东亚夏季风的年际变化及其对环流和降水的影响

Using NCEP/NCAR reanalysis geopotential height (GHT) and wind at 850 hPa, GHT at 500 hPa, precipitation rate, sea level pressure (SLP) and precipitation observations from more than 600 stations nationwide in June–August from 1951 to 2006, and focusing on the East Asia-West Pacific region (10°–80°N, 70°–180°E), interannual variation of East Asian summer monsoon (EASM) and its correlations with general circulation and precipitation patterns are studied by using statistical diagnostic methods such as 9-point high pass filtering, empirical orthogonal function (EOF) analysis, composite analysis and other statistical diagnosis, etc. It is concluded as follows: (1) EOF analysis of SLP in the East Asia-West Pacific region shows the existence of the zonal dipole oscillation mode (APD) between the Mongolia depression and the West Pacific high, and APD index can be used as an intensity index of EASM. (2) EOF analysis of GHT anomalies at 500 hPa in the East Asia-West Pacific region shows that the first EOF mode is characterized with an obvious meridional East Asian pattern (EAP), and EAP index can also be used as an EASM intensity index. (3) The composite analysis of high/low APD index years reveals the close correlation of APD index with EAP at 500 hPa (or 850 hPa). The study shows an obvious opposite correlation exists between APD index and EAP index with a correlation coefficient of −0.23, which passes the confidence test at 0.10 level. (4) Both APD and EAP indexes are closely correlated with precipitation during flood-prone season in China and precipitation rate over the East Asia-West Pacific region. The significant correlation area at 5% confidence level is mainly located from the southern area of the Yangtze River valley to the ocean around southern Japan, and the former is a positive correlation and the latter is a negative one. Foundation: Cooperative Project funded by the Ministry of Science and Technology of the People’s Republic of China, No.2007DFB20210; National Natural Science Foundation of China, No.90502003; JICA China-Japan Technical Cooperative Project “China-Japanese Cooperative Research Center on Meteorological Disasters”. Author: Yu Shuqiu, Associate Professor, specialized in climate and climate change.     

一种基于＂3S＂技术的城镇地籍数据变更模式研究

从城镇地籍数据变更管理的发展趋势和当胁管理工作的需求现状出发,结合“3S”技术的最新发腥,引入基于时空数据模型的空删数据库技术、丽向对象等先进技术,埘城镇地籍数据变更模式进行了研究,提出了基于“3S”集成技术的城镇地籍数据变更新模式,并探讨了在这种变更模式下城镇地籍数据变更工作实施与数据管理的问题。     

Supervised neural network recognition of habitat zones of rice invertebrates

This study aimed to evaluate effectiveness and performance of several supervised neural network models and make pattern recognition on invertebrate habitat zones. Probabilistic, general regression, and linear neural networks, and discriminant analysis were used to recognize both known and unknown invertebrate habitat zones. The results showed that neural network models were better than traditional discriminant analysis in the recognition of known habitat zones. There was not distinctive variation in recognition from different neural network models. Sensitivity analysis indicated that the learning rate of the neural network would influence recognized results. An unknown invertebrate species from Lepidoptera was recognized to be soil-dweller (dryland) by both neural network models and discriminant analysis. In sensitivity analysis it was additionally recognized to be the type of plant canopy (terrestrial). Overall the species was estimated to be a soil-dweller (dryland) or live on plant canopy (terrestrial). It was concluded that neural network models can perform better than conventional statistic models in pattern recognition, but a comprehensive comparison among various models is necessary in order to achieve a high reliable recognition and prediction. Furthermore, sensitivity analysis can lead to an in-depth grasp on the mechanism in the recognition and is thus needed.     

基于机器学习的重庆长江航道雾图像特征识别研究

基于重庆市境内长江航道雷达站拍摄的雾天气过程影像资料,利用K最近邻、支持向量机、BP神经网络、随机森林等机器学习算法,对无雾和5类有雾天气个例进行图像识别训练,构建雾图像识别模型,并检验了识别准确率。结果表明：机器学习能够有效识别雾图像,随机森林算法的识别效果优于其余3种算法。对于能见度超过1500 m的无雾天气,模型的识别准确率为100%,对于能见度在1000—1500 m范围内的轻雾、能见度低于50 m的强浓雾,模型的识别准确率在90%以上,对于能见度在50—1000 m范围内的雾、大雾和浓雾,识别准确率超过70%。     

应用模式识别定量划分潜在震源区

本文以陕西关中及部分邻区为例,考虑地质构造、地震活动及地球物地场等因素,采用不同的模式识别方法和多种计算方案,以定量判定潜在震源区。其结果表明,模式识别方法有利于地质、地震活动及地球物理场等多种因素综合应用,并能选择和显示判定潜有震源区的主要特征。不同模式识别方法的比较和多种试验方案的综合,则可提高潜在震源区判定的可靠性和稳定性。     

广东旅游休闲产业空间布局模式的构建

从大珠三角与其周边地区的地理梯度特征,可见大珠三角在广东地理、经济、文化中的核心地位,其周边地区的边缘地位。这种“核心”与“边缘”或“中心”与“外围”的关系实际上构造了一个相对稳定的旅游系统,前者主要成为旅游客源地,后者主要成为旅游接待地。大珠三角城际在空间上的逐步融合,构成了广东“环大珠三角城市群游憩带”和“点-轴树状游憩网”,以及“南部濒海游憩廊”的旅游休闲产业空间布局模式。     

区域土地利用及土地覆盖的空间格局研究--以广西梧州市为例

从分析梧州市土地利用现状入手, 总结其土地利用的现状特征, 而后在引入多样性指数、优势度指数、均匀度指数和破碎度指数的基础上, 对梧州市土地利用／ 覆盖的空间格局进行了定量分析。最后, 根据计算结果得出有关结论。     

7月份两种东亚阻塞形势对中国主要雨带位置的不同影响

根据长期的业务实践,把7月份东亚阻塞形势分为副热带高压偏西型(W型)和副热带高压偏东型(E型)两类阻塞形势,对比两种阻塞形势下中国主要雨带位置的差别后发现,W型主要雨带在长江流域,1951年以来较严重的长江大水是此类阻塞形势造成的;E型主要雨带位于江南至华南地区,长江流域洪涝较轻。不仅两种阻塞形势的7月份环流有重大差别,其前期秋、冬、春季海洋、大气和天气气候特点也大不相同。     

中长期径流预报的一种灰关联模式识别与预测方法

基于时间序列多重信息利用的扩维原理和灰色系统理论的关联分析思想,提出一种应用于水文中长期预报的方法.它的特点是直接从径流序列的扩维相型关联分析中,寻求径流情势变化规律,较适合于缺乏输入因子资料或选择影响因子有困难条件下的水文中长期预报.利用海河、黄河和长江流域若干水文站的实测资料序列对该方法做了初步验证.