Sea surface temperature from a geostationary satellite by optimal estimation

Optimal estimation (OE) is applied as a technique for retrieving sea surface temperature (SST) from thermal imagery obtained by the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on Meteosat 9. OE requires simulation of observations as part of the retrieval process, and this is done here using numerical weather prediction fields and a fast radiative transfer model. Bias correction of the simulated brightness temperatures (BTs) is found to be a necessary step before retrieval, and is achieved by filtered averaging of simulations minus observations over a time period of 20 days and spatial scale of 2.5° in latitude and longitude. Throughout this study, BT observations are clear-sky averages over cells of size 0.5° in latitude and longitude. Results for the OE SST are compared to results using a traditional non-linear retrieval algorithm (“NLSST”), both validated against a set of 30108 night-time matches with drifting buoy observations. For the OE SST the mean difference with respect to drifter SSTs is − 0.01 K and the standard deviation is 0.47 K, compared to − 0.38 K and 0.70 K respectively for the NLSST algorithm. Perhaps more importantly, systematic biases in NLSST with respect to geographical location, atmospheric water vapour and satellite zenith angle are greatly reduced for the OE SST. However, the OE SST is calculated to have a lower sensitivity of retrieved SST to true SST variations than the NLSST. This feature would be a disadvantage for observing SST fronts and diurnal variability, and raises questions as to how best to exploit OE techniques at SEVIRI's full spatial resolution.

Optimal estimation of sea surface temperature from split-window observations

Optimal estimation (OE) improves sea surface temperature (SST) estimated from satellite infrared imagery in the “split-window”, in comparison to SST retrieved using the usual multi-channel (MCSST) or non-linear (NLSST) estimators. This is demonstrated using three months of observations of the Advanced Very High Resolution Radiometer (AVHRR) on the first Meteorological Operational satellite (Metop-A), matched in time and space to drifter SSTs collected on the global telecommunications system. There are 32,175 matches. The prior for the OE is forecast atmospheric fields from the Météo-France global numerical weather prediction system (ARPEGE), the forward model is RTTOV8.7, and a reduced state vector comprising SST and total column water vapour (TCWV) is used. Operational NLSST coefficients give mean and standard deviation (SD) of the difference between satellite and drifter SSTs of 0.00 and 0.72 K. The “best possible” NLSST and MCSST coefficients, empirically regressed on the data themselves, give zero mean difference and SDs of 0.66 K and 0.73 K respectively. Significant contributions to the global SD arise from regional systematic errors (biases) of several tenths of kelvin in the NLSST. With no bias corrections to either prior fields or forward model, the SSTs retrieved by OE minus drifter SSTs have mean and SD of − 0.16 and 0.49 K respectively. The reduction in SD below the “best possible” regression results shows that OE deals with structural limitations of the NLSST and MCSST algorithms. Using simple empirical bias corrections to improve the OE, retrieved minus drifter SSTs are obtained with mean and SD of − 0.06 and 0.44 K respectively. Regional biases are greatly reduced, such that the absolute bias is less than 0.1 K in 61% of 10°-latitude by 30°-longitude cells. OE also allows a statistic of the agreement between modelled and measured brightness temperatures to be calculated. We show that this measure is more efficient than the current system of confidence levels at identifying reliable retrievals, and that the best 75% of satellite SSTs by this measure have negligible bias and retrieval error of order 0.25 K.

A modified PNN algorithm with optimal PD modeling using the orthogonal least squares method

In this paper a modified algorithm is suggested for developing polynomial neural network (PNN) models. Optimal partial description (PD) modeling is introduced at each layer of the PNN expansion, a task accomplished using the orthogonal least squares (OLS) method. Based on the initial PD models determined by the polynomial order and the number of PD inputs, OLS selects the most significant regressor terms reducing the output error variance. The method produces PNN models exhibiting a high level of accuracy and superior generalization capabilities. Additionally, parsimonious models are obtained comprising a considerably smaller number of parameters compared to the ones generated by means of the conventional PNN algorithm. Three benchmark examples are elaborated, including modeling of the gas furnace process as well as the iris and wine classification problems. Extensive simulation results and comparison with other methods in the literature, demonstrate the effectiveness of the suggested modeling approach.

