广东省突发性地质灾害气象预警实践

本文基于十年来的地质灾害气象预警工作实践,统计分析了广东省历年来降雨及突发性地质灾害的特点,揭示了广东省突发性地质灾害在不同降雨量、降雨强度及降雨类型下的成灾规律;并在总结地质灾害气象预警工作实践成果的基础上,分析存在问题,提出进一步完善地质灾害预警的技术与方法,为地质灾害气象预警精细化和实时临灾预警提供科学依据。     

古龙油田油-水同层油藏形成主控因素与分布规律

松辽盆地北部中央坳陷的古龙油田葡萄花油层油-水关系复杂,油层原始含油饱和度低,油-水同层比例大.应用近年来精细油藏评价大量钻井、试油、试采和分析化验资料,深入研究油-水同层形成主控;因素,认为葡萄花油层成藏受到构造、砂体规模、异常高压和地层水活动强弱的控制,形成了两种类型的油-水同层,并建立占龙凹陷葡萄花油层西滞留、东分异的差异性成藏模式,总结出古龙油田葡萄花油层滞留型、分异型油-水同层分布规律,为大面积油-水同层岩性油藏提交探明储量、编制开发方案提供了依据.     

中国降水混沌识别及空间聚类

0-1混沌测试方法是一种新的可直接作用于时间序列的混沌识别方法,不需要进行相空间重构,通过对Chebyshev映射的检验验证了有效性。运用0-1方法对中国640个气象站1960-2011年月降水序列进行混沌识别,并运用基于密度的顾及非空间属性的空间聚类方法（DBSC）对计算结果进行空间聚类。结果表明,各气象站月降水序列均表现出明显的混沌特性,且K值的空间分布具有明显的分区特征：从大尺度上看,全国可分为西北高值区、南方次高区、华北-东北中值区和青藏低值区;从小尺度上看,全国分出了29个空间簇。中国降水混沌空间聚类结果不仅与大尺度的气候类型分布相吻合,而且也反映了局部降水动力系统变化特征,这就为降水系统的时空规律研究提供了一条新的途径和方法。     

引起“碧利斯”强降水的MCS数值模拟研究

利用多种观测资料和数值模拟,对0604号强热带风暴碧利斯登陆后在湖南、广东等地引发强降水的中尺度对流系统活动特征进行了分析.结果表明,在"碧利斯"登陆后西行减弱过程中,由于西南季风的持续维持,"碧利斯"减弱后的低压环流中仍保持有强降水所需的充足水汽供应,造成局地强降水的MCS十分活跃.ARPS模式较好地模拟了7月15日发生在湖南南部的中尺度降雨过程,并揭示出"碧利斯"变性过程中,环境风场垂直切变结构强迫的次级环流决定了MCS活动特点,同时利用湿Q矢量诊断了低压次级环流的垂直运动特征.造成这次强降水过程的MCS在台风低压切变线以北的偏北潮湿气流中生成发展,低层偏北急流造成的动力辐合效应、对流不稳定性层结的建立是MCS在湖南南部迅速发展的重要原因.     

应用奇异向量方法的适应性观测实例研究

近年来,通过适应性观测技术来减小预报误差已成为国际上数值预报中的一项关键技术,然而实施适应性观测对减小预报误差的影响评估是一个需要深入讨论的问题。文中利用奇异向量方法以2007年3月4日东北地区暴风雪天气过程为研究对象,考察了预报误差对不同观测区域观测资料的敏感性,在确定能量范数的基础上,分析了奇异向量的水平分和特征和垂直分布特征,利用奇异向量的空间结构确定了敏感区域。通过伪逆初始扰动场作为分析误差,研究验证区域的预报误差对不同区域增加观测的敏感性,试验结果表明,在敏感区域内进行补充观测来改善分析误差,能够最有效地提高验证区域内的预报水平;而减小非敏感区域内的分析误差对减小预报误差的贡献相对较小。这些结果表明,利用奇异向量法定义敏感区进行适应性观测,能够和有限的观测资源和计算资源的条件下,最大程度地减小验证区域的预报误差,从而达到提高验证区域预报准确率的目的。     

试论干酪根生油与热力学第二定律的关系

用热力学第二定律考察干酪根生油,是一个吸热和熵减的过程,与放热和熵增为特征的自发过程相悖。因此,热力学第二定律并不支持干酪根生油过程。对初生石油在泥岩中的初次运移提出质疑。在否定基岩油藏"上生下储"的基础上,认为石油来源于深部。     

地震波形数据处理软件研发

通过分析地震数据EDAS Event格式与SEED格式在文件头与数据部分存储的特点与规律,利用Visual Basic语言研发地震波形数据处理软件.利用此软件,可以完成地震记录数据的格式转换,以及数据的抽取与合并,保证数据记录的连续与衔接,提高数据的连续性和利用价值.     

