Evolution of the sun''s near-surface asphericities over the activity cycle

Solar oscillations provide the most accurate measures of cycle dependent changes in the sun, and the Solar and Heliospheric Observatory/Michelson Doppler Imager (MDI) data are the most precise of all. They give us the opportunity to address the real challenge — connecting the MDI seismic measures to observed characteristics of the dynamic sun. From inversions of the evolving MDI data, one expects to determine the nature of the evolution, through the solar cycle, of the layers just beneath the sun's surface. Such inversions require one to guess the form of the causal perturbation — usually beginning with asking whether it is thermal or magnetic. Matters here are complicated because the inversion kernels for these two are quite similar, which means that we don't have much chance of disentangling them by inversion. However, since the perturbation lies very close to the solar surface, one can use synoptic data as an outer boundary condition to fix the choice. It turns out that magnetic and thermal synoptic signals are also quite similar. Thus, the most precise measure of the surface is required.

We argue that the most precise synoptic data come from the Big Bear Solar Observatory (BBSO) Solar Disk Photometer (SDP). A preliminary analysis of these data implies a magnetic origin of the cycle-dependent sub-surface perturbation. However, we still need to do a more careful removal of the facular signal to determine the true thermal signal.     

Continuous tracking of cmes using MICA, andLASCO C2 and C3 coronagraphs

In this work we have tracked coronal mass ejections observed with the ground based Mirror Coronagraph for Argentina (MICA) and the Large Angle and Spectroscopic Coronagraph (LASCO) C2 and C3 on board of the Solar and Heliospheric Observatory (SOHO). The MICA telescope is located at El Leoncito (31.8 S, 69.3 W), San Juan (Argentina), since 1997 as part of a bilateral scientific project between Germany and Argentina. SOHO is a project of international cooperation between ESA and NASA. Together these instruments are able to observe the solar corona ranging from 1.05 to 32 solar radii. MICA images the Fe XIV emission line corona and LASCO coronagraphs observe the Thomson scattered white light corona. We have selected events for which there are observations from the three coronagraphs. Using the composite data we were able to obtain height-time diagrams for the corresponding dynamical coronal features traveling outwards in order to determine some of their kinematical properties, i.e., plane of sky velocity and acceleration.     

工件表面轮廓均方根斜率的光散射测量

描述并确定具有明显纹理粗糙表面均方根斜率的光散射技术(均方根斜率是联合表面轮廓高度和波长特性的混合参数)。称为散射光锥法(The scattered light-conemethod)的该技术是基于激光角散射检测阵列(DALLAS——Defector Array for Laser LishtAngular Scattering),它用于测量粗糙表面散射光角分布的仪器。均方根斜率是从DALLAS光散射图象的角宽得到的。一般可以发现角宽(即估计的均方根斜率)对光的入射角和散射角变化相当大时是不敏感的。这些结果与表面材料无关,并且对正弦和随机粗糙表面都是有效的。介绍了散射光锥法的测量原理、实验、数据分析和几点结论。     

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.     

Aerosols and clouds in the upper troposphere–lower stratosphere region detected by GOMOS and ACE: Intercomparison and analysis of the years 2004 and 2005

Satellite-based limb occultation measurements are well suited for the detection and mapping of polar stratospheric clouds (PSCs) and cirrus clouds. PSCs are of fundamental importance for the formation of the Antarctic ozone hole that occurs every year since the early 1980s in Southern Hemisphere spring. Despite progress in the observation, modeling and understanding of PSCs in recent years, there are still important questions which remain to be resolved, e.g. PSC microphysics, composition, formation mechanisms and long-term changes in occurrence. In addition, it has recently become clear that cirrus clouds significantly affect the global energy balance and climate, due to their influence on atmospheric thermal structure.     

Development of a gas chromatography compatible Sample Processing System (SPS) for the in-situ analysis of refractory organic matter in martian soil: preliminary results

In the frame of the 2009 Mars Science Laboratory (MSL) mission a new sample preparation system (SPS) compatible with gas chromatography–mass spectrometry (GC–MS) has been developed for the in situ analysis of complex organic molecules in the Martian soil. The goal is to detect, if they exist, some of the key compounds that play an important role in life on Earth including carboxylic acids, amino acids and nucleobases.     

Time-dependent cosmic ray modulation

Time-dependent cosmic ray modulation is calculated over multiple solar cycles using our well established two-dimensional time-dependent modulation model. Results are compared to Voyager 1, Ulysses and IMP cosmic ray observations to establish compatibility. A time-dependence in the diffusion and drift coefficients, implicitly contained in recent expressions derived by , ,  and , is incorporated into the cosmic ray modulation model. This results in calculations which are compatible with spacecraft observations on a global scale over consecutive solar cycles. This approach compares well to the successful compound approach of Ferreira and Potgieter (2004). For both these approaches the magnetic field magnitude, variance of the field and current sheet tilt angle values observed at Earth are transported time-dependently into the outer heliosphere. However, when results are compared to observations for extreme solar maximum, the computed step-like modulation is not as pronounced as observed. This indicates that some additional merging of these structures into more pronounced modulation barriers along the way is needed.     

Improved rainfall estimation over the Indian region using satellite infrared technique

The GOES Precipitation Index (GPI) technique (Arkin, 1979) for rainfall estimation has been in operation for the last three decades. However, its applications are limited to the larger temporal and spatial scales. The present study focuses on the augmentation on GPI technique by incorporating a moisture factor for the environmental correction developed by Vicente et al. (1998). It consists of two steps; in the first step the GPI technique is applied to the Kalpana-IR data for rainfall estimation over the Indian land and oceanic region and in the second step an environmental moisture correction factor is applied to the GPI-based rainfall to estimate the final rainfall. Detailed validation with rain gauges and comparison with Tropical Rainfall Measuring Mission (TRMM) merged data product (3B42) are performed and it is found that the present technique is able to estimate the rainfall with better accuracy than the GPI technique over higher temporal and spatial domains for many operational applications in and around the Indian regions using Indian geostationary satellite data. Further comparison with the Doppler Weather Radar shows that the present technique is able to retrieve the rainfall with reasonably good accuracy.