Plasma structure within poleward-moving cusp/cleft auroral transients: EISCAT Svalbard radar observations and an explanation in terms of large local time extent of events

We report high-resolution observations of the southward-IMF cusp/cleft ionosphere made on December 16th 1998 by the EISCAT (European incoherent scatter) Svalbard radar (ESR), and compare them with observations of dayside auroral luminosity, as seen at a wavelength of 630 nm by a meridian scanning photometer at Ny Alesund, and of plasma flows, as seen by the CUTLASS (co-operative UK twin location auroral sounding system) Finland HF radar. The optical data reveal a series of poleward-moving transient red-line (630 nm) enhancements, events that have been associated with bursts in the rate of magnetopause reconnection generating new open flux. The combined observations at this time have strong similarities to predictions of the effects of soft electron precipitation modulated by pulsed reconnection, as made by Davis and Lockwood (1996); however, the effects of rapid zonal flow in the ionosphere, caused by the magnetic curvature force on the newly opened field lines, are found to be a significant additional factor. In particular, it is shown how enhanced plasma loss rates induced by the rapid convection can explain two outstanding anomalies of the 630 nm transients, namely how minima in luminosity form between the poleward-moving events and how events can re-brighten as they move poleward. The observations show how cusp/cleft aurora and transient poleward-moving auroral forms appear in the ESR data and the conditions which cause enhanced 630 nm emission in the transients: they are an important first step in enabling the ESR to identify these features away from the winter solstice when supporting auroral observations are not available.

Switchable amplification of vibrational circular dichroism as a probe of local chiral structure

A new method to detect the vibrational circular dichroism (VCD) of a localized part of a chiral molecular system is reported. A local VCD amplifier was implemented, and the distance dependence of the amplification was investigated in a series of peptides. The results indicate a characteristic distance of 2.0±0.3 bonds, which suggests that the amplification is a localized phenomenon. The amplifier can be covalently coupled to a specific part of a molecule, and can be switched ON and OFF electrochemically. By subtracting the VCD spectra obtained when the amplifier is in the ON and OFF states, the VCD of the local environment of the amplifier can be separated from the total VCD spectrum. Switchable local VCD amplification thus makes it possible to “zoom in” on a specific part of a chiral molecule.

ReadingAct RGB-D action dataset and human action recognition from local features

For general home monitoring, a system should automatically interpret people’s actions. The system should be non-intrusive, and able to deal with a cluttered background, and loose clothes. An approach based on spatio-temporal local features and a Bag-of-Words (BoW) model is proposed for single-person action recognition from combined intensity and depth images. To restore the temporal structure lost in the traditional BoW method, a dynamic time alignment technique with temporal binning is applied in this work, which has not been previously implemented in the literature for human action recognition on depth imagery. A novel human action dataset with depth data has been created using two Microsoft Kinect sensors. The ReadingAct dataset contains 20 subjects and 19 actions for a total of 2340 videos. To investigate the effect of using depth images and the proposed method, testing was conducted on three depth datasets, and the proposed method was compared to traditional Bag-of-Words methods. Results showed that the proposed method improves recognition accuracy when adding depth to the conventional intensity data, and has advantages when dealing with long actions.

Preferred response of the East Asian summer monsoon to local and non-local anthropogenic sulphur dioxide emissions

In this study, the atmospheric component of a state-of-the-art climate model (HadGEM2-ES) that includes earth system components such as interactive chemistry and eight species of tropospheric aerosols considering aerosol direct, indirect, and semi-direct effects, has been used to investigate the impacts of local and non-local emissions of anthropogenic sulphur dioxide on the East Asian summer monsoon (EASM). The study focuses on the fast responses (including land surface feedbacks, but without sea surface temperature feedbacks) to sudden changes in emissions from Asia and Europe. The initial responses, over days 1–40, to Asian and European emissions show large differences. The response to Asian emissions involves a direct impact on the sulphate burden over Asia, with immediate consequences for the shortwave energy budget through aerosol–radiation and aerosol–cloud interactions. These changes lead to cooling of East Asia and a weakening of the EASM. In contrast, European emissions have no significant impact on the sulphate burden over Asia, but they induce mid-tropospheric cooling and drying over the European sector. Subsequently, however, this cold and dry anomaly is advected into Asia, where it induces atmospheric and surface feedbacks over Asia and the Western North Pacific (WNP), which also weaken the EASM. In spite of very different perturbations to the local aerosol burden in response to Asian and European sulphur dioxide emissions, the large scale pattern of changes in land–sea thermal contrast, atmospheric circulation and local precipitation over East Asia from days 40 onward exhibits similar structures, indicating a preferred response, and suggesting that emissions from both regions likely contributed to the observed weakening of the EASM. Cooling and drying of the troposphere over Asia, together with warming and moistening over the WNP, reduces the land–sea thermal contrast between the Asian continent and surrounding oceans. This leads to high sea level pressure (SLP) anomalies over Asia and low SLP anomalies over the WNP, associated with a weakened EASM. In response to emissions from both regions warming and moistening over the WNP plays an important role and determines the time scale of the response.

