基于随机集合的非传统型有效波极值模型

The analysis and design of offshore structures necessitates the consideration of wave loads. Realistic modeling of wave loads is particularly important to ensure reliable performance of these structures. Among the available methods for the modeling of the extreme significant wave height on a statistical basis, the peak over threshold method has attracted most attention. This method employs Poisson process to character- ize time-varying properties in the parameters of an extreme value distribution. In this paper, the peak over threshold method is reviewed and extended to account for subjectivity in the modeling. The freedom in selecting the threshold and the time span to separate extremes from the original time series data is incorpo- rated as imprecision in the model. This leads to an extension from random variables to random sets in the probabilistic model for the extreme significant wave height. The extended model is also applied to different periods of the sampled data to evaluate the significance of the climatic conditions on the uncertainties of the parameters.     

The distribution of chlorophyll a and its influencing factors in different regions of the Bering Sea

The distribution of chlorophyll a(Chl a) and its relationships with physical and chemical parameters in different regions of the Bering Sea were discussed in July 2010. The results showed the seawater column Chl a concentrations were 13.41–553.89 mg/m2 and the average value was 118.15 mg/m2 in the study areas. The horizontal distribution of Chl a varied remarkably from basin to shelf in the Bering Sea. The regional order of Chl a concentrations from low to high was basin, slope, outer shelf, inner shelf, and middle shelf. The vertical distribution of Chl a was grouped mainly from single-peak type in basin, slope, outer shelf, and middle shelf, where the deep Chl a maxima(DCM) layer was observed at 25–50 m, 30–35 m, 36–44 m, and 37–47 m, respectively. The vertical distribution of Chl a mainly had three basic patterns: standard single-peak type, surface maximum type, and bottom maximum type in the inner shelf. The analysis also showed that the transportation of ocean currents may control the distribution of Chl a, and the effects were not simple in the basin of the Bering Sea. There was a positive correlation between Chl a and temperature, but no significant correlation between Chl a and nutrients. The Bering Sea slope was an area deeply influenced by slope current. Silicate was the factor that controlled the distribution of Chl a within parts of the water in the slope. Light intensity was an important environmental factor in controlling seawater column Chl a in the shelf, where Chl a was limited by nitrate rather than phosphate within the upper water. Meanwhile, there was a positive relationship between Chl a and salinity. Algal blooms broke out at Sta. B6 of the southwestern St. Lawrence Island and Stas F6 and F11 in the middle of the Bering Strait.     

Species distribution modelling to support marine conservation planning: The next steps

Species distribution models (SDMs) offer great potential for inclusion into the toolbox of today's marine environmental manager, especially with regard to marine conservation and planning. The application of SDMs in the marine environment over recent years has been varied but there are still relatively few examples in comparison with terrestrial application, and this is especially true in deep-sea marine ecosystems. This short article builds upon two recent review articles concerning the application of species distribution modelling studies in the marine realm, offering additional practical considerations for discussion. Recommendations for progressing the improved application of SDMs to support marine conservation planning are given, including combining model outputs with other data layers, metadata standards and model error. SDMs have both an urgent and long term contribution to make to marine conservation planning globally, and it is hoped that this article, in combination with developing research on marine SDMs, will contribute to some much needed discussion and inform best practice and new research to enable these models to be of greater use to marine managers.     

北太平洋中尺度涡时空特征分析

利用1993~2011年19 a的AVISO卫星高度计资料研究了北太平洋(10°~60°N,120°E~100°W)中尺度涡的时空分布特征,结果表明:北太平洋每年约产生1 800余个涡旋,其中气旋涡稍多。北太平洋东部沿岸、西北沿岸、黑潮延伸体北侧、副热带逆流区是中尺度涡的高发区,春、冬季是涡旋的高发季节。涡极性分布以35°N为界,北部多反气旋涡,南部多气旋涡。涡旋半径以100 km左右为主,并且基本随纬度升高而减小,涡旋数量随着周期增长而急剧下降。反气旋涡的平均半径和周期均大于气旋涡。利用Argo浮标剖面资料分析的6个个例涡旋的垂直结构显示,每个涡旋都有其独特的冷暖核结构,深度不同。研究结果对于分析北太平洋涡动能分布及传输具有一定的参考价值。     