Estimating seasonal habitat suitability for migratory species in the Bohai Sea and Yellow Sea: A case study of Tanaka’s snailfish (Liparis tanakae)

Acquiring a comprehensive and accurate understanding of habitat preference is essential for species conservation and fishery management, especially for mobile species that migrate seasonally. Presence and absence data from field surveys are recommended when available due to their high reliability. Using field survey data, we investigated seasonal habitat suitability requirements for Tanaka’s snailfish (Liparis tanakae) in the Bohai Sea and Yellow Sea (BSYS) via a machine-learning method, random forests (RFs). Five environmental and biologically relevant variables (bottom temperature, bottom salinity, current velocity, depth and distance to shore) were used to build the ecological niches between the presence/absence data and suitable habitat. In addition, the degree to which false absence data might impact model performance was evaluated. Our results indicated that RFs provided accurate predictions, with seasonal habitat suitability maps of L. tanakae differing substantially. Bottom temperature and salinity were identified as important factors influencing the distribution of L. tanakae. False absence data were found to have negative effects on model performance and the decrease in evaluation metrics was usually significant (P<0.05) after 30% or more errors were added to the absence data. Through identifying highly suitable areas within its geographic range, our study provides a baseline for L. tanakae that can be further applied in ecosystem modelling and fishery management in the BSYS.     

Application of equilibrium partitioning approach to derive sediment quality criteria for heavy metals in a shallow eutrophic lake, Lake Chaohu, China

In this study, the equilibrium partitioning approach was used to derive the sediment quality criteria (SQC) recommended values of eight heavy metals (Cr, Cu, Pb, Zn, Cd, As, Fe and Mn) for surface sediments taken from Lake Chaohu. The concentration of the heavy metal in the interstitial water (C _IW) was determined by the film diffusion gradient technology to obtain the metal partitioning coefficient (K _P). Moreover, the metal fractionation of the sediments were analyzed using European Community Bureau of Reference sequential extraction procedure and the partitioning of bound phases including total organic carbon (TOC), grain sizes and acid volatile sulfide (AVS) were also investigated. The values of K _P for Cr, Cu, Pb, Zn, Cd, As, Fe and Mn were 3,924.84, 2,276.23, 17,811.30, 738.35, 10,986.54, 718.74, 5,875.34 and 341.20 L/kg, respectively. Sediment quality criteria were normalized on the basis of fine materials, AVS, TOC and the residual metals (M _R). SQC values for Cr, Cu, Pb, Zn, Cd, As, Fe and Mn based on Chinese surface water quality criteria were derived with the values of 78.53, 56.95, 362.93, 74.68, 23.90, 71.84, 3,546.53 and 68.42 mg/kg, respectively. The suggested SQC values in this study were compared SQCs from different countries and areas, which indicated SQCs from different countries or regions appeared to have great discrepancies attributed to the difference of the physical and chemical characteristics of sediments.     

高光谱热红外遥感：现状与展望

高光谱热红外数据中蕴含着丰富的长波光谱信息,可以更精细的揭示地气耦合过程导致的辐射变化,反映热红外谱段特有的地物诊断特征,同时高光谱特性也可以为热红外关键特征参数的病态反演问题提供更合理的假设和约束条件,具有重要的研究价值和应用前景。高光谱热红外遥感技术自诞生起,在吸纳多光谱热红外遥感技术的基础上迅速发展,成为热红外遥感领域的重要研究方向和突破点。然而,当前高光谱热红外遥感存在着可用数据不足,处理方法传统,反演精度有限,应用难以有效实施等问题。为进一步明晰高光谱热红外遥感的研究进展和现存挑战,本文在高光谱热红外相关文献深入分析的基础上,梳理了高光谱热红外研究的发展脉络和热点,介绍了现有国内外主要的高光谱热红外传感器,分析了高光谱大气效应校正、地表温度和发射率分离以及地气关键特征参数一体化反演的现状和问题,总结了相关典型行业应用,展望了高光谱热红外的发展方向,以期为未来高光谱热红外研究工作的开展提供借鉴和帮助。