Deducing Electron Properties from Hard X-ray Observations

X-radiation from energetic electrons is the prime diagnostic of flare-accelerated electrons. The observed X-ray flux (and polarization state) is fundamentally a convolution of the cross-section for the hard X-ray emission process(es) in question with the electron distribution function, which is in turn a function of energy, direction, spatial location and time. To address the problems of particle propagation and acceleration one needs to infer as much information as possible on this electron distribution function, through a deconvolution of this fundamental relationship. This review presents recent progress toward this goal using spectroscopic, imaging and polarization measurements, primarily from the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI). Previous conclusions regarding the energy, angular (pitch angle) and spatial distributions of energetic electrons in solar flares are critically reviewed. We discuss the role and the observational evidence of several radiation processes: free-free electron-ion, free-free electron-electron, free-bound electron-ion, photoelectric absorption and Compton backscatter (albedo), using both spectroscopic and imaging techniques. This unprecedented quality of data allows for the first time inference of the angular distributions of the X-ray-emitting electrons and improved model-independent inference of electron energy spectra and emission measures of thermal plasma. Moreover, imaging spectroscopy has revealed hitherto unknown details of solar flare morphology and detailed spectroscopy of coronal, footpoint and extended sources in flaring regions. Additional attempts to measure hard X-ray polarization were not sufficient to put constraints on the degree of anisotropy of electrons, but point to the importance of obtaining good quality polarization data in the future.     

Comparison of satellite orbit ephemerides for use in GPS meteorology

This paper discusses GPS (Global Position System) meteorology. The research presented is based on a comparison of values of precipitable water vapour PWV, based on GPS measurements using final and predicted ephemerides of satellite orbits. We analysed recent year’s improvement in predicting ephemerides. We compared the data outputs from a radiosonde using GPS receiver measurements directly from the meteorological station from which the radiosondes were launched. The results indicate a high quality of the predicted ephemerides. This finding makes predicted ephemerides highly usable for near real-time estimations of PWV. To use PWV in meteorological forecast applications, this high speed of PWV values supply is necessary.     

Microflares and the Statistics of X-ray Flares

This review surveys the statistics of solar X-ray flares, emphasising the new views that RHESSI has given us of the weaker events (the microflares). The new data reveal that these microflares strongly resemble more energetic events in most respects; they occur solely within active regions and exhibit high-temperature/nonthermal emissions in approximately the same proportion as major events. We discuss the distributions of flare parameters (e.g., peak flux) and how these parameters correlate, for instance via the Neupert effect. We also highlight the systematic biases involved in intercomparing data representing many decades of event magnitude. The intermittency of the flare/microflare occurrence, both in space and in time, argues that these discrete events do not explain general coronal heating, either in active regions or in the quiet Sun.     

Signatures of the Sudden Stratospheric Warming events of January–February 2008 in Seoul,S. Korea

The period January–February 2008 was characterized by four Sudden Stratospheric Warmings (SSWs) in the Northern Hemisphere, of which the last warming, at the end of February 2008, was a major warming. A significant decrease in mesospheric water vapour (H₂O) of more than 2 ppmv (∼40%) was observed by the ground-based microwave (GBMW) radiometer in Seoul, S. Korea [37.3°N, 126.3°E] during the major SSW. A comparison with ground-based mesospheric H₂O observations from the mid-latitude station in Bern [46.9°N, 7°E] revealed an anticorrelation in the mesospheric H₂O data during the major SSW. In addition, prior to the major warming, strong periodic fluctuations were recorded in the Aura MLS vertical temperature distribution between 15 and 0.05 hPa at Seoul. The mesospheric temperature oscillation was found to have a period of ∼10–14 days with a persistency of 3–4 cycles.     

电子设备机壳电磁屏蔽技术研究

文章阐述了谱域分析方法计算屏蔽效能的原理，针对电子设备机壳上的周期结构矩形孔阵，应用谱域法对其屏蔽性能进行了分析和计算。在此基础上利用谱域法和FDTD法对矩形孔周期结构导电板进行了比对分析和计算，并用试验方法进行了测试，计算结果与FDTD法计算结果基本一致，也与测试结果比较吻合。     

Relationships between soil properties of the abandoned fields and spectral data derived from the advanced spaceborne thermal emission and reflection radiometer (ASTER)

The structural transformation of Polish agriculture after 1989 has been leading to significant changes in land use. As a result a large part of formerly ploughed fields lies abandoned and they occur across considerable variability in soil typological units. Accurate information about soil conditions within the abandoned fields facilitates proper management in the new socio-economic situation. Such information can be collected using satellite images since the structure and condition of the vegetation growing on the abandoned fields reflects soil properties. The objective of this study is to evaluate the relationships between physical and chemical attributes of soil within the abandoned fields and spectral reflectance patterns recorded by ASTER sensors onboard Terra Satellite. Soil samples were collected at five abandoned fields which have not been ploughed since 2000 and analyzed in the laboratory to determine their physical and chemical properties. Nine ASTER nearly cloud-free pictures were used for this study in order to derive the remote-sensing attributes of the abandoned fields. In order to evaluate the relationships between soil fertility and remotely sensed data, partial least-squares (PLS) and a multiple linear regression (MLR) analysis between these two datasets were carried out. In the regression analysis, only soil TEB (total exchangeable bases) stock in the whole profile displayed the highest correlation with remotely sensed data acquired in April and May and the best predictors were NDVI and LSWI vegetation indices.