Cyanopolyynes in hot cores: modelling G305.2+0.2

We present results from a time-dependent gas-phase chemical model of a hot core based on the physical conditions of G305.2+0.2. While the cyanopolyyne HC₃N has been observed in hot cores, the longer chained species, HC₅N, HC₇N and HC₉N, have not been considered as the typical hot-core species. We present results which show that these species can be formed under hot core conditions. We discuss the important chemical reactions in this process and, in particular, show that their abundances are linked to the parent species acetylene which is evaporated from icy grain mantles. The cyanopolyynes show promise as 'chemical clocks' which may aid future observations in determining the age of hot core sources. The abundance of the larger cyanopolyynes increases and decreases over relatively short time-scales,  ∼10^2.5 yr  . We present results from a non-local thermodynamic equilibrium statistical equilibrium excitation model as a series of density, temperature and column density dependent contour plots which show both the line intensities and several line ratios. These aid in the interpretation of spectral-line data, even when there is limited line information available. In particular, non-detections of HC₅N and HC₇N in Walsh et al. are analysed and discussed.     

Adaptive neuro-fuzzy evaluation of wind farm power production as function of wind speed and direction

Wind velocity assumes a critical part for measuring the power created by the wind turbines. Nonetheless, power production from wind has a few weaknesses. One significant issue is that wind is a discontinuous energy source which implies that there exists substantial variability in the generation of vigor because of different variables, for example, wind speed. Wind direction is a significant variable for proficient turbine control for getting the most energy with a given wind speed. Taking into account the conjectures on wind heading, it might be conceivable to adjust the turbine to the wind bearing to get the most energy yield. Since both forecasts of wind speed and direction are basic for effective wind energy collecting it is crucial to develop a methodology for estimation of wind speed and direction and afterwards to estimate wind farm power production as function of wind pace and heading distribution. Despite the fact that various numerical functions have been proposed for demonstrating the wind speed and direction frequency distribution, there are still disadvantages of the models like very demanding in terms of calculation time. In this investigation adaptive neuro-fuzzy inference system (ANFIS), which is a particular sort of the artificial neural networks (ANN) family, was used to anticipate the wind speed and direction frequency dispersion. Thereafter, the ANFIS system was utilized to gauge wind homestead power creation as function of wind velocity and bearing. Neural system in ANFIS modifies parameters of enrollment capacity in the fuzzy logic of the fuzzy inference system. The reenactment outcomes exhibited in this paper demonstrate the adequacy of the created technique.     

Problems inherent in using aircraft for radio oceanography studies

Some of the disadvantages relating to altitude stability and proximity to the ocean are described for radio oceanography studies using aircraft. The random oscillatory motion introduced by the autopilot in maintaining aircraft altitude requires a more sophisticated range tracker for a radar altimeter than would be required in a satellite application. One-dimensional simulations of the sea surface (long-crested waves) are performed using both the JONSWAP spectrum and the Pierson-Moskowitz spectrum. The results of the simulations indicate that care must be taken in trying to experimentally verify instrument measurement accuracy. Because of the relatively few wavelengths examined from an aircraft due to proximity to the ocean and low velocity compared to a satellite, the random variation in the sea surface parameters being measured can far exceed an instrument's ability to measure them.     

Elimination of directional wave spectrum contamination from noise in elevation measurements

The Surface Contour Radar (SCR) is a 36-GHz computer-controlled airborne radar which generates a false-color-coded elevation map of the sea surface below the aircraft in real time, and can routinely produce ocean directional wave spectra with post-flight data processing which have much higher angular resolution than pitch-and-roll buoys. The SCR range measurements are not error-free and the resulting errors in the elevations corrupt the directional wave spectrum. This paper presents a technique for eliminating that contamination.     

Intermittent heating in a model of solar coronal loops

X-ray and EUV observations of the solar corona reveal a very complex and dynamic environment where there are many examples of structures that are believed to outline the Sun's magnetic field. In this present study, the authors investigate the temporal response of the temperature, density and pressure of a solar coronal plasma contained within a magnetic loop to an intermittent heating source generated by Ohmic dissipation. The energy input is produced by a one-dimensional MHD flare model. This model is able to reproduce some of the statistical properties derived from X-ray flare observations. In particular the heat deposition consists of both a sub-flaring background and much larger, singular dissipative events. Two different heating profiles are investigated: (a) the spatial average of the square of the current along the loop and (b) the maximum of the square of the current along the loop. For case (a), the plasma parameters appear to respond more to the global variations in the heat deposition about its average value rather than to each specific event. For case (b), the plasma quantities are more intermittent in their evolution. In both cases the density response is the least bursty signal. It is found that the time-dependent energy input can maintain the plasma at typical coronal temperatures. Implications of these results upon the latest coronal observations are discussed.     

