Numerical modelling of low temperature plasma

The intention of this thesis is to gain a better understanding of basic physical processes occurring in low temperature plasmas. This is achieved by applying both analytic and numerical models. Low temperature plasmas are found in both technological and astrophysical contexts. Three different situations are investigated: an instability in electronegative plasmas; electron avalanches during plasma initiation; and a phenomenon called the Critical Ionisation Velocity interaction. Industrial plasma discharges with electronegative gases are found to be unstable in certain conditions. Fluctuations in light emission, particle number densities and potential are observed. The instability has been reproduced in a variety of experiments. Reports from the experiments are discussed to characterise the key features of the instability. An, as yet un-considered, physical process that could explain the instability is introduced. The instability relies on the plasma's transparency to the electric field. This mechanism is investigated using simple zero-dimensional numerical and analytic models. The results from the models are compared to experimental results. The calculated frequencies are in good agreement with the experimental measurements. This shows that the instability mechanism described here is relevant. For the remaining two problems a three-dimensional particle model is constructed. This model calculates the trajectories of each individual particle. The potential field is solved self-consistently on a computational mesh. Poisson's equation is solved using a Multigrid technique. This iterative solution method uses many grids, of different resolutions, to smooth the error on all spatial scales. The mathematical foundation and details of the components of the Multigrid method are presented. Several test cases where analytic solutions of Poisson's equation exist are used to determine the accuracy of the solver. The implemented solver is found to be both efficient and accurate. Collisions are vitally important to the evolution of plasmas. The chemistry resulting from collisions is the reason why plasmas are so useful in technological applications. Electron collisions are included in the particle model using a Monte-Carlo technique. A basic method is given and several improvements are described. The most efficient combination of improvements is determined through a series of test cases. The error resulting from the collision selection process is characterised. Technological plasmas are formed from the electrical breakdown of a neutral gas. At atmospheric pressure the breakdown occurs as an electron avalanche. The particle model is used to simulate the nanosecond evolution of the avalanche from a single electron-ion pair. Special attention is paid to the inelastic collisions and the creation of metastables. The inelastic losses are used to estimate the photon emission from the electron avalanche. The Critical Ionisation Velocity phenomena is investigated using the particle model. When a neutral gas streams across a magnetised plasma the ionisation rate increases rapidly if the speed of the neutrals exceeds a critical value. Collisions between neutrals and positive ions create pockets of unbalanced negative charge. Electrons in these pockets are accelerated by their potential field and can reach energies capable of ionisation. The evolution of such an electron overdensity is simulated and their energy gain under different density and magnetic field conditions is calculated. The results from the simulation may explain the discrepancy between laboratory and space experiments

0.395 THz Surface Wave Oscillator for DNP-NMR Applications

The simulation and design of an oversized, two-dimensional, periodic surface lattice (2D PSL) interaction cavity used within a 0.395 THz, pulsed radiation source is presented. Powerful, pulsed radiation with good spectral purity is demonstrated. The device is well-suited for use in DNP-NMR spectroscopy and has numerous other applications due to the scalability of the interaction cavity allowing for radiation output at different frequencies. The device exploits the coupling of volume and surface fields in the 2D PSL interaction cavity to excite a single cavity eigenmode. The observed output power is 13.5kW and the efficiency of the device is 27

Does increased atmospheric resolution improve seasonal climate predictions?

