Evaluating the potential for statistical decadal predictions of sea surface temperatures with a perfect model approach

We explore the potential for making statistical decadal predictions of sea surface temperatures (SSTs) in a perfect model analysis, with a focus on the Atlantic basin. Various statistical methods (Lagged correlations, Linear Inverse Modelling and Constructed Analogue) are found to have significant skill in predicting the internal variability of Atlantic SSTs for up to a decade ahead in control integrations of two different global climate models (GCMs), namely HadCM3 and HadGEM1. Statistical methods which consider non-local information tend to perform best, but which is the most successful statistical method depends on the region considered, GCM data used and prediction lead time. However, the Constructed Analogue method tends to have the highest skill at longer lead times. Importantly, the regions of greatest prediction skill can be very different to regions identified as potentially predictable from variance explained arguments. This finding suggests that significant local decadal variability is not necessarily a prerequisite for skillful decadal predictions, and that the statistical methods are capturing some of the dynamics of low-frequency SST evolution. In particular, using data from HadGEM1, significant skill at lead times of 6–10 years is found in the tropical North Atlantic, a region with relatively little decadal variability compared to interannual variability. This skill appears to come from reconstructing the SSTs in the far north Atlantic, suggesting that the more northern latitudes are optimal for SST observations to improve predictions. We additionally explore whether adding sub-surface temperature data improves these decadal statistical predictions, and find that, again, it depends on the region, prediction lead time and GCM data used. Overall, we argue that the estimated prediction skill motivates the further development of statistical decadal predictions of SSTs as a benchmark for current and future GCM-based decadal climate predictions.

Evaluating a new LISFLOOD-FP formulation with data from the summer 2007 floods in Tewkesbury, UK

Two-dimensional flood inundation modelling is a widely used tool to aid flood risk management. In urban areas, the model spatial resolution required to represent flows through a typical street network often results in an impractical computational cost at the city scale. This paper presents the calibration and evaluation of a recently developed formulation of the LISFLOOD-FP model, which is more computationally efficient at these resolutions. Aerial photography was available for model evaluation on 3 days from the 24 to the 31 of July. The new formulation was benchmarked against the original version of the model at 20 and 40 m resolutions, demonstrating equally accurate simulation, given the evaluation data but at a 67 times faster computation time. The July event was then simulated at the 2 m resolution of the available airborne LiDAR DEM. This resulted in more accurate simulation of the floodplain drying dynamics compared with the coarse resolution models, although maximum inundation levels were simulated equally well at all resolutions tested.

Evaluating the effectiveness of common structures in property portfolio construction

A good portfolio structure enables an investor to diversify more effectively and understand systematic influences on their performance. However, in the property market, the choice of structure is affected by data constraints and convenience. Using individual return data, this study tests the hypothesis that some common structures in the UK do not explain a significant amount about property returns. It is found that, in the periods studied, not all the structures were effective and, for the annual returns, no structures were significant in all periods. The results suggest that the drivers represented by the structures take some time to be reflected in individual property returns. They also confirm the results of other studies in finding property type a much stronger factor in explaining returns than regions.

Evaluating the effects of tannins on the extent and rate of in vitro measured gas and methane production using the Automated Pressure Evaluation System (APES)

An in vitro study was conducted to investigate the effect of tannins on the extent and rate of gas and methane production, using an automated pressure evaluation system (APES). In this study three condensed tannins (CT; quebracho, grape seed and green tea tannins) and four hydrolysable tannins (HT; tara, valonea, myrabolan and chestnut tannins) were evaluated, with lucerne as a control substrate. CT and HT were characterised by matrix assisted laser desorption ionisation-time of flight mass spectrometry (MALDI-TOF-MS). Tannins were added to the substrate at an effective concentration of 100 g/kg either with or without polyethylene glycol (PEG6000), and incubated for 72 h in pooled, buffered rumen liquid from four lactating dairy cows. After inoculation, fermentation bottles were immediately connected to the APES to measure total cumulative gas production (GP). During the incubation, 11 gas samples were collected from each bottle at 0, 1, 4, 7, 11, 15, 23, 30, 46, 52 and 72 h of incubation and analysed for methane. A modified Michaelis-Menten model was fitted to the methane concentration patterns and model estimates were used to calculate the total cumulative methane production (GPCH4). GP and GPCH4 curves were fitted using a modified monophasic Michaelis-Menten model. Addition of quebracho reduced GP (P=0.002), whilst the other tannins did not affect GP. Addition of PEG increased GP for quebracho (P=0.003), valonea (P=0.058) and grape seed tannins (P=0.071), suggesting that these tannins either inhibited or tended to inhibit fermentation. Addition of quebracho and grape seed tannins also reduced (P≤0.012) the maximum rate of gas production, indicating that microbial activity was affected. Quebracho, valonea, myrabolan and grape seed decreased (P≤0.003) GPCH4 and the maximum rate (0.001≤ P≤ 0.102) of CH4 production. Addition of chestnut, green tea and tara tannins did not affect total gas nor methane production. Valonea and myrabolan tannins have most promise for reducing methane production as they had only a minor impact on gas production.