Performance-based contracting in the construction sector

Construction procurement is complex and there is a very wide range of options available to procurers. Inappropriate choices about how to procure may limit practical opportunities for innovation. In particular, traditional approaches to construction procurement set up many obstacles for technology suppliers to provide innovative solutions. This is because they are often employed as sub-contractors simply to provide and install equipment to specifications developed before the point at which they become involved in a project. A research team at the University of Reading has developed a procurement framework that comprehensively defines the various options open to procurers in a more fine-grained way than has been known in the past. This enables informed decisions that can establish tailor-made procurement approaches that take into account the needs of specific clients. It enables risk and reward structures to be aligned so that contracts and payment mechanisms are aligned precisely with what a client seeks to achieve. This is not a “one-size-fits-all” approach. Rather, it is an approach that enables informed decisions about how to organize individual procurements that are appropriate to particular circumstances, acknowledging that they differ for each client and for each procurement exercise. Within this context, performance-based contracting (PBC) is explored in terms of the different ways in which technology suppliers within constructed facilities might be encouraged and rewarded for the kinds of innovation sought by the ultimate clients. Examples from various industry sectors are presented, from public sector and from private sector, with a commentary about what they sought to achieve and the extent to which they were successful. The lessons from these examples are presented in terms of feasibility in relation to financial issues, governance, economics, strategic issues, contractual issues and cash flow issues for clients and for contractors. Further background documents and more detailed readings are provided in an appendix for those who wish to find out more.

Optimal planning of cocoa clonal selection programmes

Data from three cocoa (Theobroma cacao) clonal selection trials are used to investigate the genetic and environmental components of variation in yield and the percentage of total pods affected by black pod disease (Phytophtora pod rot). Simulations based on these estimated components of variation are then used to discuss the best choice in future of numbers of clones, replicates and years of harvest to maximise selection advances in the traits measured. The three main conclusions are the need to increase the number of clones at the expense of the number of replicates of each clone, the diminishing returns from additional years of harvesting and the importance of widening the genetic base of the clones chosen to be tested.

Nexus between contracting and construction professional service businesses: empirical evidence from international market

he construction market around the world has witnessed the growing eminence of construction professional services (CPSs), such as urban planning, architecture, engineering, and consultancy, while the traditional contracting sector remains strong. Nowadays, it is not uncommon to see a design firm taking over the work of a traditional main contractor, or vice versa, of overseeing the delivery of a project. Although the two sectors of contracting and CPS share the same purpose of materializing the built environment, they are as different as they are interrelated. Much has been mentioned about the nexus between the two but little has been done to articulate it using empirical evidence. This study examined the nexus between contracting and CPS businesses by offering and testing lead-lag effects between the two sectors in the international market. A longitudinal panel data composed of 23 top international contractors and CPS firms was adopted. Surprisingly, results of the panel data analyses show that CPS business does not have a significant positive causal effect on contracting as a downstream business, and vice versa. CPS and contracting subsidiaries, although within the same company, do not necessarily form a consortium to undertake the same project; rather, they often collaborate with other CPS or contracting counterparts to undertake projects. This paper provides valuable insights into the sophisticated nexus between contracting and CPS in the international construction market. It will support business executives’ rational decision making for selecting proper contracting or CPS allies, or a proper mergers and acquisitions strategy in the international market. The paper also provides a fresh perspective through which researchers can better investigate the diversification strategies adopted by international contracting and CPS firms.

Optimal steady motions for oriented vehicles

Motivated by the motion planning problem for oriented vehicles travelling in a 3-Dimensional space; Euclidean space E3, the sphere S3 and Hyperboloid H3. For such problems the orientation of the vehicle is naturally represented by an orthonormal frame over a point in the underlying manifold. The orthonormal frame bundles of the space forms R3,S3 and H3 correspond with their isometry groups and are the Euclidean group of motion SE(3), the rotation group SO(4) and the Lorentzian group SO(1; 3) respectively. Orthonormal frame bundles of space forms coincide with their isometry groups and therefore the focus shifts to left-invariant control systems defined on Lie groups. In this paper a method for integrating these systems is given where the controls are time-independent. For constant twist motions or helical motions, the corresponding curves g(t) 2 SE(3) are given in closed form by using the well known Rodrigues’ formula. However, this formula is only applicable to the Euclidean case. This paper gives a method for computing the non-Euclidean screw/helical motions in closed form. This involves decoupling the system into two lower dimensional systems using the double cover properties of Lie groups, then the lower dimensional systems are solved explicitly in closed form.

On the application of optimal wavelet filter banks for ECG signal classification

This paper discusses ECG signal classification after parametrizing the ECG waveforms in the wavelet domain. Signal decomposition using perfect reconstruction quadrature mirror filter banks can provide a very parsimonious representation of ECG signals. In the current work, the filter parameters are adjusted by a numerical optimization algorithm in order to minimize a cost function associated to the filter cut-off sharpness. The goal consists of achieving a better compromise between frequency selectivity and time resolution at each decomposition level than standard orthogonal filter banks such as those of the Daubechies and Coiflet families. Our aim is to optimally decompose the signals in the wavelet domain so that they can be subsequently used as inputs for training to a neural network classifier.