We assess the impact of atmospheric horizontal resolution on the prediction skill and fidelity of seasonal forecasts. We show the response to an increase of atmospheric resolution from 0.8 to 0.3⁰ horizontal grid spacing in parallel ensembles of forecasts. Changes in the prediction skill of major modes of tropical El Nino Southern Oscillation (ENSO) and extratropical North Atlantic Oscillation (NAO) variability are small and not detected and there is no discernible impact on the weak signal-to-noise ratio in seasonal predictions of the winter NAO at this range of resolutions. Although studies have shown improvements in the simulation of tropical cyclones as model resolution is increased, we find little impact on seasonal prediction skill of either their numbers or intensity. Over this range of resolutions it appears that the benefit of increasing atmospheric resolution to seasonal climate predictions is minimal. However, at yet finer scales there appears to be increased eddy feedback which could strengthen weak signals in predictions of the NAO. Until prediction systems can be run operationally at these scales, it may be better to use additional computing resources for other enhancements such as increased ensemble size, for which there is a clear benefit in extratropical seasonal prediction skill

Numerical analysis of high-power X-band sources, at low magnetic confinement, for use in a multi-source array

High-power microwave sources are typically relativistic in nature, employing multi-kilo-ampere electron beams that require significant magnetic confinement for efficient operation. As the desired output power increases so does the complexity, and overall energy requirements, of the source. It can therefore be advantageous to consider the use of several, moderate-power, sources operating as a phased array; for an array of N sources the far-field peak intensity scales as N2, and the peak-of-field may be steered electronically by varying the relative phases of the different output signals. In this paper we present the numerical analysis of a short-pulse (∼1ns) X-band backward-wave oscillator, driven by a 210keV, 1.4kA electron beam, suitable for use as the radiative element in such an array. Investigation of the required magnetic confinement showed two peaks in performance, with the highest efficiency, of 43%, predicted at the low magnetic confinement peak at 0.3T, corresponding to 125MW peak output power. The magnitude, and timing, of the peak in the output pulse were functions of the rise-time of the electron beam energy, with longer rise-times resulting in delayed peak-of-field and lower peak output power. When operating in an array, to maintain effective output in the region of N2, it was determined that the beam rise-times, across all sources, should be ≤150ps with the adjustment of the relative timing between output’s being ±30ps

Re-emergence of North Atlantic subsurface ocean temperature anomalies in a seasonal forecast system

A high-resolution coupled ocean atmosphere model is used to study the effects of seasonal re-emergence of North Atlantic subsurface ocean temperature anomalies on northern hemisphere winter climate. A 50-member control ensemble is integrated from 1 September 2007 to 28 February 2008 and compared with a parallel ensemble with perturbed ocean initial conditions. The perturbation consists of a density-compensated subsurface Atlantic temperature anomaly corresponding to the observed subsurface temperature anomaly for September 2010. The experiment is repeated for two atmosphere horizontal resolutions (~ 60 km and ~ 25 km) in order to determine whether the sensitivity of the atmosphere to re-emerging temperature anomalies is dependent on resolution. A wide range of re-emergence behavior is found within the perturbed ensembles. While the observations seem to indicate that most of the re-emergence is occurring in November, most members of the ensemble show re-emergence occurring later in the winter. However, when re-emergence does occur it is preceded by an atmospheric pressure pattern that induces a strong flow of cold, dry air over the mid-latitude Atlantic, and enhances oceanic latent heat loss. In response to re-emergence (negative SST anomalies), there is reduced latent heat loss, less atmospheric convection, a reduction in eddy kinetic energy and positive low-level pressure anomalies downstream. Within the framework of a seasonal forecast system the results highlight the atmospheric conditions required for re-emergence to take place and the physical processes that may lead to a significant effect on the winter atmospheric circulation

Indian summer monsoon onset forecast skill in the UK Met Office initialized coupled seasonal forecasting system (GloSea5-GC2)

