Using the seismic waveform data recorded by regional seismic network of Yunnan and Sichuan and the method of CAP, we calculate and obtain the focal mechanism of 268 earthquakes with the magnitude of ML≥4.0 occurring in Yunnan during Jan. 1999 to Aug. 2014; then, we analyze the types and the regional feature of the focal mechanism of earthquakes in Yunnan, on the basis of the focal mechanism of 109 earthquakes analyzed by Harvard University. Based on the data of the above focal mechanism solutions, we adopt the method of damped regional-scale stress inversion to calculate the best-fitting tectonic stress tensor of every grid in Yunnan; and adopt the method of maximum principal stress to calculate the direction of maximum horizontal principal stress in Yunnan. The result shows that: (1)the strike-slip type is the most principal type of the earthquake focus in the study area and the second is the normal faulting type; while, the reverse-fault type is relatively small. The spatial distribution of focal mechanism is obvious. This reflects that the dynamic source and acting force are different in different parts of the study area. (2)The direction of the stress field in Yunnan shows a certain spatial continuity. Maximum horizontal principal compressive stress is mainly clockwise from north to south and counterclockwise from the west to the east. The direction of stress field shows inhomogeneity in space. There exist two stress conversion zones respectively in EW and NS direction. The inversion result of stress field shows that the stress field in Yunnan is complex and the principal stress direction changes greatly; and there are obvious differences in different regions. 相似文献
In this paper, according to the results of the satellite imagery interpretation and field investigation, we study the active features and the latest active times of the Chuxiong-Nanhua fault, the Quaternary basins formation mechanism, and the relationship between the fault and the 1680 Chuxiong MS6 ¾ earthquake. Several Quaternary profiles at Lvhe, Nanhua reveal that the fault has offset the late Pleistocene deposits of the T2 and T3 terraces of Longchuan river, indicating that the fault was obviously active in late Quaternary. The Chuxiong-Nanhua fault has been dominated by dextral strike slip motion in the late Quaternary, with an average rate of 1.6-2.0mm/a. Several pull apart Quaternary basins of Chuxiong, Nanhua, and Ziwu etc. have developed along the fault. The 1680 Chuxiong MS6 ¾ earthquake and several moderate earthquakes have occurred near the fault. The Chuxiong-Nanhua fault are the seismogenic structure of those earthquakes, the latest fault movement was in the late-Pleistocene, and even the Holocene. In large area, the Chuxiong-Nanhua fault and the eastern Qujiang fault and the Shiping fault composed a set of NW-trending oblique orientation active faults, and the motion characteristics are all mainly dextral strike slip. The motion characteristics, like the red river fault of the Sichuan-Yunnan Rhombic Block southwestern boundary, are concerned with the escaping movement of the Sichuan-Yunnan Rhombic Block. 相似文献
Satellite records show that the extent and thickness of sea ice in the Arctic Ocean have significantly decreased since the early 1970s. The prediction of sea ice is highly important, but accurate simulation of sea ice variations remains highly challenging. For improving model performance, sensitivity experiments were conducted using the coupled ocean and sea ice model (NEMO-LIM), and the simulation results were compared against satellite observations. Moreover, the contribution ratios of dynamic and thermodynamic processes to sea ice variations were analyzed. The results show that the performance of the model in reconstructing the spatial distribution of Arctic sea ice is highly sensitive to ice strength decay constant (Crhg). By reducing the Crhg constant, the sea ice compressive strength increases, leading to improved simulated sea ice states. The contribution of thermodynamic processes to sea ice melting was reduced due to less deformation and fracture of sea ice with increased compressive strength. Meanwhile, dynamic processes constrained more sea ice to the central Arctic Ocean and contributed to the increases in ice concentration, reducing the simulation bias in the central Arctic Ocean in summer. The root mean square error (RMSE) between modeled and the CryoSat-2/SMOS satellite observed ice thickness was reduced in the compressive strength-enhanced model solution. The ice thickness, especially of multiyear thick ice, was also reduced and matched with the satellite observation better in the freezing season. These provide an essential foundation on exploring the response of the marine ecosystem and biogeochemical cycling to sea ice changes.
