-latitude (40°S–40°N) mean, the models suggest a warming ratio of 1.51 ± 0.13, while recent observations suggest a ratio of 1.54 ± 0.09.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Multidecadal modulation of El Nino-Southern Oscillation (ENSO) variance by Atlantic Ocean sea surface temperatures

Observations suggest a possible link between the Atlantic Multidecadal Oscillation (AMO) and El Nino Southern Oscillation (ENSO) variability, with the warm AMO phase being related to weaker ENSO variability. A coupled ocean-atmosphere model is used to investigate this relationship and to elucidate mechanisms responsible for it. Anomalous sea surface temperatures (SSTs) associated with the positive AMO lead to change in the basic state in the tropical Pacific Ocean. This basic state change is associated with a deepened thermocline and reduced vertical stratification of the equatorial Pacific ocean, which in turn leads to weakened ENSO variability. We suggest a role for an atmospheric bridge that rapidly conveys the influence of the Atlantic Ocean to the tropical Pacific. The results suggest a non-local mechanism for changes in ENSO statistics and imply that anomalous Atlantic ocean SSTs can modulate both mean climate and climate variability over the Pacific.

On logarithmic ratio quantities and their units

The use of special units for logarithmic ratio quantities is reviewed. The neper is used with a natural logarithm (logarithm to the base e) to express the logarithm of the amplitude ratio of two pure sinusoidal signals, particularly in the context of linear systems where it is desired to represent the gain or loss in amplitude of a single-frequency signal between the input and output. The bel, and its more commonly used submultiple, the decibel, are used with a decadic logarithm (logarithm to the base 10) to measure the ratio of two power-like quantities, such as a mean square signal or a mean square sound pressure in acoustics. Thus two distinctly different quantities are involved. In this review we define the quantities first, without reference to the units, as is standard practice in any system of quantities and units. We show that two different definitions of the quantity power level, or logarithmic power ratio, are possible. We show that this leads to two different interpretations for the meaning and numerical values of the units bel and decibel. We review the question of which of these alternative definitions is actually used, or is used by implication, by workers in the field. Finally, we discuss the relative advantages of the alternative definitions.

Determination of the vibrational transition moment ratio for the Coriolis interacting v9 and v10 fundamentals of allene

Comparison between observed and calculated infrared band contours has been made to determine the vibrational transition moment ratio |M10/M9| for the Coriolis interacting ν9 and ν10 perpendicular fundamentals of allene-h4. The ratio obtained is appreciably lower than that of a previous estimate and the result obtained by integrated band intensity measurements of Overend and Crawford. From the best estimate of the ratio, the dipole moment derivatives of the two bands are determined; the value for the weaker band ν9 is subject to a large uncertainty.

Intercropping with pulses to concentrate nitrogen and sulphur in wheat

The effects of intercropping wheat with faba bean (Denmark, Germany, Italy and UK) and wheat with pea (France), in additive and replacement designs on grain nitrogen and sulphur concentrations were studied in field experiments in the 2002/03, 2003/04 and 2004/05 growing seasons. Intercropping wheat with grain legumes regularly increased the nitrogen concentration of the cereal grain, irrespective of design or location. Sulphur concentration of the cereal was also increased by intercropping, but less regularly and to a lesser extent compared with effects on nitrogen concentration. Nitrogen concentration (g/kg) in wheat additively intercropped with faba bean was increased by 8% across all sites (weighted for inverse of variance), but sulphur concentration was only increased by 4%, so N:S ratio was also increased by 4%. Intercropping wheat with grain legumes increased sodium dodecyl sulphate (SDS)-sedimentation volume. The effect of intercropping on wheat nitrogen concentration was greatest when intercropping had the most deleterious effect on wheat yield and the least deleterious effect on pulse yield. Over all sites and seasons, and irrespective of whether the design was additive or replacement, increases in crude protein concentration in the wheat of 10 g/kg by intercropping with faba bean were associated with 25-30% yield reduction of the wheat, compared with sole-cropped wheat. It was concluded that the increase in protein concentration of wheat grain in intercrops could be of economic benefit when selling wheat for breadmaking, but only if the bean crop was also marketed effectively.

The effect of ram replacement and sex ratio on the sexual response of anoestrous ewes

It is accepted that an important source of variation in the response of anoestrous ewes, to the introduction of rams, is the intensity of male stimulation. The aim of this study was to investigate strategies capable of increasing the impact and transmission of the ram stimuli. In Experiment 1, two groups of seven ewes (Bluefaced Leicester male x Swaledale female) were individually penned with one ram and for the next 6 h the rams either remained in the pen or were replaced hourly. Blood samples revealed no difference in the pattern of plasma LH secretion. In Experiment 2, three groups of 16 ewes were either introduced to one ram, individually (H) or in groups of 8 (L), or remained isolated. Ram introduction increased the plasma LH pulsatility (P < 0.001). H ewes displayed more (nine versus six) male-induced LH pulses (pulses occurring within the first 45 min) and more pulses per 8 h intervals than the L group of ewes (1.9 +/- 0.3 versus 1.3 +/- 0.3), but these differences were not significant. It was concluded that (i) frequent replacement of rams within a few hours following ram introduction to ewes does not further improve the response of ewes, especially if the ram:ewe ratio is high; (ii) the characterization of the plasma LH secretion parameters during a period of 6-8 h does not seem to be an effective method to detect small differences in the intensity of stimulation received by the ewes when exposed to rams; (iii) North Country Mule ewes (Bluefaced Leicester male x Swaledale female) in the UK respond to the presence of rams in spring (late oestrous/early anoestrous season) with an elevation in plasma LH secretion. (c) 2005 Elsevier B.V. All rights reserved.

Effects of triazole and strobilurin fungicide programmes, with and without late-season nitrogen fertiliser, on the baking quality of Malacca winter wheat

Field experiments were conducted over 3 years to study the effect of applying triazole and strobilurin fungicides on the bread-making quality of Malacca winter wheat. Averaged over all years the application of a fungicide programme increased yields, particularly when strobilurin fungicides were applied. Reductions in protein concentration, sulphur concentration, Hageberg failing number and loaf volumes also occurred as the amount of fungicide applied increased. However, there were no deleterious effects of fungicide application on sodium dodecyl sulphate (SDS) sedimentation volumes, N:S ratios or dough theology. Effects of fungicide application on bread-making quality were not product specific. Therefore, it appears that new mechanisms to explain strobilurin effects on bread-making quality do not need to be invoked. Where reductions in protein concentration did occur they could be compensated for by a late-season application of nitrogen either as granular ammonium nitrate at flag leaf emergence or foliar urea at anthesis. These applications, however, sometimes increased the N:S ratio of the extracted flour and failed to improve loaf volume. Multiple regression analysis revealed that main effects of year, flour protein concentration and N:S ratio could explain 93% of the variance in loaf volume caused by season, fungicide and nitrogen treatments. However, an equally good fit was achieved by just including sulphur concentration with year. (C) 2004 Elsevier Ltd. All rights reserved.