Effect of a 5 day enrofloxacin treatment on Salmonella enterica serotype Typhimurium DT104 in the pig

Objectives: There are concerns that the use of enrofloxacin in livestock production may contribute to the development of fluoroquinolone resistance in zoonotic bacteria. The objective of our study was to investigate the effect of a single 5 day enrofloxacin treatment on Salmonella enterica serotype Typhimurium DT104 in a pig model. Results: Our results showed that a single treatment failed to eradicate S. Typhimurium DT104, which continued to be isolated up to 35 days after treatment. We also provide evidence that treatment positively selects for S. Typhimurium DT104 strains that are already nalidixic acid resistant (gyrA Asn-87) or cyclohexane resistant, the latter being indicative of an up-regulated efflux pump. Emergence of fluoroquinolone resistance was not detected during treatment or post-treatment in any of the Salmonella strains monitored. However, the effect of enrofloxacin on the nalidixic acid-resistant and cyclohexane-resistant S. Typhimurium DT104 outlasted the current withdrawal time of 10 days for Baytril (commercial veterinary formulation of enrofloxacin). Conclusions: In conclusion, our study has provided direct evidence that enrofloxacin-treated pigs could be entering abattoirs with higher numbers of quinolone-resistant zoonotic bacteria than untreated pigs, increasing the risk of these entering the food chain.

The Prophetic Sound: a day and night of noise cabaret(symposium of talks and live performances)

'The Prophetic Sound: a day and night of noise cabaret' is the first event hosted by Agency of Noise. This all day event brought together artists and academics whose subject of focus is noise (in creative practice). Artists from across the UK were invited to consider a future post-digital era in which everything with a microchip has malfunctioned, as a thought exercise and starting point for response through sound. In response to Jacques Attali’s claim that music is prophecy, The Prophetic Sound asks us to consider if noise can communicate in an unbridled, unfiltered, way that is somehow not culturally coded -before it becomes sound that is recognised, refined, manipulated and exploited for musical or other cultured purpose. Featuring students from Reading, Brighton, LCC and Goldsmiths alongside more established artists and academics from across the UK, this event brings into focus locations where pattern, timbre, pitch, organisation and sequencing of sounds become distinguishable from noise and asks us to consider, through diversion within such locations, new origins for future communication systems. The Prophetic Sound included talks, films, presentations and performances from: Ryo Ikeshiro / Inigo Wilkins / Neal Spowage / Dane Sutherland / Poulomi Desai / Benedict Drew / AAS / Polly Fibre / Steven Dickie As part of The Prophetic Sound, POLLYFIBRE (Ellison, C.) performed LIVE RECORDING with Amplified Scissors. This industrial activity by POLLYFIBRE short-circuits the complicated chain that is music production. The distinctive roles of consumer, producer, composer, and performer collapse in a series of live ‘cuts’ where vinyl discs are produced with amplified scissors. Production happens through action and action becomes production. A limited edition of 9 flexi discs were produced and available for special collectors at the event.

Introductory remarks

The very first numerical models which were developed more than 20 years ago were drastic simplifications of the real atmosphere and they were mostly restricted to describe adiabatic processes. For prediction of a day or two of the mid tropospheric flow these models often gave reasonable results but the result deteriorated quickly when the prediction was extended further in time. The prediction of the surface flow was unsatisfactory even for short predictions. It was evident that both the energy generating processes as well as the dissipative processes have to be included in numerical models in order to predict the weather patterns in the lower part of the atmosphere and to predict the atmosphere in general beyond a day or two. Present-day computers make it possible to attack the weather forecasting problem in a more comprehensive and complete way and substantial efforts have been made during the last decade in particular to incorporate the non-adiabatic processes in numerical prediction models. The physics of radiational transfer, condensation of moisture, turbulent transfer of heat, momentum and moisture and the dissipation of kinetic energy are the most important processes associated with the formation of energy sources and sinks in the atmosphere and these have to be incorporated in numerical prediction models extended over more than a few days. The mechanisms of these processes are mainly related to small scale disturbances in space and time or even molecular processes. It is therefore one of the basic characteristics of numerical models that these small scale disturbances cannot be included in an explicit way. The reason for this is the discretization of the model's atmosphere by a finite difference grid or the use of a Galerkin or spectral function representation. The second reason why we cannot explicitly introduce these processes into a numerical model is due to the fact that some physical processes necessary to describe them (such as the local buoyance) are a priori eliminated by the constraints of hydrostatic adjustment. Even if this physical constraint can be relaxed by making the models non-hydrostatic the scale problem is virtually impossible to solve and for the foreseeable future we have to try to incorporate the ensemble or gross effect of these physical processes on the large scale synoptic flow. The formulation of the ensemble effect in terms of grid-scale variables (the parameters of the large-scale flow) is called 'parameterization'. For short range prediction of the synoptic flow at middle and high latitudes, very simple parameterization has proven to be rather successful.

