宁夏六盘山区多年降水的时空变化分析

选用宁夏六盘山区4个代表测站自建站以来至2007年的各月降水资料,用回归、周期和突变分析等统计方法进行分析,揭示了其多年时空变化规律.通过分析,得出了其季、年线性变化趋势和年变化周期及突变点,发现各区域降水存在着不同的变化规律,年降水均呈减少趋势,存在准14 a、11 a等变化周期,并发生了多次突变.     

基于集对分析的洪水分类研究

为避免常规分类方法复杂的数学理论和繁琐的计算,提出了基于集对原理的洪水分类新方法——集对分析法(SPAM)。系统地给出了集对分析法的基本思路和计算步骤。建议方法概念清晰,结构简单,计算简洁,易操作,是一种有效的分类途径。以实测洪水过程为例,应用研究表明集对分析法的分类结果是可行的。     

雪崩、分形与雷暴放电中强闪的自组织演化

强调了雪崩、分形与远离平衡系统自组织演化的联系。利用2003年夏季青藏高原中部地区雷暴放电的地面电场野外观测资料,基于近年来发展的分形及多重分形分析中的去势涨落分析(detrend-ed fluctuation analysis,DFA)方法,对强闪前电场信号的关联及多重分形特征进行了分析,发现强放电前过程具有明显的分形和多重分形特征,多重分形谱与推广的二项倍增串级模式符合。分析在一定程度上表明了雷暴强放电发生的可能的自组织演化性。     

海口市重污染天气潜在源分析研究

在进入冬半年后,海口市受弱冷空气或较强下沉气流控制时,易出现污染天气,对2013—2015年当年10月至翌年1月的气团轨迹进行了聚类分析、潜在源贡献因子分析(Potential Source Contribution Function,PSCF)和重轨迹分析(Concentration Weighted trajectory,CWT),结果表明:在污染时段内,海口大多受到来自中国华南和华东的东北向气流影响。PSCF和CWT分析表明,广东、福建、江西的大部分地区,以及湖南东部、广西东部等地区,是对海口地区污染天气污染物浓度的潜在贡献大值区。在进行预报时,可参考主要天气影响系统,和一些关键区域的外源影响以及本地污染的堆积情况。     

Response of ocean dynamics to multiple equilibria of the Kuroshio path South of Japan

Variability of the Kuroshio path to the south of Japan plays a central role in the local climate change and exerts tremendous influences on the local atmosphere and ocean. In this study, the response of ocean dynamics, in terms of the eddy kinetic energy (EKE), potential vorticity (PV), relative vorticity, and eddy-mean flow interaction, to the Kuroshio path change is discussed. Kuroshio path south of Japan includes the near-shore non-large meander (nNLM), the off-shore non-large meander (oNLM), and the typical large meander (tLM). Analyses reveal that the distribution of EKE, PV, relative vorticity, and energy exchange between the eddy field and the mean flow respectively varies with the Kuroshio path: (1) The tLM has the maximum EKE along the path; (2) The positive and negative PV are located at the onshore and offshore side of Kuroshio axis, respevetively; (3) The distributions of anomalous relative voritcity of nNLM, oNLM, and tLM are consistent with sea surface height anomalies (SSHAs); (4) The tLM has the largest energy exchange between the eddy field and the mean flow in terms of the rate of barotropic energy conversion. On the other hand, the stability analysis of ocean currents suggests that the three Kuroshio paths south of Japan have their own intrinsic properties of the instability.     

冬季北大西洋涛动与中国北方极端低温相关性的年代际变化

本文基于中国地面气温日值网格数据集（V2.0）,采用滑动相关和相关分析等方法,揭示了冬季北大西洋涛动（NAO）对中国北方极端低温影响的事实,进一步证实了东北后冬（1、2月）冷日（夜）与同期NAO相关性的年代际变化。研究发现:在20世纪80年代中期前,东北后冬冷日（夜）频发,与NAO的相关性较好,而在80年代中期后东北后冬冷日（夜）少发,与NAO的相关性减弱。其中,1月在1969~1988阶段,东北冷日（夜）与NAO的相关性最好,相关区域显著,相关系数可达-0.68（-0.66）,而在1989~2009阶段二者相关性最弱,相关区域不显著。进一步分析发现,在不同年代际背景下,NAO引起的大气环流异常是导致东北1月冷日（夜）与1月NAO相关性年代际变化的重要原因。相关性较好的年代,NAO引起的环流异常有利于冷涡等天气系统维持在贝加尔湖到东北一带,使东北地区气温偏低,冷日（夜）频发;相关性较弱的年代,不利于冷空气南下,使东北地区气温偏高,冷日（夜）少发。     

