Spectral absorption of marine stratocumulus clouds derived from in situ cloud radiation measurements

A multiwavelength scanning radiometer was used to measure the angular distribution of scattered radiation deep within a cloud layer at discrete wavelengths between 0.5 and 2.3 microns. The relative angular distribution of the intensity field at each wavelength is used to determine the similarity parameter, and hence single scattering albedo, of the cloud at that wavelength using the diffusion domain method. In addition to the spectral similarity parameter, the analysis provides a good estimate of the optical thickness of the cloud beneath the aircraft. In addition to the radiation measurements, microphysical and thermodynamic measurements were obtained from which the expected similarity parameter spectrum was calculated using accepted values of the refractive index of liquid water and the transmission function of water vapor. An analysis is presented for the results obtained for a 50 km section of clean marine stratocumulus clouds on 10 July 1987. These observations were obtained off the coast of California from the University of Washington Convair C-131A aircraft as part of the First ISCCP Regional Experiment (FIRE). A comparison of the experimentally-derived similarity parameter spectrum with that expected theoretically from the cloud droplet size distribution measured simultaneously from the aircraft is presented. The measurements and theory are in very close agreement for this case of clean maritime clouds

Cloud absorption properties as derived from airborne measurements of scattered radiation within clouds

Researchers briefly review the diffusion domain method for deriving the cloud similarity parameter and present preliminary analyses of the results thus far obtained. The presentation concentrates on the following points: (1) intercomparison of calibrated reflected intensities between the cloud absorption radiometer and the U.K. multispectral cloud radiometer; (2) quality control tests required to select those portions of an aircraft flight for which measurements are obtained within the diffusion domain; (3) case studies of the spectral similarity parameter of marine stratocumulus clouds; and comparisons of the experimentally-derived similarity parameter spectrum with that expected theoretically from the cloud droplet size distribution obtained from in situ observations

Rotor redesign for a highly loaded 1800 ft/sec tip speed fan. 3: Laser Doppler velocimeter report

Laser Doppler velocimeter (LDV) techniques were employed for testing a highly loaded, 550 m/sec (1800 ft/sec) tip speed, test fan stage, the objective to provide detailed mapping of the upstream, intrablade, and downstream flowfields of the rotor. Intrablade LDV measurements of velocity and flow angle were obtained along four streamlines passing through the leading edge at 45%, 69%, 85%, and 95% span measured from hub to tip, at 100% of design speed, peak efficiency; 100% speed, near surge; and 95% speed, peak efficiency. At the design point, most passages appeared to have a strong leading edge shock, which moved forward with increasing strength near surge and at part speeds. The flow behind the shock was of a complex mixed subsonic and supersonic form. The intrablade flowfields were found to be significantly nonperiodic at 100% design speed, peak efficiency

A Bayesian parameter estimation approach to pulsar time-of-arrival analysis

The increasing sensitivities of pulsar timing arrays to ultra-low frequency (nHz) gravitational waves promises to achieve direct gravitational wave detection within the next 5-10 years. While there are many parallel efforts being made in the improvement of telescope sensitivity, the detection of stable millisecond pulsars and the improvement of the timing software, there are reasons to believe that the methods used to accurately determine the time-of-arrival (TOA) of pulses from radio pulsars can be improved upon. More specifically, the determination of the uncertainties on these TOAs, which strongly affect the ability to detect GWs through pulsar timing, may be unreliable. We propose two Bayesian methods for the generation of pulsar TOAs starting from pulsar "search-mode" data and pre-folded data. These methods are applied to simulated toy-model examples and in this initial work we focus on the issue of uncertainties in the folding period. The final results of our analysis are expressed in the form of posterior probability distributions on the signal parameters (including the TOA) from a single observation.Comment: 16 pages, 4 figure

