Fourteen years (September 2002 to August 2016) of high-resolution satellite observations of sea surface temperature (SST) data are used to describe the frontal pattern and frontogenesis on the southeastern continental shelf of Brazil. The daily SST fronts are obtained using an edge-detection algorithm, and the monthly frontal probability (FP) is subsequently calculated. High SST FPs are mainly distributed along the coast and decrease with distance from the coastline. The results from empirical orthogonal function (EOF) decompositions reveal strong seasonal variability of the coastal SST FP with maximum (minimum) in the astral summer (winter). Wind plays an important role in driving the frontal activities, and high FPs are accompanied by strong alongshore wind stress and wind stress curl. This is particularly true during the summer, when the total transport induced by the alongshore component of upwelling-favorable winds and the wind stress curl reaches the annual maximum. The fronts are influenced by multiple factors other than wind forcing, such as the orientation of the coastline, the seafloor topography, and the meandering of the Brazil Current. As a result, there is a slight difference between the seasonality of the SST fronts and the wind, and their relationship was varying with spatial locations. The impact of the air-sea interaction is further investigated in the frontal zone, and large coupling coefficients are found between the crosswind (downwind) SST gradients and the wind stress curl (divergence). The analysis of the SST fronts and wind leads to a better understanding of the dynamics and frontogenesis off the southeastern continental shelf of Brazil, and the results can be used to further understand the air-sea coupling process at regional level.
Active seismic sources are critical for obtaining high resolution images of the subsurface. For active imaging in urban areas, environment friendly and green seismic sources are required. In present work, we introduce a new type of green active source based on the gaseous detonation of methane and oxygen. When fired in a closed container, the chemical reaction, i.e. gaseous detonation, will produce high pressure air over 150MPa. Seismic waves are produced when high pressure air is quickly released to impact the surroundings. The first field experiment of this active source was carried out in December, 2017 in Jingdezhen, Jiangxi Province, where a series of active sources were excited to explore their potential in mine exploration. In current work, we analyzed the seismic waves recorded by near-field accelerators and a dense short-period seismic array and compared them with those from a mobile airgun source, another kind of active source by releasing high pressure air into water. The results demonstrate that it can be used for high resolution near surface imaging. Firstly, the gaseous detonation productions are harmless CO2 and water, making it a green explosive source. Secondly, the dominant seismic frequencies are 10-80Hz and a single shot can be recorded up to 15km, making it suitable for local structure investigations. Thirdly, it can be excited in vertical wells, similar to traditional powder explosive sources. It can also act as an additional on-land active source to airgun sources, which requires a suitable water body as intermediate media to generate repeating signals. Moreover, the short duration and high frequency signature of the source signals make it safe with no damage to nearby buildings. These make it convenient to excite in urban areas. As a new explosive source, the excitation equipment and conditions, such as gas ratio, sink depth and air-releasing directions, need further investigation to improve seismic wave generation efficiency. 相似文献
Many synthetic model studies suggested that the best way to obtain good 3D interpretation results is to distribute the MT sites at a 2D grid array with regular site spacing over the target area. However, MT 3D inversion was very difficult about 10 years ago. A lot of MT data were collected along one profile and then interpreted with 2D inversion. How to apply the state-of-the-art 3D inversion technique to interpret the accumulated mass MT profiles data is an important topic. Some studies on 3D inversion of measured MT profile data suggested that 2D inversions usually had higher resolution for the subsurface than 3D inversions. Meanwhile, they often made their interpretation based on 2D inversion results, and 3D inversion results were only used to evaluate whether the overall resistivity structures were correct. Some researchers thought that 3D inversions could not resolute the local structure well, while 2D inversion results could agree with the surface geologic features much well and interpret the geologic structures easily. But in the present paper, we find that the result of 3D inversion is better than that of 2D inversion in identifying the location of the two local faults, the Shade Fault(SDF)and the Yunongxi Fault(YNXF), and the deep structures.
In this paper, we first studied the electrical structure of SDF and YNXF based on a measured magnetotelluric(MT) profile data. Besides, from the point of identifying active faults, we compared the capacity of identifying deep existing faults between 2D inversion models and 3D models with different inversion parameters. The results show that both 2D and 3D inversion of the single-profile data could obtain reasonable and reliable electrical structures on a regional scale. Combining 2D and 3D models, and according to our present data, we find that both SDF and YNXF probably have cut completely the high resistivity layer in the upper crust and extended to the high conductivity layer in the middle crust. In terms of the deep geometry of the faults, at the profile's location, the SDF dips nearly vertically or dips southeast with high dip angle, and the YNXF dips southeast at depth. In addition, according to the results from our measured MT profile, we find that the 3D inversion of single-profile MT data has the capacity of identifying the location and deep geometry of local faults under present computing ability. Finally, this research suggests that appropriate cell size and reasonable smoothing parameters are important factors for the 3D inversion of single-profile MT data, more specifically, too coarse meshes or too large smoothing parameters on horizontal direction of 3D inversion may result in low resolution of 3D inversions that cannot identify the structure of faults. While, for vertical mesh size and data error thresholds, they have limited effect on identifying shallow tectonics as long as their changes are within a reasonable range. 3D inversion results also indicate that, to some extent, adding tippers to the 3D inversion of a MT profile can improve the model's constraint on the deep geometry of the outcropped faults. 相似文献