Problems in four-dimensional data assimilation

With the introduction of new observing systems based on asynoptic observations, the analysis problem has changed in character. In the near future we may expect that a considerable part of meteorological observations will be unevenly distributed in four dimensions, i.e. three dimensions in space and one in time. The term analysis, or objective analysis in meteorology, means the process of interpolating observed meteorological observations from unevenly distributed locations to a network of regularly spaced grid points. Necessitated by the requirement of numerical weather prediction models to solve the governing finite difference equations on such a grid lattice, the objective analysis is a three-dimensional (or mostly two-dimensional) interpolation technique. As a consequence of the structure of the conventional synoptic network with separated data-sparse and data-dense areas, four-dimensional analysis has in fact been intensively used for many years. Weather services have thus based their analysis not only on synoptic data at the time of the analysis and climatology, but also on the fields predicted from the previous observation hour and valid at the time of the analysis. The inclusion of the time dimension in objective analysis will be called four-dimensional data assimilation. From one point of view it seems possible to apply the conventional technique on the new data sources by simply reducing the time interval in the analysis-forecasting cycle. This could in fact be justified also for the conventional observations. We have a fairly good coverage of surface observations 8 times a day and several upper air stations are making radiosonde and radiowind observations 4 times a day. If we have a 3-hour step in the analysis-forecasting cycle instead of 12 hours, which is applied most often, we may without any difficulties treat all observations as synoptic. No observation would thus be more than 90 minutes off time and the observations even during strong transient motion would fall within a horizontal mesh of 500 km * 500 km.

Design of a forecasting system for ECMWF

As laid out in its convention there are 8 different objectives for ECMWF. One of the major objectives will consist of the preparation, on a regular basis, of the data necessary for the preparation of medium-range weather forecasts. The interpretation of this item is that the Centre will make forecasts once a day for a prediction period of up to 10 days. It is also evident that the Centre should not carry out any real weather forecasting but merely disseminate to the member countries the basic forecasting parameters with an appropriate resolution in space and time. It follows from this that the forecasting system at the Centre must from the operational point of view be functionally integrated with the Weather Services of the Member Countries. The operational interface between ECMWF and the Member Countries must be properly specified in order to get a reasonable flexibility for both systems. The problem of making numerical atmospheric predictions for periods beyond 4-5 days differs substantially from 2-3 days forecasting. From the physical point we can define a medium range forecast as a forecast where the initial disturbances have lost their individual structure. However we are still interested to predict the atmosphere in a similar way as in short range forecasting which means that the model must be able to predict the dissipation and decay of the initial phenomena and the creation of new ones. With this definition, medium range forecasting is indeed very difficult and generally regarded as more difficult than extended forecasts, where we usually only predict time and space mean values. The predictability of atmospheric flow has been extensively studied during the last years in theoretical investigations and by numerical experiments. As has been discussed elsewhere in this publication (see pp 338 and 431) a 10-day forecast is apparently on the fringe of predictability.

