Dynamics of Axisymmetric Truncated Dynamo Models

An important question regarding the study of mean field dynamo models is how to make precise the nature of their underlying dynamics. This is difficult both because relatively little is known about the dynamical behaviour of infinite dimensional systems and also due to the numerical cost of studying the related partial differential equations. As a first step towards their understanding, it is useful to consider the corresponding truncated models. Here we summarise some recent results of the study of a class of truncated axisymmetric mean field dynamo models. We find conclusive evidence in these models for various types of intermittency as well as multiple attractors and final state sensitivity. We also find that the understanding of the underlying dynamics of such dynamo models requires the study of a new class of dynamical systems, referred to as the non-normal systems. Current work demonstrates that these types of systems are capable of a novel type of intermittency and also of relevance for the understanding of the full axisymmetric PDE dynamo models.     

Importance of no‐rain measurements on the comparison of radar and rain gauge rain rate

This study evaluated four possible cases of comparing radar and rain gauge rain rate for the detection of mean‐field bias. These four cases, or detection designs, consider in this study are: (1) design 1‐uses all the data sets available, including zero radar rain rate and zero rain gauge rain rate, (2) design 2—uses the data sets of positive radar rain rate and zero or positive rain gauge rain rate, (3) design 3—uses the data sets of zero or positive radar rain rate and positive rain gauge rain rate and (4) design 4—uses the data sets of positive radar rain rate and positive rain gauge rain rate. A theoretical review of these four detection designs showed that only the design 1 causes no design bias, but designs 2, 3 and 4 can cause positive, negative and negative design biases, respectively. This theoretical result was also verified by applying these four designs to the rain rate field generated by a multi‐dimensional rain rate model, as well as to that of the Mt Gwanak radar in Korea. The results from both applications showed that especially the design 4, which is generally used for the detection of mean‐field bias of radar rain rate, causes a serious design bias; therefore, is inappropriate as a design for detecting the mean‐field bias of radar rain rate. Copyright © 2009 John Wiley & Sons, Ltd.     

AVERAGE GLOBAL LOCATIONS

Global distributions are commonly described by maps and tables which emphasize the dispersion of a distribution. The Mean Spheroidal Center (M.S.C.) defines the average location of a world distribution. It is an objectively determined point within the sphere's surface. The M.S.C. calculations are demonstrated using the world's 25 largest cities in each of four time periods.     

Evaluation of the “fishing down marine food web” process in the north-west of Persian Gulf(Khuzestan Province) during the period of 2002–2011

The worldwide increase in commercial fisheries and its impact on ecosystems as well as inefficient fishery management have led to overfishing and frequent breakdown of traditional fish stocks.In this context,an analysis of Khuzestan inshore fisheries data covering the years 2002–2011,was conducted in reliance on testing for occurrence of the fishing down marine food webs(FDMFW) phenomenon in the North of Persian Gulf Large Marine Ecosystem(LME).In this study,the mean trophic level(m TL) and the fishing-in-balance(FIB)-index of Khuzestan landings during this period of time were estimated using the trophic level of 47 fishery resources.Increase in total landings(Y) was observed,which explained the high fishing yield in major fishery resources(especially demersal).Moreover,the moderates decreasing trend in m TL per decade,and the increasing trend in FIB-index were observed.The status of fishery resources in Khuzestan inshore waters(under exploited but not overexploited),the rise in Y,FIB and slightly drop in m TL can be considered as indirect indicators of the fishing impacts on the trophic structure of marine communities.Based on this result,probability occurrence of FDMFW process in Khuzestan inshore waters is low to some extent.However,we suggest that the goal of management programs in Khuzestan inshore waters should prevent the continuance of this trend in the long-term using an ecosystem-based approach.     

新型张力腿式储油处理平台的动力响应分析

针对目前小油田早期生产中存在的不足,提出一种适用于浅水海域的新型张力腿式储油处理平台,该平台主要由储油箱、浮箱、吸力桩、系泊链和甲板结构构成,具备原油处理和储存功能。应用非线性时域耦合分析法,研究了有义波高、平均波周期、水深对该平台的运动响应和系泊链张力的影响。计算结果表明,波高对平台动力响应有较大影响,有义波高每增加0.4 m,平台水平位移相应增加0.408 m,而系泊链力随有义波高的增加呈准线性增大;波周期对平台水平运动影响显著,平均波周期从6.5 s逐级变化至8.5 s时,最大水平位移自3.760 m渐增至5.467 m,而波周期对系泊链力影响较小,变化率一般小于10%;该新型平台对水深大于20 m的浅水海域有良好的动力特性,而对水深小于20 m的海域却表现异常。因此,该新型张力腿式平台能满足水深不小于20 m浅海区的油田早期生产需要。     