Agent-based homeostatic control for green energy in the smart grid

With dwindling non-renewable energy reserves and the adverse effects of climate change, the development of the smart electricity grid is seen as key to solving global energy security issues and to reducing carbon emissions. In this respect, there is a growing need to integrate renewable (or green) energy sources in the grid. However, the intermittency of these energy sources requires that demand must also be made more responsive to changes in supply, and a number of smart grid technologies are being developed, such as high-capacity batteries and smart meters for the home, to enable consumers to be more responsive to conditions on the grid in real-time. Traditional solutions based on these technologies, however, tend to ignore the fact that individual consumers will behave in such a way that best satisfies their own preferences to use or store energy (as opposed to that of the supplier or the grid operator). Hence, in practice, it is unclear how these solutions will cope with large numbers of consumers using their devices in this way. Against this background, in this paper, we develop novel control mechanisms based on the use of autonomous agents to better incorporate consumer preferences in managing demand. These agents, residing on consumers' smart meters, can both communicate with the grid and optimise their owner's energy consumption to satisfy their preferences. More specifically, we provide a novel control mechanism that models and controls a system comprising of a green energy supplier operating within the grid and a number of individual homes (each possibly owning a storage device). This control mechanism is based on the concept of homeostasis whereby control signals are sent to individual components of a system, based on their continuous feedback, in order to change their state so that the system may reach a stable equilibrium. Thus, we define a new carbon-based pricing mechanism for this green energy supplier that takes advantage of carbon-intensity signals available on the internet in order to provide real-time pricing. The pricing scheme is designed in such a way that it can be readily implemented using existing communication technologies and is easily understandable by consumers. Building upon this, we develop new control signals that the supplier can use to incentivise agents to shift demand (using their storage device) to times when green energy is available. Moreover, we show how these signals can be adapted according to changes in supply and to various degrees of penetration of storage in the system. We empirically evaluate our system and show that, when all homes are equipped with storage devices, the supplier can significantly reduce its reliance on other carbon-emitting power sources to cater for its own shortfalls. By so doing, the supplier reduces the carbon emission of the system by up to 25% while the consumer reduces its costs by up to 14.5%. Finally, we demonstrate that our homeostatic control mechanism is not sensitive to small prediction errors and the supplier is incentivised to accurately predict its green production to minimise costs

Gravitational wave detection using pulsars: status of the Parkes Pulsar Timing Array project

The first direct detection of gravitational waves may be made through observations of pulsars. The principal aim of pulsar timing array projects being carried out worldwide is to detect ultra-low frequency gravitational waves (f ~ 10^-9 to 10^-8 Hz). Such waves are expected to be caused by coalescing supermassive binary black holes in the cores of merged galaxies. It is also possible that a detectable signal could have been produced in the inflationary era or by cosmic strings. In this paper we review the current status of the Parkes Pulsar Timing Array project (the only such project in the Southern hemisphere) and compare the pulsar timing technique with other forms of gravitational-wave detection such as ground- and space-based interferometer systems.Comment: Accepted for publication in PAS

Emotional disorders: Cluster 4 of the proposed meta-structure for DSM-V and ICD-11

Background The extant major psychiatric classifications DSM-IV, and ICD-10, are atheoretical and largely descriptive. Although this achieves good reliability, the validity of a medical diagnosis would be greatly enhanced by an understanding of risk factors and clinical manifestations. In an effort to group mental disorders on the basis of aetiology, five clusters have been proposed. This paper considers the validity of the fourth cluster, emotional disorders, within that proposal.Method We reviewed the literature in relation to 11 validating criteria proposed by a Study Group of the DSM-V Task Force, as applied to the cluster of emotional disorders.Results An emotional cluster of disorders identified using the 11 validators is feasible. Negative affectivity is the defining feature of the emotional cluster. Although there are differences between disorders in the remaining validating criteria, there are similarities that support the feasibility of an emotional cluster. Strong intra-cluster co-morbidity may reflect the action of common risk factors and also shared higher-order symptom dimensions in these emotional disorders.Conclusion Emotional disorders meet many of the salient criteria proposed by the Study Group of the DSM-V Task Force to suggest a classification cluster.</p

Constraining the coalescence rate of supermassive black-hole binaries using pulsar timing

Pulsar timing observations are used to place constraints on the rate of coalescence of supermassive black-hole (SMBH) binaries as a function of mass and redshift. In contrast to the indirect constraints obtained from other techniques, pulsar timing observations provide a direct constraint on the black-hole merger rate. This is possible since pulsar timing is sensitive to the gravitational waves (GWs) emitted by these sources in the final stages of their evolution. We find that upper bounds calculated from the recently published Parkes Pulsar Timing Array data are just above theoretical predictions for redshifts below 10. In the future, with improved timing precision and longer data spans, we show that a non-detection of GWs will rule out some of the available parameter space in a particular class of SMBH binary merger models. We also show that if we can time a set of pulsars to 10ns timing accuracy, for example, using the proposed Square Kilometre Array, it should be possible to detect one or more individual SMBH binary systems

Does risk aversion affect transmission and generation planning? A Western North America case study

We investigate the effects of risk aversion on optimal transmission and generation expansion planning in a competitive and complete market. To do so, we formulate a stochastic model that minimizes a weighted average of expected transmission and generation costs and their conditional value at risk (CVaR). We show that the solution of this optimization problem is equivalent to the solution of a perfectly competitive risk-averse Stackelberg equilibrium, in which a risk-averse transmission planner maximizes welfare after which risk-averse generators maximize profits. This model is then applied to a 240-bus representation of the Western Electricity Coordinating Council, in which we examine the impact of risk aversion on levels and spatial patterns of generation and transmission investment. Although the impact of risk aversion remains small at an aggregate level, state-level impacts on generation and transmission investment can be significant, which emphasizes the importance of explicit consideration of risk aversion in planning models