广西北仑河口红树林保护区表层海水溶解态重金属时空分布及其影响因素

根据2013年5月(春季)和8月(夏季)对广西北仑河口红树林保护区的现场调查监测数据,研究了表层海水中溶解态重金属Cu、Zn、Pb、Cd、Cr、As、Hg的时空分布特征,探讨了其影响因素,并对其污染水平进行了评价。结果表明,表层海水各溶解态重金属的浓度、空间波动程度在春、夏季均存在一定的差异;Hg的污染明显超过国家一类海水水质标准,且夏季污染水平高于春季。Cu-Zn、Cu-Cd、Zn-Pb、Zn-Cd之间存在显著正相关,春、夏季As以及夏季Cr分别与盐度之间呈显著正相关,其他重金属与盐度之间无显著相关性。各重金属的时空分布主要受到陆源输入、沿岸江河冲淡水和海水盐度变化等因素的影响。     

基于高性能计算平台的天宫一号遥感数据地面预处理系统

针对天宫一号传感器特点,设计并实现了基于高性能并行集群环境的遥感数据地面预处理系统,可完成对高并发、海量遥感数据处理任务的快速、高效处理.该系统可通过传感器的星上定标参数完成系统辐射校正、系统几何校正等处理过程,生产出高光谱热红外谱段和高光谱数据的1级、2级遥感产品.同时,在数据产品封装与输出分系统中,采用了较为通用的GeoTiff与HDF作为产品的主要输出格式,可满足领域内多种用户的需求.     

基于改进的Kriging法区域似大地水准面精化分析

区域似大地水准面精化研究主要是用于测绘学科,将精化结果应用到绘制地形图中,减少户外工作量,降低人力成本。传统采用的Kriging法在精化时会出现误差,精度值不达标。所以,改用了一种基于已知的拟合残差进行计算的改进方法重新精化研究。将改进的Kriging法与传统的Kriging法对比后,改进后的方法精化结果的拟合精度明显要高于传统方法。     

基于ICESat-2 ATLAS数据的DEM高程精度评价

为探究ASTER GDEMV3、SRTM1 DEM和AW3D30 DEM 3种开源DEM数据的高程精度,本文以高精度ICESat-2 ATLAS测高数据为参考数据,利用GIS统计分析、误差相关分析及数理统计对DEM的高程精度进行对比评价。结果表明：①AW3D30的质量最稳定;SRTM1 DEM在平原精度最高;在高原山地精度由高到低依次为AW3D30 DEM、ASTER GDEMV3、SRTM1 DEM。②DEM数据高程精度受地表覆盖影响较大,且与地形因素密切相关,在相同地表覆盖的两个研究区中DEM数据高程精度表现情况不一致,SRTM在平原地表覆盖下精度表现最好,平均误差为3.15 m,AW3D30 DEM在山地地表覆盖下精度表现最好,平均误差为7.61 m。③坡度对DEM数据的高程精度影响较大,在两个研究区3种DEM数据的高程误差均随坡度的增加而增加;坡向对DEM数据的高程精度影响较小,未发现明显的规律。     

西安市浅层地温场垂向分布特征及其影响因素分析

根据西安市内布设的12口长观孔监测的一年内的月平均地温,绘制不同时期地温随深度变化曲线,系统分析西安市浅层地温场垂向上的分布特征及其影响因素。分析得出：西安市垂向上的分布特征有两种类型：渐变升温型和升温降温交替型。影响其分布的主要因素是地质构造、地下水活动以及岩性。在开发利用过程中要针对浅层地温场不同的变化类型因地制宜地进行调查评价工作,合理开发西安市浅层地温能。     

甘肃清水县地质灾害类型、形成条件及发育规律分析

清水县是甘肃省地质灾害较为严重的地区之一。本文根据清水县地质灾害调查与区划项目野外调查成果资料,在概述县域自然地理条件及地质背景的基础上,全面阐述了全县已有的地质灾害类型及特征,从地形地貌、岩土体类型与结构、地质构造、大气降水、人类工程活动5个方面深入分析了地质灾害的形成条件,并探讨了地质灾害的分布发育规律,以期为区域地质灾害防治提供科学依据。