Spatial and Temporal Scale Variations of Sea Surface Temperature in the East Sea Using NOAA/AVHRR Data

Sea surface temperature fields in the East Sea are composed of various spatial structures such as eddies, fronts, filaments, turbulent-like features and other mesoscale variations associated with the oceanic circulations of the East Sea. These complex SST structures have many spatial scales and evole with time. Semi-monthly averaged SST distributions based on extensive satellite observations of SSTs from 1990 through 1995 were constructed to examine the characteristics of their spatial and temporal scale variations by using statistical methods of multi-dimensional autocorrelation functions and spectral analysis. Two-dimensional autocorrelation functions in the central part of the East Sea revealed that most of the spatial SST structures are anisotropic in the shape of ellipsoids with minor axes of about 90–290 km and major axes of 100–400 km. Two dimensional spatial scale analysis demonstrated a consistent pattern of seasonal variation that the scales appear small in winter and spring, increase gradually to summer, and then decrease again until the spring of the next year. These structures also show great spatial inhomogeneity and rapid temporal change on time scales as short as a semi-month in some cases. The slopes in spectral energy density spectra of SSTs show characteristics quite similar to horizontal and geostrophic turbulence. Temporal spectra at each latitude are demonstrated by predominant peaks of one and two cycles per year in all regions of the East Sea, implying that SSTs present very strong annual and semi-annual variations. This revised version was published online in August 2006 with corrections to the Cover Date.     

场域视角下清代北京宣南雅文化核心区范围及空间关联特征

清代北京“宣南文化”是以名人雅士为主体的“雅文化”,宣南地区可视为雅文化大场域。抽提影响雅文化形成的三类核心建筑载体要素：寺庙、名人居所、会馆,在场域视角下用GIS分析三要素微场域的空间分布、关联和聚集,从而递进探析宣南“雅文化核心区”区域性子场域的存在和范围,以及内部要素微场域聚集形成的空间特征和成因。结论包括：① 雅文化核心区范围为清代北京外城西部的中部、中北部“双肾”形区域;其与俗文化区空间临近,没有绝对清晰的边界,投射出雅俗文化间的排斥依存、融渗互补。② 核心区子场域内部的空间关联特征为“三要素、两聚集”的“链条式”“中心-过渡中心”层次性空间结构。③ 量化印证微观街区尺度下“同乡之情”是名人居所与会馆聚集的内在驱动力。在北京“文化中心”战略定位下,为传统文化保护更新策略的提出奠定历史研究基础;在历史文化研究方面,具有方法上的实践创新和借鉴意义。     

中国空气质量时空变化特征

基于2015年中国343个地区空气质量指数（AQI）数据,运用统计分析和空间自相关分析方法,对全国及陆地表层系统九大区域空气质量时空变化特征进行分析。结果表明：① 全国及九大区域空气质量春季较差、夏秋优良、冬季最差,AQI季节均值呈现“U”形变化特征。② 全 国及九大区域AQI月均值变化趋势呈现“L”形特征。③ 全国及九大区域AQI日均值变化趋势呈现周期性W~脉冲型波动规律。④ “高污染”和“低污染”区域呈现出北高南低的南北分异格局。⑤ 九大区域首要污染物频次结构差异明显,频次最高的首要污染物PM_2.5或者PM₁₀在空间上呈现出明显的东西分异格局。     

降水数据空间插值的时间尺度效应

介绍了克里金插值法的前提条件和基本原理,进行了对降水数据的插值试验,发现了时间尺度的改变比变异函数模型的改变对降水数据插值结果精度的影响更大。     

强震地面运动超随机特性的几点注记

本文详细论述了功率谱与功率谱密度、平方和SS与平方平均值MS的适用范围及物理意义,比较深入地分析了平稳和非平稳加速度时间历程的统计特征,通过引入时域包线获取特定相位的方法,考虑了非平稳特性。本文基于非平稳时间历程,在不考虑频率非平稳性的基础上,提出了设计地震动三要素:(1)平方和SS;(2)归一化自相关函数或其对应的功率谱;(3)地震动时域包线.本文提出了在设计地震动合成中考虑超随机特性的实用方法,并指出地震动的超随机特性(即归一化功率谱的锯齿状波动部分,或归一化自相关函数的随机噪声部分)与相位的随机性是地震动随机特性的两个重要方面。本文将地震动的统计分析直接建立在非平稳时间历程的基础之上,从而避开了要对地震动进行平稳化处理的困难。这样提取出的地震动统计特征完全是以真实地震动记录为基础的。应用这些统计特征,可模拟出符合统计要求的基于非平稳时间历程的设计地震动。最后本文还讨论了工程上常用的将反应谱近似转换为功率谱的转换式的一些缺陷。     

有关Kanai-Tajimi模型的统计特征分析

选择金井清过滤白噪声模型,采用留数定理推导出K-T谱激励的自相关函数表达式,并在此基础上利用相关函数法分析出K-T谱激励下的平稳反应,并采用功率谱方法加以验证。这些结果可为结构随机地震反应时域分析和抗震可靠性评估提供基础。     

On trend detection

A main obstacle to trend detection in time series occurs when they are autocorrelated. By reducing the effective sample size of a series, autocorrelation leads to decreased trend significance. Numerous recipes attempt to mitigate the effect of autocorrelation, either by adjusting for the reduced effective sample size or by removing the autocorrelated components of a series. This short note deals with the latter, also called prewhitening (PW). It is known that removal of autocorrelation also removes part of the trend, which may affect the signal‐to‐noise ratio. Two popular methods have dealt with this problem, the trend‐free prewhitening (TFPW) and the iterative prewhitening. Although it is generally accepted that both methods reduce the adverse effects of PW on the trend magnitude, corresponding effects on statistical significance have not been clearly stated for TFPW. Using a Monte Carlo approach, it is demonstrated that both methods entail quite different Type‐I error rates. The iterative prewhitening produces rates that are generally close to the nominal significance level. The TFPW, however, shows very high Type‐I error rates with increasing autocorrelation. The corresponding rate of false trend detections is unacceptable for applications, so that published trends based on TFPW need to be reassessed.     

一种卫星钟自相关的实时钟差预报算法

针对实时精密单点定位(RT-PPP)中实时数据流存在中断、延迟等问题,该文构建了顾及卫星钟自相关的随机模型,提出了一种基于方差分量估计的自适应卡尔曼滤波钟差超短期/短期预报算法,评估了连续27d实测法国空间研究中心(CNES)实时数据流CLK93产品完整率和精度水平,利用哈达玛方差对比分析了该实时产品与德国地学研究中心(GFZ)事后GBM产品的频率稳定性。利用本文算法与传统卡尔曼算法对两类产品进行预报,结果显示:CLK93产品BDS系统(C)、GPS系统(G)、GLONASS系统(R)、Galileo系统(E)30s和1min预报精度分别平均提升了8.50%、8.44%、7.20%、6.96%;GBM产品相应4个系统12h和24h预报精度分别平均提升了3.14%、3.53%、0.96%、10.01%。