Identification of Convective and Stratiform Clouds Based on the Improved DBSCAN Clustering Algorithm

A convective and stratiform cloud classification method for weather radar is proposed based on the density-based spatial clustering of applications with noise (DBSCAN) algorithm. To identify convective and stratiform clouds in different developmental phases, two-dimensional (2D) and three-dimensional (3D) models are proposed by applying reflectivity factors at 0.5° and at 0.5°, 1.5°, and 2.4° elevation angles, respectively. According to the thresholds of the algorithm, which include echo intensity, the echo top height of 35 dBZ (ET), density threshold, and ε neighborhood, cloud clusters can be marked into four types: deep-convective cloud (DCC), shallow-convective cloud (SCC), hybrid convective-stratiform cloud (HCS), and stratiform cloud (SFC) types. Each cloud cluster type is further identified as a core area and boundary area, which can provide more abundant cloud structure information. The algorithm is verified using the volume scan data observed with new-generation S-band weather radars in Nanjing, Xuzhou, and Qingdao. The results show that cloud clusters can be intuitively identified as core and boundary points, which change in area continuously during the process of convective evolution, by the improved DBSCAN algorithm. Therefore, the occurrence and disappearance of convective weather can be estimated in advance by observing the changes of the classification. Because density thresholds are different and multiple elevations are utilized in the 3D model, the identified echo types and areas are dissimilar between the 2D and 3D models. The 3D model identifies larger convective and stratiform clouds than the 2D model. However, the developing convective clouds of small areas at lower heights cannot be identified with the 3D model because they are covered by thick stratiform clouds. In addition, the 3D model can avoid the influence of the melting layer and better suggest convective clouds in the developmental stage.     

纵向和横向同时约束AVO反演

为了提高AVO(amplitude versus offset)反演结果的精度和横向连续性,本文提出了一种新的AVO反演约束方法,该方法结合贝叶斯原理和卡尔曼滤波算法实现了对反演参数纵向和横向的同时约束.文章首先结合反演参数的纵向贝叶斯先验概率约束和反演参数的横向连续性假设建立了与卡尔曼滤波算法对应的AVO反演系统的数学模型,然后将该数学模型代入卡尔曼滤波算法框架,利用卡尔曼滤波算法实现了双向约束AVO反演.二维模型测试和实际数据测试结果表明,相对于单纯的纵向贝叶斯先验概率约束,双向约束能更准确地刻画参数的横向变化,得到更准确、横向连续性更好的反演结果.     

三维地质模型中地震波共轭梯度非线性走时反演

地震体波走时层析成像是探测地球内部速度结构的重要方法之一。基于三维块状建模以及三角形拼接的界面描述方式,结合快速高效的逐段迭代射线追踪方法,获得三维复杂地质模型中的地震射线路径与走时信息,采用共轭梯度非线性反演算法,进行地震波走时反演。实验结果表明共轭梯度反演算法在三维层状模型中具有较高的有效性。     

高光谱气体背景场特征及震情跟踪应用前景

基于2004—2017年华北地区高光谱数据,计算CH4、CO、O3总量背景场,发现不同气体在时间尺度上受温度、湿度、高空辐射等影响有较明显的周期性特征,在空间尺度上CH4、CO总量平原高于山区,O3总体呈现随纬度升高而降低的特征;利用RST算法对华北地区5.0级以上地震进行震例总结发现,震前62.5%的地震震中附近出现气体高值异常,异常气体主要为CH4、CO,而O3异常不明显。研究结果表明,RST算法对高光谱气体CH4、CO进行异常提取可作为地震预报的辅助依据,服务于震情跟踪判定。     