Local and landscape effects on bee functional guilds in pigeon pea crops in Kenya

Pollinators face many challenges within agricultural systems due to landscape changes and intensification which can affect resource availability that can impact pollination services. This paper examines pigeon pea pollination and considers how landscape context and agricultural intensification in terms of pesticide use affects the abundance of bees characterized by species guilds on crops. The study was conducted on six paired farms across a gradient of habitat complexity based on the distance of each farm from adjacent semi-natural vegetation in Kibwezi Sub-county, Kenya. The study found that farms which do not use insecticides in farm management, but are in close proximity to natural habitat have greater bee guild abundance, but at further distances, overall abundance is reduced with or without insecticide use. At 1 km landscape radius, the complexity of habitats but not patch size had a positive impact on the abundance of cavity nesting bees and mason bees, which can be attributed to the interspersion of the small-holder farms with semi-natural habitats across the landscapes producing mosaics of heterogeneous habitats. The study revealed the strongest relationships between fruit set and bee abundance to be with the carpenter bee, social bee and solitary bee guilds, which are among the most abundant bees visiting pigeon pea flowers in this system. Our findings provide the foundation for conservation efforts by identifying which bee guilds pollinated pigeon peas. From this study, we suggest managing the floral and nesting resources that would best support the most abundant crop pollinators, and also reducing insecticide application to the crop.

Governing calculative practices: An investigation of development viability modelling in the English planning system

Over the last decade the English planning system has placed greater emphasis on the financial viability of development. ‘Calculative’ practices have been used to quantify and capture land value uplifts. Development viability appraisal (DVA) has become a key part of the evidence base used in planning decision-making and informs both ‘site-specific’ negotiations about the level of land value capture for individual schemes and ‘area-wide’ planning policy formation. This paper investigates how implementation of DVA is governed in planning policy formation. It is argued that the increased use of DVA raises important questions about how planning decisions are made and operationalised, not least because DVA is often poorly understood by some key stakeholders. The paper uses the concept of governance to thematically analyse semi-structured interviews conducted with the producers of DVAs and considers key procedural issues including (in)consistencies in appraisal practices, levels of stakeholder consultation and the potential for client and producer bias. Whilst stakeholder consultation is shown to be integral to the appraisal process in order to improve the quality of the appraisals and to legitimise the outputs, participation is restricted to industry experts and excludes some interest groups, including local communities. It is concluded that, largely because of its recent adoption and knowledge asymmetries between local planning authorities and appraisers, DVA is a weakly governed process characterised by emerging and contested guidance and is therefore ‘up for grabs’.

A global empirical system for probabilistic seasonal climate prediction

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961–2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño–Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

An assessment of Indian monsoon seasonal forecasts and mechanisms underlying monsoon interannual variability in the Met Office GloSea5-GC2 system

