摘要：This paper analyzes the seismicity in Bohai Sea,introducing a shape factor K to characterize the seismic risk distribution in sub-regions of the sea. Based on the seismic design ground motions for 46 platforms located in the Bohai Sea,a statistical analysis was performed for different peak ground acceleration (PGA) ratios at two different probability levels. In accordance with the two-stage design method,a scheme of two seismic design levels is proposed,and two seismic design objectives are established respectively for the strength level earthquake and the ductility level earthquake. By analogy with and comparison to the Chinese seismic design code for buildings,it is proposed that the probability level for the strength level earthquake and ductility level earthquake have a return period of 200 and 1000 - 2500 years,respectively. The validity of these proposed values is discussed. Finally,the PGAs corresponding to these two probability levels are calculated for different sub-regions of the Bohai Sea.

摘要：The maximum entropy distribution, which consists of various recognized theoretical distributions, is a better curve to estimate the design thickness of sea ice. Method of moment and empirical curve fitting method are common-used parameter estimation methods for maximum entropy distribution. In this study, we propose to use the particle swarm optimization method as a new parameter estimation method for the maximum entropy distribution, which has the advantage to avoid deviation introduced by simplifications made in other methods. We conducted a case study to fit the hindcasted thickness of the sea ice in the Liaodong Bay of Bohai Sea using these three parameter-estimation methods for the maximum entropy distribution. All methods implemented in this study pass the K-S tests at 0.05 significant level. In terms of the average sum of deviation squares, the empirical curve fitting method provides the best fit for the original data, while the method of moment provides the worst. Among all three methods, the particle swarm optimization method predicts the largest thickness of the sea ice for a same return period. As a result, we recommend using the particle swarm optimization method for the maximum entropy distribution for offshore structures mainly influenced by the sea ice in winter, but using the empirical curve fitting method to reduce the cost in the design of temporary and economic buildings.

摘要：Evaluation and projection of temperature extremes over China are carried out with 8 model datasets from CMIF5. Compared with the NCEP reanalysis data, multi-model weighted ensemble is capable of reproducing the 8 temperature extreme indices and 20-yeax return values of annual maximum/minimum temperatures. The time correlation coefficients of all the 8 indices between multi-model ensemble and the reanalysis can reach a significance level of 0.10. The spatial correlation coefficient of 20-year return level of annual maximum/minimum temperatures is greater than 0.98. Under the RCP4.5 scenario, more extreme warm events and less cold events are expected over China in multi-model ensemble. By the middle of the 21st century, the heat wave duration index will be multiplied 2.6 times. At the end of the 21st century, the cold wave duration index will decrease 71%, and the 20-year return value will increase 4℃ in parts of China for the maximum/minimum temperatures.