江汉平原主要河流沉积物磁学特征及其与物源区表壳岩性的响应

为了建立江汉平原沉积物示踪的磁学模型,对汇入江汉平原的主要河流现代沉积物磁学特征进行了研究,结果表明:(1)在江汉平原范围内,无论长江、汉江,还是周边的漳河、沮水、玛瑙河和清江,它们的现代沉积物的磁学参数特征均显示出明显的差异,而且和源区表壳岩性也显示出极好的相关性;(2)长江和汉江现代沉积物中铁磁性矿物均以亚铁磁性矿物为主,它们主导了样品的磁性特征,但长江沉积物比汉江沉积物亚铁磁性矿物含量高;(3)长江和汉江沉积物的亚铁磁性矿物晶粒都以假单畴-多畴为主,并且长江沉积物磁性颗粒总体上要比汉江的粗;(4)在汇入江汉平原的主要支流中,汉江的亚铁磁性矿物含量远远高于其他支流,且磁性矿物的晶粒也比其他支流的粗;(5)除汉江以外的支流中,玛瑙河沉积物中磁性矿物的晶粒比较细且不完全反铁磁性矿物含量较高,漳河中的超顺磁物质含量较高,而清江中不完全反铁磁性矿物含量较高且磁性矿物的晶粒相对较粗.上述结果表明,在江汉平原利用沉积物的磁学特征可达到沉积物物源示踪的目的.      

区域生态地球化学评价核心与对策

生态地球化学是地学与土壤学、农业、环境学和生态学等多学科交叉融合产生的新学科,是地球化学领域新的发展方向。区域生态地球化学评价是在区域地球化学调查基础上,针对影响流域/区带生态系统安全性的元素异常而开展的一项评价和研究工作。多目标区域地球化学调查获得的海量高精度地球化学数据,可为环境质量评价提供背景值、为土地的质量和生态管护提供地球化学依据;调查还发现了一系列影响流域生态安全性的元素异常,针对异常元素分布特征,区域生态地球化学评价将开展异常元素追踪和成因甄别、生态效应评价和生态系统安全性的预警预测等项评价和研究工作。文章论述了区域地球化学调查成果,介绍了区域地球化学评价的思路,阐述了区域生态地球化学评价的主要问题与对策。     

西准噶尔红山地区晚古生代赞岐岩锆石U Pb年代学、地球化学特征及其地质意义

中亚造山带西部西准噶尔地区红山花岗岩体内部发育多期似岩墙状安山质暗色条带,LA-ICP-MS锆石U-Pb同位素定年和岩石化学与同位素分析表明,它们具有不同的形成年龄、相同的源区和相似的形成过程。其中,具有不规则状或环状形态的暗色条带,其锆石U-Pb年龄为319.1±2.9 Ma和313.3±2.4 Ma,远大于红山岩体花岗岩锆石结晶年龄(305～301Ma),可能是红山岩体侵位过程中所捕掳的围岩;具有线性展布特征的安山质暗色条带,其锆石U-Pb年龄为295±2Ma,形成于红山岩体侵位之后,构成伸展岩墙群。红山岩体中的安山质暗色条带和线状岩墙群具有相似的岩石化学组成,富SiO_2(56.48%～63.09%)、MgO(3.56%～6.31%),具有高的Mg#值(51.74～62.40)及Na_2O/K_2O值(1.34～3.43);球粒陨石标准化稀土元素(REE)配分模式呈明显的右倾型,富集轻稀土元素(LREE)和大离子亲石元素(LILE)Rb、K、Ba、U、Sr,亏损高场强元素(HFSE)Th、Nb、Ce、P和重稀土元素,具较弱的负铕异常;其同位素组成特征为(~(87 )Sr/~(86 )Sr)i=0.703295～0.703620,(~(143) Nd/~(144) Nd)i=0.512612～0.512618,εNd(t)=6.91～7.62,(~(206) Pb/~(204) Pb)t为17.6883～17.9876,(~(207) Pb/~(204) Pb)t为15.5313～15.5686,(~(208)Pb/~(204)Pb)t为37.4460～38.0581。它们具有与赞岐岩类似的地球化学特征,总体表现出与弧岩浆作用相关的地球化学特征,可能具有共同的物质来源,为准噶尔洋板片俯冲消减后同一地幔源区在不同阶段的产物。其中,形成于弧岩浆作用时期的赞岐岩(319～313 Ma),构成与岛弧花岗岩类伴生的环状似岩墙状安山质暗色条带;形成于后造山伸展岩浆作用晚期的赞岐岩(～295Ma),构成与达拉布特左行走滑作用相关的陆内伸展岩墙群。安山质暗色条带(岛弧火山作用)、红山岩体(后造山伸展)和线状岩墙群(陆内伸展)记录了西准噶尔红山地区洋陆转换的全过程。     