We assess Indian summer monsoon seasonal forecasts in GloSea5-GC2, the Met Office fully coupled subseasonal to seasonal ensemble forecasting system. Using several metrics, GloSea5-GC2 shows similar skill to other state-of-the-art forecast systems. The prediction skill of the large-scale South Asian monsoon circulation is higher than that of Indian monsoon rainfall. Using multiple linear regression analysis we evaluate relationships between Indian monsoon rainfall and five possible drivers of monsoon interannual variability. Over the time period studied (1992-2011), the El Nino-Southern Oscillation (ENSO) and the Indian Ocean dipole (IOD) are the most important of these drivers in both observations and GloSea5-GC2. Our analysis indicates that ENSO and its teleconnection with the Indian rainfall are well represented in GloSea5-GC2. However, the relationship between the IOD and Indian rainfall anomalies is too weak in GloSea5-GC2, which may be limiting the prediction skill of the local monsoon circulation and Indian rainfall. We show that this weak relationship likely results from a coupled mean state bias that limits the impact of anomalous wind forcing on SST variability, resulting in erroneous IOD SST anomalies. Known difficulties in representing convective precipitation over India may also play a role. Since Indian rainfall responds weakly to the IOD, it responds more consistently to ENSO than in observations. Our assessment identifies specific coupled biases that are likely limiting GloSea5-GC2 prediction skill, providing targets for model improvement.

Atmospheric electrification in dusty, reactive gases in the solar system and beyond

Detailed observations of the solar system planets reveal a wide variety of local atmospheric conditions. Astronomical observations have revealed a variety of extrasolar planets none of which resembles any of the solar system planets in full. Instead, the most massive amongst the extrasolar planets, the gas giants, appear very similar to the class of (young) Brown Dwarfs which are amongst the oldest objects in the universe. Despite of this diversity, solar system planets, extrasolar planets and Brown Dwarfs have broadly similar global temperatures between 300K and 2500K. In consequence, clouds of different chemical species form in their atmospheres. While the details of these clouds differ, the fundamental physical processes are the same. Further to this, all these objects were observed to produce radio and X-ray emission. While both kinds of radiation are well studied on Earth and to a lesser extent on the solar system planets, the occurrence of emission that potentially originate from accelerated electrons on Brown Dwarfs, extrasolar planets and protoplanetary disks is not well understood yet. This paper offers an interdisciplinary view on electrification processes and their feedback on their hosting environment in meteorology, volcanology, planetology and research on extrasolar planets and planet formation.

A new method for the characterisation and verification of local spatial predictability for convective scale ensembles

The use of kilometre-scale ensembles in operational forecasting provides new challenges for forecast interpretation and evaluation to account for uncertainty on the convective scale. A new neighbourhood based method is presented for evaluating and characterising the local predictability variations from convective scale ensembles. Spatial scales over which ensemble forecasts agree (agreement scales, S^A) are calculated at each grid point ij, providing a map of the spatial agreement between forecasts. By comparing the average agreement scale obtained from ensemble member pairs (S^A(mm)_ij), with that between members and radar observations (S^A(mo)_ij), this approach allows the location-dependent spatial spread-skill relationship of the ensemble to be assessed. The properties of the agreement scales are demonstrated using an idealised experiment. To demonstrate the methods in an operational context the S^A(mm)_ij and S^A(mo)_ij are calculated for six convective cases run with the Met Office UK Ensemble Prediction System. The S^A(mm)_ij highlight predictability differences between cases, which can be linked to physical processes. Maps of S^A(mm)_ij are found to summarise the spatial predictability in a compact and physically meaningful manner that is useful for forecasting and for model interpretation. Comparison of S^A(mm)_ij and S^A(mo)_ij demonstrates the case-by-case and temporal variability of the spatial spread-skill, which can again be linked to physical processes.

Closed-loop feedback computation model of dynamical reputation based on the local trust evaluation in business-to-consumer e-commerce

Trust and reputation are important factors that influence the success of both traditional transactions in physical social networks and modern e-commerce in virtual Internet environments. It is difficult to define the concept of trust and quantify it because trust has both subjective and objective characteristics at the same time. A well-reported issue with reputation management system in business-to-consumer (BtoC) e-commerce is the “all good reputation” problem. In order to deal with the confusion, a new computational model of reputation is proposed in this paper. The ratings of each customer are set as basic trust score events. In addition, the time series of massive ratings are aggregated to formulate the sellers’ local temporal trust scores by Beta distribution. A logical model of trust and reputation is established based on the analysis of the dynamical relationship between trust and reputation. As for single goods with repeat transactions, an iterative mathematical model of trust and reputation is established with a closed-loop feedback mechanism. Numerical experiments on repeated transactions recorded over a period of 24 months are performed. The experimental results show that the proposed method plays guiding roles for both theoretical research into trust and reputation and the practical design of reputation systems in BtoC e-commerce.