Statistical–dynamical downscaling of present day and future precipitation regimes in the Aksu river catchment in Central Asia

A statistical–dynamical downscaling (SDD) approach is applied to determine present day and future high-resolution rainfall distributions in the catchment of the river Aksu at the southern slopes of the Tienshan Mountains, Central Asia. First, a circulation weather type (CWT) classification is employed to define typical lower atmospheric flow regimes from ERA-40 reanalysis data. Selected representatives of each CWT are dynamically downscaled with the regional climate model COSMO-CLM 4.8 at a horizontal grid resolution of 0.0625°, using the ERA-40 reanalysis data as boundary conditions. Finally, the simulated representatives are recombined to obtain a high-resolution rainfall climatology for present day climate. The methodology is also applied to ensemble simulations of three different scenarios of the global climate model ECHAM5/MPI-OM1 to derive projections of rainfall changes until 2100. Comparisons of downscaled seasonal and annual rainfall with observational data suggest that the statistical–dynamical approach is appropriate to capture the observed present-day precipitation climatology over the low lands and the first elevations of the Tienshan Mountains. On the other hand, a strong bias is found at higher altitudes, where precipitation is clearly underestimated by SDD. The application of SDD to the ECHAM5/MPI-OM1 ensemble reveals that precipitation changes by the end of the 21st century depend on the season. While for autumn an increase of seasonal precipitation is found for all simulations, a decrease in precipitation is obtained during winter for most parts of the Aksu catchment. The spread between different ECHAM5/MPI-OM1 ensemble members is strongest in spring, where trends of opposite sign are found. The largest changes in rainfall are simulated for the summer season, which also shows the most pronounced spatial heterogeneity. Most ECHAM5/MPI-OM1 realizations indicate a decrease of annual precipitation over large parts of the Tienshan, and an increase restricted to the southeast of the study area. These results provide a good basis for downscaling present-day and future rainfall distributions for hydrological purposes.

Evaluation of a photosynthesis-based biogenic isoprene emission scheme in JULES and simulation of isoprene emissions under present-day climate conditions

We have incorporated a semi-mechanistic isoprene emission module into the JULES land-surface scheme, as a first step towards a modelling tool that can be applied for studies of vegetation – atmospheric chemistry interactions, including chemistry-climate feedbacks. Here, we evaluate the coupled model against local above-canopy isoprene emission flux measurements from six flux tower sites as well as satellite-derived estimates of isoprene emission over tropical South America and east and south Asia. The model simulates diurnal variability well: correlation coefficients are significant (at the 95 % level) for all flux tower sites. The model reproduces day-to-day variability with significant correlations (at the 95 % confidence level) at four of the six flux tower sites. At the UMBS site, a complete set of seasonal observations is available for two years (2000 and 2002). The model reproduces the seasonal pattern of emission during 2002, but does less well in the year 2000. The model overestimates observed emissions at all sites, which is partially because it does not include isoprene loss through the canopy. Comparison with the satellite-derived isoprene-emission estimates suggests that the model simulates the main spatial patterns, seasonal and inter-annual variability over tropical regions. The model yields a global annual isoprene emission of 535 ± 9 TgC yr−1 during the 1990s, 78 % of which from forested areas.

Generalised Bayesian cloud detection for satellite imagery. part 2: technique and validation for day-time imagery

Numerical Weather Prediction (NWP) fields are used to assist the detection of cloud in satellite imagery. Simulated observations based on NWP are used within a framework based on Bayes' theorem to calculate a physically-based probability of each pixel with an imaged scene being clear or cloudy. Different thresholds can be set on the probabilities to create application-specific cloud masks. Here, the technique is shown to be suitable for daytime applications over land and sea, using visible and near-infrared imagery, in addition to thermal infrared. We use a validation dataset of difficult cloud detection targets for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) achieving true skill scores of 89% and 73% for ocean and land, respectively using the Bayesian technique, compared to 90% and 70%, respectively for the threshold-based techniques associated with the validation dataset.