利用SCIT算法分析江淮地区对流云特征

本文设计了一种运用SCIT算法提取雷达拼图中对流云特征量的方法:用SCIT算法识别并追踪云体,算法中只用一个反射率阈值识别对流单体、云体边界;使用模糊逻辑法区分层状云和对流云,提取对流云雷达特征量。使用该方法提取了2013—2015年江淮地区夏季对流云的雷达特征量,并对雷达特征量与降水量分布的关系进行统计分析。结果表明:江淮地区夏季对流云中生命史为13～30 min的对流云比较多,约占总数的60%;生命史大于30 min的对流云较少,并具有平均回波强度、VIL、冷层厚度较大的特征,其最大回波强度和VIL与降水量的相关性较好。     

Operational Evaluation of the Quantitative Precipitation Estimation by a CINRAD-SA Dual Polarization Radar System

In this paper, the quantitative precipitation estimation based on hydrometeor classification (HCA-QPE) algorithm was proposed for the first operational S band dual-polarization radar promoted by the CINRAD/SA radar of China. The HCA-QPE algorithm, the localized Colorado State University-Hydrometeor Identification of Rainfall (CSU-HIDRO) and Joint Polarization Experiment (JPOLE) algorithms, and the dynamic Z-R relationships based on variational correction QPE (DRVC-QPE) algorithm were evaluated with the rainfall events from March 1 to October 30, 2017 in the Guangdong Province. The results indicated that even though the HCA-QPE algorithm did not use the observed rainfall data for correction, its estimation accuracy was better than that of the DRVC-QPE algorithm when the rainfall rate was greater than 5mm h^(-1); and the stronger the rainfall intensity, the greater the QPE improvement. And the HCA-QPE algorithm worked better than the localized CSU-HIDRO and JPOLE algorithms. This study preliminarily verified the improved accuracy of QPE by a dual-polarization radar system modified from CINRAD-SA radar.     

Emissions of Volatile Organic Compounds from Sunflower and Beech: Dependence on Temperature and Light Intensity

Emissions of volatile organic compounds (VOCs) from sunflower (Helianthus annuus L. cv. giganteus) were measured in a continuously stirred tank reactor. The compounds predominantly emitted from sunflower were: isoprene, the monoterpenes -pinene, -pinene, sabinene, 3-carene and limonene, an oxygenated terpene, not positively identified so far and the sesquiterpene -caryophyllene. Emission rates ranged from 0.8 x 10^–16 to 4.3 x 10 ^–15 mol cm^–2 s^–1 at a temperature of 25°C and at a light intensity of 820 µEm^–2 s^–1. A dependence of the emission rates on temperature as well as on light intensity was observed. The emission rates of -pinene, sabinene and thujene from beech (Fagus sylvatica L.) were also affected by temperature as well as by light intensity. Our results suggest that an emission algorithm for all compounds emitted from sunflower and beech has to consider temperature and light intensity simultaneously. The observations strongly indicate that the emissions of VOCs from sunflower and beech are in part closely coupled to the rate of biosynthesis and in part originate from diffusion out of pools. The emission rates can be described by an algorithm that combines the model given by Tingey and coworkers with the algorithm given by Guenther and coworkers after slight modification.