The Arctic surface energy budget as simulated with the IPCC AR4 AOGCMs

Ensembles of simulations of the twentieth- and twentyfirst-century climate, performed with 20 coupled models for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment, provide the basis for an evaluation of the Arctic (70°–90°N) surface energy budget. While the various observational sources used for validation contain differences among themselves, some model biases and across-model differences emerge. For all energy budget components in the twentieth-century simulations (the 20C3M simulation), the across-model variance and the differences from observational estimates are largest in the marginal ice zone (Barents, Kara, Chukchi Seas). Both downward and upward longwave radiation at the surface are underestimated in winter by many models, and the ensenmble mean annual net surface energy loss by longwave radiation is 35 W/m², which is less than for the NCEP and ERA40 reanalyses but in line with some of the satellite estimates. Incoming solar radiation is overestimated by the models in spring and underestimated in summer and autumn. The ensemble mean annual net surface energy gain by shortwave radiation is 39 W/m², which is slightly less than for the observational based estimates, In the twentyfirst-century simulations driven by the SRES A2 scenario, increased concentrations of greenhouse gasses increase (average for 2080–2100 minus average for 1980–2000 averages) the annual average ensemble mean downward longwave radiation by 30.1 W/m². This was partly counteracted by a 10.7 W/m² reduction in downward shortwave radiation. Enhanced sea ice melt and increased surface temperatures increase the annual surface upward longwave radiation by 27.1 W/m² and reduce the upward shortwave radiation by 13.2 W/m², giving an annual net (shortwave plus longwave) surface radiation increase of 5.8 W/m² , with the maximum changes in summer. The increase in net surface radiation is largely offset by an increased energy loss of 4.4 W/m² by the turbulent fluxes.     

A fine-scale point process model of rainfall with dependent pulse depths within cells

Abstract

A cluster point process model is considered for the analysis of fine-scale rainfall time series. The model is based on three Poisson processes. The first is a Poisson process of storm origins, where each storm has a random (exponential) lifetime. The second is a Poisson process of cell origins that occur during the storm lifetime, terminating when the storm finishes. Each cell has a random lifetime that follows an exponential distribution (or terminates when the storm terminates, whichever occurs first). During cell lifetimes, a third Poisson process of instantaneous pulses occurs. The model is essentially an extension of the well-known Bartlett-Lewis rectangular pulses model, with the rectangular profiles replaced with a Poisson process of instantaneous pulse depths to ensure more realistic rainfall profiles for fine-scale series. Model equations, derived in Cowpertwait et al. (2007 Cowpertwait, P., Isham, V. and Onof, C. 2007. Point process models of rainfall: developments for fine-scale structure. Proceedings of the Royal Society of London, Series A, 463: 2569–2587. [Crossref], [Web of Science ®] , [Google Scholar]), are used to fit different sets of properties to a 60 year record of 5-min data taken from Kelburn, New Zealand. As in the previous work, two superposed processes are used to account for two main and distinct precipitation types (convective and stratiform). By treating the within-cell pulses as dependent random variables, it is found, by simulation, that improved fits to extreme values and the proportion of dry intervals are obtained.

Citation Cowpertwait, P. S. P., Xie, G., Isham, V., Onof, C. & Walsh, D. C. I. (2011) A fine-scale point process model of rainfall with dependent pulse depths within cells. Hydrol. Sci. J. 56(7), 1110–1117.     

Evaluation of LPM permafrost distribution in NE Asia reconstructed and downscaled from GCM simulations

A high‐resolution map of potential frozen ground distribution in NE Asia (90–150°E, 25–60°N) at the period of the Last Permafrost Maximum (LPM, c. 21 000 years ago) was dually reconstructed by means of a statistical classification using air freezing and thawing indices and a topographical downscaling using a digital relief model (ETOPO1). Background LPM climate data were derived from global climate model simulations of the Paleoclimate Model Intercomparison Project, Phase II (PMIP2). The reconstructed LPM map shows the southward shift of the southern limit of climate‐driven permafrost by 400–1500 km, with the greatest advance in the western sector (90–110°E), encompassing an area from central Siberia to most of the Altai area. The advance of environmentally conditional permafrost and seasonally frozen ground was greatest in the eastern sector (110–150°E), with an average shift of about 450 km. The descent of the lower limit of LPM alpine permafrost was in the range of 400–800 m. A comparison of the reconstructed map with published literature shows that this method, simplistically constructed yet effectively recognizing seasonality, continentality and topography, captures local features better than more elaborate methods. The sensitivity examination of a constant atmospheric lapse rate shows that altitudes of 2000–5000 m a.s.l. were most sensitive, though with only a limited effect on overall LPM distribution.     

Susceptibility as a tool for studying magnetic stratigraphy of marine sediments

Eighty six gravity cores collected from the Pacific Ocean by the Scripps Institution of Oceanography have been logged for magnetic susceptibility using a simple and rapid technique. These logs fall into three types: Type 1 showing several highs and lows, Type 2 with a single-broad-hump, and Type 3 showing nearly constant susceptibility with depth. Type 1 cores are found to be mainly from sediment-trap (trenches) areas which are close to the active volcanoes and the high peaks probably correspond to a slump or deposition of volcanic material; these events occurred between 0·1 and 2·8 million years ago. Type 2 cores are by far the most common, (56 out of 86) and show a maximum deposition of magnetic material (i.e. crest region of the hump) in the range of 0·2 and 1·7 million years. The susceptibility during this period was about a factor of two higher for several cores compared to their respective values during the last 0·1 million years. Oceanwide deposition of volcanic material and/or the atmospherically transported dust rich in magnetic material (cosmic and/or terrestrial) by our planet can account for such an increase. A third possibility may be the change (decrease) in accumulation rates of the sediments during this period. In type 3 cores the susceptibility is almost constant with depth and these are randomly distributed (excluding the sediment trap areas) analogous to the case of type 2 cores. A high deposition rate in these areas can alter type 2 into type 3. It appears that the maximum of type 2 hump can act as a stratigraphic marker since type 2 cores are the most common ones and are widely distributed over the entire Pacific.     

GPU-Accelerated Simulation of Massive Spatial Data Based on the Modified Planar Rotator Model

Mathematical Geosciences - A novel Gibbs Markov random field for spatial data on Cartesian grids based on the modified planar rotator (MPR) model of statistical physics has been recently introduced...