An optimal inverse method using Doppler lidar measurements to estimate the surface sensible heat flux

Inverse methods are widely used in various fields of atmospheric science. However, such methods are not commonly used within the boundary-layer community, where robust observations of surface fluxes are a particular concern. We present a new technique for deriving surface sensible heat fluxes from boundary-layer turbulence observations using an inverse method. Doppler lidar observations of vertical velocity variance are combined with two well-known mixed-layer scaling forward models for a convective boundary layer (CBL). The inverse method is validated using large-eddy simulations of a CBL with increasing wind speed. The majority of the estimated heat fluxes agree within error with the proscribed heat flux, across all wind speeds tested. The method is then applied to Doppler lidar data from the Chilbolton Observatory, UK. Heat fluxes are compared with those from a mast-mounted sonic anemometer. Errors in estimated heat fluxes are on average 18 %, an improvement on previous techniques. However, a significant negative bias is observed (on average −63%) that is more pronounced in the morning. Results are improved for the fully-developed CBL later in the day, which suggests that the bias is largely related to the choice of forward model, which is kept deliberately simple for this study. Overall, the inverse method provided reasonable flux estimates for the simple case of a CBL. Results shown here demonstrate that this method has promise in utilizing ground-based remote sensing to derive surface fluxes. Extension of the method is relatively straight-forward, and could include more complex forward models, or other measurements.

Ion flows and heating at a contracting polar-cap boundary: GISMOS observations indicating viscous-like interaction on the flanks of the magnetotail

This paper complements that in this issue by Clauer et al. concerning the international GISMOS campaign of 3–5 June 1987. From a detailed study of the EISCAT data, the polar-cap boundary, as defined by an almost shear east-west convection reversal, is found to contract across the EISCAT field of view between 04 and 07 MLT. An annulus of enhanced ion temperature and non-thermal plasma is observed immediately equatorward of the contracting boundary due to the lag in the response of the neutral-wind pattern to the change in ion flows. The ion flow inside the polar cap and at the boundary is shown to be relatively smooth, compared with that in the auroral oval, at 15-second resolution. The flow at the boundary is directed poleward, with velocities which exceed that of the boundary itself. The effect of velocity shears on the beamswinging technique used to derive the ion flows has been analysed in detail and it is found that spurious flows across a moving boundary can be generated. However, these are much smaller than the observed flows into the polar cap and cannot explain the 7 kV potential difference across the observed segment of the cap boundary between 04:30–06:30 UT. The ion temperature enhancements at the two observing azimuths is used to define the boundary orientation. The results are consistent with recent observations of slow anti-sunward flow of closed field lines on the flanks of the geomagnetic tail, which appears to be generated by some form of “viscous” coupling to the magnetosheath plasma.

Ion flows and heating at a contracting polar-cap boundary

Data recorded by the POLAR experiment run on the EISCAT radar during the international GISMOS campaign of 3–5 June 1987 are studied in detail. The polar-cap boundary, as denned by an almost shear East-West convection reversal, was observed to jump southward across the EISCAT field of view in two steps at 02:00 and 03:00 Magnetic Local Time and subsequently to contract back between 04:00 and 07:00 M.L.T. An annulus of enhanced ion temperature and non-thermal plasma was observed immediately equatorward of the contracting boundary due to the lag in the response of the neutral-wind pattern to the change in ion flows. The ion flow at the boundary is shown to be relatively smooth at 15 s resolution and directed northward, with velocities which exceed that of the boundary itself. The effect of velocity shears on the beamswinging technique used to derive the ion flows is analyzed in detail and it is shown that, for certain orientations of the cap boundary, spurious flows into the cap can be generated. However, these are much smaller than the observed flows into the polar cap and cannot explain the potential difference across the observed segment of the cap boundary (extending over 2 h of M.L.T.) which is roughly 7 kV. Similarly, an observed slowing of the zonal flow near the boundary cannot be explained as an error introduced by the use of the beamswinging technique. The results could be interpreted as being due to reconnection occurring on the dawn flank of the magnetopause (mapping to the polar cap at 04:30 06:30 M.L.T.). However, they are more consistent with recent observations of slow anti-sunward flow of closed field lines on the flanks of the geomagnetic tail, which appears to be generated by some form of “viscous” coupling to the magnetosheath plasma.

