Investigating Earth’s Atmospheric Electricity: a Role Model for Planetary Studies

The historical development of terrestrial atmospheric electricity is described, from its beginnings with the first observations of the potential gradient to the global electric circuit model proposed by C.T.R. Wilson in the early 20th century. The properties of the terrestrial global circuit are summarised. Concepts originally needed to develop the idea of a global circuit are identified as “central tenets”, for example, the importance of radio science in establishing the conducting upper layer. The central tenets are distinguished from additional findings that merely corroborate, or are explained by, the global circuit model. Using this analysis it is possible to specify which observations are preferable for detecting global circuits in extraterrestrial atmospheres. Schumann resonances, the extremely low frequency signals generated by excitation of the surface-ionosphere cavity by electrical discharges, are identified as the most useful single measurement of electrical activity in a planetary atmosphere.     

Comet Knudsen Layers

This paper reviews some important results about Knudsen layers obtained in theoretical gas kinetics research in the last few decades, focusing on the weak and strong evaporation problems in two-surface, half-space, and spherical geometries. Furthermore, the application of such results in cometary science is reviewed. In order to illustrate some properties of the half-space evaporation problem for water ice surfaces at temperatures relevant for active comets, a number of numerical Direct Simulation Monte Carlo calculations are presented.     

DEMETER Observations of EM Emissions Related to Thunderstorms

The paper is related to specific emissions at frequency <3 MHz observed by the low altitude satellite DEMETER in relation with the thunderstorm activity. At its altitude (～700 km), the phenomena observed on the E-field and B-field spectrograms recorded by the satellite are mainly dominated by whistlers. Particular observations performed by DEMETER are reported. It concerns multiple hop whistlers and interaction between whistlers and lower hybrid noise. Two new phenomena discovered by the satellite are discussed. First, V-shaped emissions up to 20 kHz are observed at mid-latitude during night time. They are centered at the locations of intense thunderstorm activity. By comparison with VLF saucers previously observed by other satellites in the auroral zones it is hypothesized that the source region is located below the satellite and that the triggering mechanism is due to energetic electrons accelerated during sprite events. Second, emissions at frequency ～2 MHz are observed at the time of intense whistlers. These emissions are produced in the lower ionosphere in probable relation with Transient Luminous Events (TLEs).     

On the electrodynamics of counter stream in pulsar’s inner annular cap region

The electric properties of pulsar’s inner annular gap are explored in this paper. Under two main assumptions, (1) the pulsar is alive, (2) the total charge of pulsar should not vary with time, the condition for the acceleration of negative particle in the annular region is derived. The acceleration condition is j₋ ? 0.5j₊, i.e., the current carried by negative particles is greater than or equal to 0.5 times of the current carried by positive particles. This condition holds even when the backward flow of positive particles exists in the annular region. It is noted that the outflow of negative particles offers good opportunities to understand the current closure problem of pulsar as well as wide radiation beam of pulsar observed at high energy band.     

Electromagnetic waves observed by Venus Express at periapsis: Detection and analysis techniques

The magnetometer on Venus Express was designed to be able to obtain 128 Hz samples of the magnetic field from two sensors in a gradiometer configuration. This mode is used around periapsis to determine whether the signals reported at low altitudes near 100 Hz, had the properties of electromagnetic waves generated by electric discharges in the Venus atmosphere. The lack of a magnetic cleanliness program and the shortness of the magnetometer boom make this a challenging measurement. Fortunately the signals are sufficiently strong that they can be easily resolved with rather straightforward analysis techniques.     

An Artificial Neural Network based approach for estimation of rain intensity from spectral moments of a Doppler Weather Radar

By using a Doppler Weather Radar (DWR) at Shriharikota (13.66°N & 80.23°E), an Artificial Neural Network (ANN) based technique is proposed to improve the accuracy of rain intensity estimation. Three spectral moments of a Doppler spectra are utilized as an input data to an ANN. Rain intensity, as measured by the tipping bucket rain gauges around the DWR station, are considered as a target values for the given inputs. Rain intensity as estimated by the developed ANN model is validated by the rain gauges measurements. With the help of a developed technique, reasonable improvement in the estimation of rain intensity is observed. By using the developed technique, root mean square error and bias are reduced in the range of 34–18% and 17–3% respectively, compared to Z–R approach.     