Accurate and precise forecasting of the Indian monsoon is important for the socio-economic security of India, with improvements in agriculture and associated sectors from prediction of the monsoon onset. In this study we establish the skill of the UK Met Office coupled initialized global seasonal forecasting system, GloSea5-GC2, in forecasting Indian monsoon onset. We build on previous work that has demonstrated the good skill of GloSea5 at forecasting interannual variations of the seasonal mean Indian monsoon using measures of large-scale circulation and local precipitation. We analyze the summer hindcasts from a set of three springtime start-dates in late April/early May for the 20-year hindcast period (1992-2011). The hindcast set features at least fifteen ensemble members for each year and is analyzed using five different objective monsoon indices. These indices are designed to examine large and local-scale measures of the monsoon circulation, hydrological changes, tropospheric temperature gradient, or rainfall for single value (area-averaged) or grid-point measures of the Indian monsoon onset. There is significant correlation between onset dates in the model and those found in reanalysis. Indices based on large-scale dynamic and thermodynamic indices are better at estimating monsoon onset in the model rather than local-scale dynamical and hydrological indices. This can be attributed to the model's better representation of large-scale dynamics compared to local-scale features. GloSea5 may not be able to predict the exact date of monsoon onset over India, but this study shows that the model has a good ability at predicting category-wise monsoon onset, using early, normal or late tercile categories. Using a grid-point local rainfall onset index, we note that the forecast skill is highest over parts of central India, the Gangetic plains, and parts of coastal India - all zones of extensive agriculture in India. El Niño Southern Oscillation (ENSO) forcing in the model improves the forecast skill of monsoon onset when using a large-scale circulation index, with late monsoon onset coinciding with El Niño conditions and early monsoon onset more common in La Niña years. The results of this study suggest that GloSea5's ensemble-mean forecast may be used for reliable Indian monsoon onset prediction a month in advance despite systematic model errors

Tropical rainfall predictions from multiple seasonal forecast systems

We quantify seasonal prediction skill of tropical winter rainfall in 14 climate forecast systems. High levels of seasonal prediction skill exist for year‐to‐year rainfall variability in all tropical ocean basins. The tropical East Pacific is the most skilful region, with very high correlation scores, and the tropical West Pacific is also highly skilful. Predictions of tropical Atlantic and Indian Ocean rainfall show lower but statistically significant scores. We compare prediction skill (measured against observed variability) with model predictability (using single forecasts as surrogate observations). Model predictability matches prediction skill in some regions but it is generally greater, especially over the Indian Ocean. We also find significant inter‐basin connections in both observed and predicted rainfall. Teleconnections between basins due to El Niño–Southern Oscillation (ENSO) appear to be reproduced in multi‐model predictions and are responsible for much of the prediction skill. They also explain the relative magnitude of inter‐annual variability, the relative magnitude of predictable rainfall signals and the ranking of prediction skill across different basins. These seasonal tropical rainfall predictions exhibit a severe wet bias, often in excess of 20% of mean rainfall. However, we find little direct relationship between bias and prediction skill. Our results suggest that future prediction systems would be best improved through better model representation of inter‐basin rainfall connections as these are strongly related to prediction skill, particularly in the Indian and West Pacific regions. Finally, we show that predictions of tropical rainfall alone can generate highly skilful forecasts of the main modes of extratropical circulation via linear relationships that might provide a useful tool to interpret real‐time forecasts

Memory for sequence order in songs

Previous research on memory for music has typically measured RT and accuracy in tests of recall and recognition of songs. Little research, however, has focused on the ability of people to switch their attention between various parts of a song to answer questions about those parts. One hypothesis is that, because music unfolds in time, one’s ability to consider different parts of a song might be influenced by where in the song someone begins their consideration, and also in which direction they are then asked to switch their attention, with the overriding bias being in a forwards direction. The current study tested this forward bias hypothesis. Fifty people were asked to identify whether the second excerpt of a pair of excerpts taken from a song came ‘before’ or ‘after’ the first excerpt in the normal course of the song. Seven pairs of excerpts, three pairs falling before the target line, and four pairs occurring after the target line, were presented for each of 8 Popular and 2 new songs. It was predicted that RTs for identifying the target lines occurring ‘after’ the probe line would be shorter than those coming ‘before’ the probe line. Results supported this hypothesis. The familiarity of a song did not affect this result. A companion experiment that compared performance on this task for musicians and non-­‐musicians replicated these results, but indicated no effect of musical expertise. These results support the hypothesis that memory for songs is biased in a forward direction