The role of animal nutrition in designing optimal foods of animal origin as reviewed by the COST Action Feed for Health (FA0802)

This review provides an overview of the main scientific outputs of a network (Action) supported by the European Cooperation in Science and Technology (COST) in the field of animal science, namely the COST Action Feed for Health (FA0802). The main aims of the COST Action Feed for Health (FA0802) were: to develop an integrated and collaborative network of research groups that focuses on the roles of feed and animal nutrition in improving animal wellbeing and also the quality, safety and wholesomeness of human foods of animal origin; to examine the consumer concerns and perceptions as regards livestock production systems. The COST Action Feed for Health has addressed these scientific topics during the last four years. From a practical point of view three main scientific fields of achievement can be identified: feed and animal nutrition; food of animal origin quality and functionality and consumers’ perceptions. Finally, the present paper has the scope to provide new ideas and solutions to a range of issues associated with the modern livestock production system.

Obstacle avoidance routing scheme through optimal sink movement for home monitoring and mobile robotic consumer devices

In recent years, ZigBee has been proven to be an excellent solution to create scalable and flexible home automation networks. In a home automation network, consumer devices typically collect data from a home monitoring environment and then transmit the data to an end user through multi-hop communication without the need for any human intervention. However, due to the presence of typical obstacles in a home environment, error-free reception may not be possible, particularly for power constrained devices. A mobile sink based data transmission scheme can be one solution but obstacles create significant complexities for the sink movement path determination process. Therefore, an obstacle avoidance data routing scheme is of vital importance to the design of an efficient home automation system. This paper presents a mobile sink based obstacle avoidance routing scheme for a home monitoring system. The mobile sink collects data by traversing through the obstacle avoidance path. Through ZigBee based hardware implementation and verification, the proposed scheme successfully transmits data through the obstacle avoidance path to improve network performance in terms of life span, energy consumption and reliability. The application of this work can be applied to a wide range of intelligent pervasive consumer products and services including robotic vacuum cleaners and personal security robots1.

Nonlinear identification using orthogonal forward regression with nested optimal regularization

An efficient data based-modeling algorithm for nonlinear system identification is introduced for radial basis function (RBF) neural networks with the aim of maximizing generalization capability based on the concept of leave-one-out (LOO) cross validation. Each of the RBF kernels has its own kernel width parameter and the basic idea is to optimize the multiple pairs of regularization parameters and kernel widths, each of which is associated with a kernel, one at a time within the orthogonal forward regression (OFR) procedure. Thus, each OFR step consists of one model term selection based on the LOO mean square error (LOOMSE), followed by the optimization of the associated kernel width and regularization parameter, also based on the LOOMSE. Since like our previous state-of-the-art local regularization assisted orthogonal least squares (LROLS) algorithm, the same LOOMSE is adopted for model selection, our proposed new OFR algorithm is also capable of producing a very sparse RBF model with excellent generalization performance. Unlike our previous LROLS algorithm which requires an additional iterative loop to optimize the regularization parameters as well as an additional procedure to optimize the kernel width, the proposed new OFR algorithm optimizes both the kernel widths and regularization parameters within the single OFR procedure, and consequently the required computational complexity is dramatically reduced. Nonlinear system identification examples are included to demonstrate the effectiveness of this new approach in comparison to the well-known approaches of support vector machine and least absolute shrinkage and selection operator as well as the LROLS algorithm.

Improving climate change detection through optimal seasonal averaging: the case of the North Atlantic jet and European precipitation

The detection of anthropogenic climate change can be improved by recognising the seasonality in the climate change response. This is demonstrated for the North Atlantic jet (zonal wind at 850 hPa, U850) and European precipitation responses projected by the CMIP5 climate models. The U850 future response is characterised by a marked seasonality: an eastward extension of the North Atlantic jet into Europe in November-April, and a poleward shift in May-October. Under the RCP8.5 scenario, the multi-model mean response in U850 in these two extended seasonal means emerges by 2035-2040 for the lower--latitude features and by 2050-2070 for the higher--latitude features, relative to the 1960-1990 climate. This is 5-15 years earlier than when evaluated in the traditional meteorological seasons (December--February, June--August), and it results from an increase in the signal to noise ratio associated with the spatial coherence of the response within the extended seasons. The annual mean response lacks important information on the seasonality of the response without improving the signal to noise ratio. The same two extended seasons are demonstrated to capture the seasonality of the European precipitation response to climate change and to anticipate its emergence by 10-20 years. Furthermore, some of the regional responses, such as the Mediterranean precipitation decline and the U850 response in North Africa in the extended winter, are projected to emerge by 2020-2025, according to the models with a strong response. Therefore, observations might soon be useful to test aspects of the atmospheric circulation response predicted by some of the CMIP5 models.