Evaluating the structure and magnitude of the ash plume during the initial phase of the 2010 Eyjafjallajökull eruption using lidar observations and NAME simulations

The Eyjafjallajökull volcano in Iceland erupted explosively on 14 April 2010, emitting a plume of ash into the atmosphere. The ash was transported from Iceland toward Europe where mostly cloud-free skies allowed ground-based lidars at Chilbolton in England and Leipzig in Germany to estimate the mass concentration in the ash cloud as it passed overhead. The UK Met Office's Numerical Atmospheric-dispersion Modeling Environment (NAME) has been used to simulate the evolution of the ash cloud from the Eyjafjallajökull volcano during the initial phase of the ash emissions, 14–16 April 2010. NAME captures the timing and sloped structure of the ash layer observed over Leipzig, close to the central axis of the ash cloud. Relatively small errors in the ash cloud position, probably caused by the cumulative effect of errors in the driving meteorology en route, result in a timing error at distances far from the central axis of the ash cloud. Taking the timing error into account, NAME is able to capture the sloped ash layer over the UK. Comparison of the lidar observations and NAME simulations has allowed an estimation of the plume height time series to be made. It is necessary to include in the model input the large variations in plume height in order to accurately predict the ash cloud structure at long range. Quantitative comparison with the mass concentrations at Leipzig and Chilbolton suggest that around 3% of the total emitted mass is transported as far as these sites by small (<100 μm diameter) ash particles.

Evaluating mid-infrared spectroscopy as a new technique for predicting sensory texture attributes of processed cheese

The objective of this study was to investigate the potential application of mid-infrared spectroscopy for determination of selected sensory attributes in a range of experimentally manufactured processed cheese samples. This study also evaluates mid-infrared spectroscopy against other recently proposed techniques for predicting sensory texture attributes. Processed cheeses (n = 32) of varying compositions were manufactured on a pilot scale. After 2 and 4 wk of storage at 4 degrees C, mid-infrared spectra ( 640 to 4,000 cm(-1)) were recorded and samples were scored on a scale of 0 to 100 for 9 attributes using descriptive sensory analysis. Models were developed by partial least squares regression using raw and pretreated spectra. The mouth-coating and mass-forming models were improved by using a reduced spectral range ( 930 to 1,767 cm(-1)). The remaining attributes were most successfully modeled using a combined range ( 930 to 1,767 cm(-1) and 2,839 to 4,000 cm(-1)). The root mean square errors of cross-validation for the models were 7.4(firmness; range 65.3), 4.6 ( rubbery; range 41.7), 7.1 ( creamy; range 60.9), 5.1(chewy; range 43.3), 5.2(mouth-coating; range 37.4), 5.3 (fragmentable; range 51.0), 7.4 ( melting; range 69.3), and 3.1 (mass-forming; range 23.6). These models had a good practical utility. Model accuracy ranged from approximate quantitative predictions to excellent predictions ( range error ratio = 9.6). In general, the models compared favorably with previously reported instrumental texture models and near-infrared models, although the creamy, chewy, and melting models were slightly weaker than the previously reported near-infrared models. We concluded that mid-infrared spectroscopy could be successfully used for the nondestructive and objective assessment of processed cheese sensory quality..

Evaluating the likelihood of the adoption of an animal welfare assessment system in European agri-food supply chains

Purpose – The purpose of this paper is to analyse the likelihood of adoption of a recently designed Welfare Assessment System in agri-food supply chains and the factors affecting the adoption decision. The application is carried out for pig and poultry chains. Design/methodology/approach – This research consisted of two main components: interviews with retailers in pig and poultry supply chains in eight different EU countries to explore their perceptions towards the adoption possibilities of the welfare assessment system; and a conjoint analysis designed to evaluate the perceived adoption likelihood of the assessment system by different Standards Formulating Organisations (SFOs). Findings – Stakeholders were found to be especially concerned about the costs of implementation of the system and how it could, or should, be merged with existing assurance schemes. Another conclusion of the study is that the presence of a strong third independent party supporting the implementation of the welfare assessment system would be the most important influence on the decision whether, or not, to adopt it. Originality/value – This research evaluates the adoption possibilities of a novel Welfare Assessment System and presents the views of different supply chain stakeholders on an adoption of such a system. The main factors affecting the adoption decision are identified and analysed. Contrary to expectations, the costs of adoption of a new welfare assessment system were not considered to be the most important factor affecting the decision of supply chain stakeholders about the adoption of this new welfare system.