The plasma mantle: Composition and other characteristics observed by means of the PROGNOZ-7 satellite

A brief summary of the main results of magnetospheric ion composition measurements in general is first presented. PROGNOZ-7 measurements in the nightside plasma mantle are then described and analyzed. Some of the results are the following: In the nightside mantle not too far from midnight the properties of the mantle are sometimes consistent with the open magnetosphere model. However during most magnetic storm situations O⁺ ions appear in the mantle in large proportions and with high energies. The acceleration process affecting the ions has been found in several cases to give equal amounts of energy to all ions independent of mass. Along the flanks of the magnetosphere the flow of the plasma is often low or absent. The O⁺ content is high (up to 20%) and the energy spectrum of both ions and electrons may be very hot, even up to the level of the ring current plasma in the keV range.The O⁺ content in the plasma mantle is positively correlated with the magnetospheric activity level. The mantle, however, does not appear to be the dominating source for the storm time ring current. Direct acceleration of ionospheric ions onto the closed field lines of the plasma sheet and ring current is most likely the main source. The magnetopause on the nightside and along the flanks of the magnetosphere appears to be a fairly solid boundary for mantle ions of ionospheric origin. This is especially evident during periods with high geomagnetic activity, when the mantle is associated with fairly strong fluxes of O⁺ ions.An interesting observation in most of the mantle passages during geomagnetically disturbed periods is the occurrence of intense, magnetosheath like, regions deep inside the mantle. In some cases these regions with strong antisunward flow and with predominant magnetosheath ion composition was observed in the innermost part of the mantle, i.e. marking a boundary region between the lobe and the mantle. These magnetosheath penetration events are usually associated with strong fluxes of accelerated ionospheric ions in nearby parts of the mantle. Evanescent penetration regions with much reduced flow properties are frequently observed in the flank mantle.     

Application of SVM on satellite images to detect hotspots in Jharia coal field region of India

The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots. This type of work will be quite helpful in the near future to develop a hotspots monitoring system using these operational satellites data.     

Solar flare forecasting model supported with artificial neural network techniques

Nowadays operational models for solar activity forecasting are still based on the statistical relationship between solar activity and solar magnetic field evolution. In order to set up this relationship, many parameters have been proposed to be the measures. Conventional measures are based on the sunspot group classification which provides limited information from sunspots. For this reason, new measures based on solar magnetic field observations are proposed and a solar flare forecasting model supported with an artificial neural network is introduced. This model is equivalent to a person with a long period of solar flare forecasting experience.     

Tidal associated temperature disturbances observed at the middle atmosphere (30–65 km) by a Rayleigh lidar at 23°S

A lidar has been operated in São José dos Campos, Brazil (23.2°S, 45.8°W) since 1972, mainly dedicated to the study of mesospheric sodium at the 589 nm resonant line. The molecular Rayleigh scattering can also be used provided we limit the height to ∼75 km where the sodium scattering begins. Nevertheless, the weak signal obtained only permits the determination of density and temperature profiles by accumulating a large number of shots giving only nocturnal average profiles. Temporal variations in density and temperature on the scale of hours can however, be obtained by performing a superposed epoch analysis for a given time interval and covering a period of several days. In this way we obtained hourly mean profiles grouped by months, seasons and overall, with data acquired from 1993 to 2004. The difference between the hourly temperatures and the nocturnal means shows for some months, with enough data coverage, downward propagating structures that apparently have tidal origin. The seasonal averages show a recurrent feature with high temperatures before and low temperatures after midnight above 50 km. Some similarity is found with the GSWM model, but the observed temperature amplitudes are twice of that for the model.