中国东部夏季降水与气温的联合EOF分析

采用JEOF等方法分析中国东部夏季降水和气温的协同变化时空分布特征,结果表明:当时间系数为正时,第1典型场降水型态从北向南(下同)呈"++-"分布,气温表现为冷异常,500 hPa回归场在中纬度地区呈显著低压异常,SST回归场表现为太平洋海域呈西北-东南的分布;第2典型场降水呈"+-"分布,气温则呈"-+"分布;第3典型场降水分布呈中间型,气温场呈"-+"分布。     

Land-surface segmentation as a method to create strata for spatial sampling and its potential for digital soil mapping

Sampling efforts are constrained by limited availability of resources. Therefore, methods to reduce the number of samples, while still achieving reasonable accuracy are needed. Land-surface segmentation (LSS) has proven a powerful technique to partition digital elevation models (DEMs) and their derivatives into relatively homogeneous areas, which can be further employed as support in soil sampling. Though topography is one of the main soil forming factors, a robust assessment of the potential of this technique to digital soil mapping (DSM) is still missing. In this study, we aimed at evaluating the potential of LSS in stratifying a landscape into relatively homogeneous areas, which can be used as strata for guiding the selection of sampling points in DSM. The experiments were carried out in two study areas where soil samples were available. Land-surface derivatives were derived from DEMs and segmented with a tool based on the multiresolution segmentation algorithm, into objects considered as homogeneous soil-landscape divisions. Thus, one sample was randomly selected within each segment from the existing sample data, based on which predictions of soil classes/sub-orders and properties, i.e. soil texture and A-horizon thickness, were made. Results were compared with predictions based on simple random sampling (SRS) and conditioned Latin hypercube (cLHS). The segmentation-based sampling (SBS) scheme performed better than SRS and cLHS schemes in predicting the A-horizon thickness, soil texture fractions and soil classes, showing a high potential of LSS in stratifying a landscape for the purposes of DSM. The novelty of this study is in the way strata are constructed, rather than in the sampling design itself. Further research is needed to demonstrate the value of a SBS design for practical use. The analyses presented here further highlight the importance of considering locally adaptive techniques in optimization of sampling schemes and predictions of soil properties.     

Unsupervised regionalization of the United States into landscape pattern types

We present a pattern-based regionalization of the conterminous US – a partitioning of the country into a number of mutually exclusive and exhaustive regions that maximizes the intra-region stationarity of land cover patterns and inter-region disparity between those patterns. The result is a discretization of the land surface into a number of landscape pattern types (LPTs) – spatial units each containing a unique quasi-stationary pattern of land cover classes. To achieve this goal, we use a recently developed method which utilizes machine vision techniques. First, the entire National Land Cover Dataset (NLCD) is partitioned into a grid of square-size blocks of cells, called motifels. The size of a motifel defines the spatial scale of a local landscape. The land cover classes of cells within a motifel form a local landscape pattern which is mathematically represented by a histogram of co-occurrence features. Using the Jensen–Shannon divergence as a dissimilarity function between patterns we group the motifels into several LPTs. The grouping procedure consists of two phases. First, the grid of motifels is partitioned spatially using a region-growing segmentation algorithm. Then, the resulting segments of this grid, each represented by its medoid, are clustered using a hierarchical algorithm with Ward’s linkage. The broad-extent maps of progressively more generalized LPTs resulting from this procedure are shown and discussed. Our delineated LPTs agree well with the perceptual patterns seen in the NLCD map.     

北京市风险投资的空间分布与合作网络研究

国内外有关风险投资(VC)空间集聚的研究大多基于国家层面,本文基于北京市VC机构的位置和联合投资信息,运用本文空间分析与社会网络分析技术,研究VC机构的空间集聚和合作网络。空间分析发现,VC机构主要集聚在CBD、金融街、中关村三大核心区;在时间尺度上呈现分散—集聚—再分散的趋势。其中,国资机构主要集聚于金融街,外资机构主要落户于CBD,且以私募基金(PE)类机构为主;中关村则依托高新技术成为创新型企业的融资区。叠加合作网络后进一步发现,城市尺度下的VC机构合作并不受地理区位限制,并且各个VC集聚区之间关系颇为紧密。按“中心度”到“边缘—核心”的递推分析表明,外资机构在北京市风险投资合作网络中具有突出地位,其对联合投资的偏好主导了网络的形态。国资虽占据了部分网络节点但核心地位不够突出,而本土民营机构虽然数量较大但在网络中多处于半边缘位置。