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顾及几何特征和拓扑连续性的道路网匹配方法

已有的道路网匹配方法需要一定的人为干预和控制,仍无法实现匹配自动化,而且对于具有一定尺度差异的数据而言,受不相关道路对象的影响,匹配结果中会存在较多的误匹配。为此,本文提出一种顾及几何特征和拓扑连续性的由粗匹配到精匹配的分层匹配策略。粗匹配阶段,利用短边中位数Hausdorff距离计算匹配对象的相似度,再以道路网弧段端点的近邻分析结果作为匹配阈值,判断匹配对象是否为同名实体;精匹配阶段,将粗匹配阶段评价结果中离散的同名实体构建为完整的道路Stroke,即以追踪的方式剔除误匹配和添加漏匹配。利用宿城区不同尺度的道路网对所提算法进行验证,结果表明,该算法具有较好的匹配效果,能够实现匹配自动化。     

一种多因子加权平均温度模型的构建方法

针对在地基GNSS水汽反演的过程中,天顶湿延迟转换为大气可降水量时如何建立精确的大气加权平均温度(Tm)模型的问题,该文在建立Tm模型前全面考虑了对Tm有显著影响的变量并选择最优回归子集。但分析发现,最优回归子集中各变量之间存在较强的相关性,这将会导致变量之间存在多重共线性,从而影响模型的稳定性和可靠性。选择2013—2015年相关气象数据作为变量并应用岭回归的方法削弱变量之间的多重共线性,建立稳定的多因子Tm回归模型。并利用该模型分别预测2016年1—12月、2019年1—7月的Tm,均方根误差分别为2.3 K和2.0 K,预测精度较高,这将为高精度的水汽反演奠定较好的数据基础。     

“频率匹配法”在集合降水预报中的应用研究

基于“频率匹配法”的思路,采用两种方法进行了集合降水预报的订正研究,一种方法是利用集合成员降水频率订正简单集合平均平滑效应的“概率匹配平均”法,另一种方法是利用实况降水频率订正集合成员降水预报系统偏差的“预报偏差订正”法,通过个例和批量试验,结果表明:(1)概率匹配平均法可以矫正简单集合平均的平滑作用所造成的小量级降水分布范围增大而强降水被削弱的负作用,这种改进对强降水区更显著,并且集合系统离散度越大这种改进也越大;但该方法对预报区域内总降水量的预报没有改进作用,不能改善预报的系统性偏差.(2)虽然预报偏差订正法对降水落区预报的改进有限,但可以订正模式降水预报的系统性误差,改进雨量预报以及集合预报系统的离散度特征和概率预报技巧;直接对集合平均预报进行偏差订正的效果优于单个成员偏差订正后的简单算术平均.(3)在对每个集合成员的降水预报进行偏差订正后,概率匹配平均仍可改善其简单平均的效果,因此在实际业务中,应该综合采用上述两种方法,以获得在消除系统性偏差的同时各量级降水分布又合理的集合平均降水预报.     

GRAPES_RAFS系统2 m温度偏差订正方法研究

本文通过对2013年6月20日至7月20日GRAPES(Global and Regional Assimilation and Prediction System)_RAFS(Rapid Analysis and Forecast System)系统每天8个时次每3h的2 m温度预报进行分析,发现各时次的预报均能较好地表征2 m温度日变化特征,但预报与实况存在一定的偏差,其中西藏东部川西高原、云贵高原、江南武夷山脉偏低于实况可达3℃,而华北地区偏高于实况3℃以上.为了减小GRAPES_RAFS系统偏差对2m温度预报的影响,本文采用平均法、双权重平均法、滑动平均法和滑动双权重平均法分别对GRAPES_RAFS系统2 m温度预报产品进行偏差订正,并对订正前后的结果进行检验分析和对比.结果表明:2 m温度订正后的平均误差大部地区减小到(一1～1℃),而均方根误差大部地区降低到2.5℃内.对于偏差较大地区,订正效果更为明显,如西藏东部川西高原,经过订正,平均误差绝对值由订正前3℃以上降低到1℃内,而RMSE由订正前4℃以上控制到3℃内.对比四种订正方法,双权重订正方法与平均法订正整体效果接近,但对个别站点,双权重订正法要优于平均法,经过滑动的订正方法比无滑动的订正方法订正效果更好,订正效果最好的是滑动双权重平均法,全国平均误差大部分在(-0.5～0.5℃)内,不超过(-1～1℃)的范围.