A 27 day persistence model of near-Earth solar wind conditions: a long lead-time forecast and a benchmark for dynamical models

Geomagnetic activity has long been known to exhibit approximately 27 day periodicity, resulting from solar wind structures repeating each solar rotation. Thus a very simple near-Earth solar wind forecast is 27 day persistence, wherein the near-Earth solar wind conditions today are assumed to be identical to those 27 days previously. Effective use of such a persistence model as a forecast tool, however, requires the performance and uncertainty to be fully characterized. The first half of this study determines which solar wind parameters can be reliably forecast by persistence and how the forecast skill varies with the solar cycle. The second half of the study shows how persistence can provide a useful benchmark for more sophisticated forecast schemes, namely physics-based numerical models. Point-by-point assessment methods, such as correlation and mean-square error, find persistence skill comparable to numerical models during solar minimum, despite the 27 day lead time of persistence forecasts, versus 2–5 days for numerical schemes. At solar maximum, however, the dynamic nature of the corona means 27 day persistence is no longer a good approximation and skill scores suggest persistence is out-performed by numerical models for almost all solar wind parameters. But point-by-point assessment techniques are not always a reliable indicator of usefulness as a forecast tool. An event-based assessment method, which focusses key solar wind structures, finds persistence to be the most valuable forecast throughout the solar cycle. This reiterates the fact that the means of assessing the “best” forecast model must be specifically tailored to its intended use.

Seasonality in Southeast Asian stock markets: some new evidence on day-of-the-week effects

This paper examines the evidence for a day-of-the-week effect in five Southeast Asian stock markets: South Korea, Malaysia, the Philippines, Taiwan and Thailand. Findings indicate significant seasonality for three of the five markets. Market risk, proxied by the return on the FTA World Price Index, is not sufficient to explain this calendar anomaly. Although an extension of the risk-return equation to incorporate interactive seasonal dummy variables can explain some significant day-of-the-week effects, market risk alone appears insufficient to characterize this phenomenon.

Present-day and mid-Holocene biomes reconstructed from pollen and plant macrofossil data from the former Soviet Union and Mongolia

Fossil pollen data supplemented by tree macrofossil records were used to reconstruct the vegetation of the Former Soviet Union and Mongolia at 6000 years. Pollen spectra were assigned to biomes using the plant-functional-type method developed by Prentice et al. (1996). Surface pollen data and a modern vegetation map provided a test of the method. This is the first time such a broad-scale vegetation reconstruction for the greater part of northern Eurasia has been attempted with objective techniques. The new results confirm previous regional palaeoenvironmental studies of the mid-Holocene while providing a comprehensive synopsis and firmer conclusions. West of the Ural Mountains temperate deciduous forest extended both northward and southward from its modern range. The northern limits of cool mixed and cool conifer forests were also further north than present. Taiga was reduced in European Russia, but was extended into Yakutia where now there is cold deciduous forest. The northern limit of taiga was extended (as shown by increased Picea pollen percentages, and by tree macrofossil records north of the present-day forest limit) but tundra was still present in north-eastern Siberia. The boundary between forest and steppe in the continental interior did not shift substantially, and dry conditions similar to present existed in western Mongolia and north of the Aral Sea.

Solar wind-magnetosphere coupling functions on timescales of 1 day to 1 year

There are no direct observational methods for determining the total rate at which energy is extracted from the solar wind by the magnetosphere. In the absence of such a direct measurement, alternative means of estimating the energy available to drive the magnetospheric system have been developed using different ionospheric and magnetospheric indices as proxies for energy consumption and dissipation and thus the input. The so-called coupling functions are constructed from the parameters of the interplanetary medium, as either theoretical or empirical estimates of energy transfer, and the effectiveness of these coupling functions has been evaluated in terms of their correlation with the chosen index. A number of coupling functions have been studied in the past with various criteria governing event selection and timescale. The present paper contains an exhaustive survey of the correlation between geomagnetic activity and the near-Earth solar wind and two of the planetary indices at a wide variety of timescales. Various combinations of interplanetary parameters are evaluated with careful allowance for the effects of data gaps in the interplanetary data. We show that the theoretical coupling, P�, function first proposed by Vasyliunas et al. is superior at all timescales from 1-day to 1-year.