气候变化和人类活动对中国东部季风区水循环影响的检测和归因

水文循环过程受气候变化与人类活动的共同作用,区分气候内部自然变率与人类活动作用于水循环贡献对于增加气候变化的理解非常重要。本研究利用近期发展的考虑地下水取用水与灌溉影响的全球陆气耦合模式进行数值模拟,基于最优指纹法分析探讨中国东部季风区黄河、淮河、海河、珠江、长江、松花江流域水循环变化(地表温度、降水、径流、蒸散发)及归因。结果表明:大部分流域的地表温度年际变化在1965~2005年间检测到包括温室气体气溶胶人为排放、臭氧与土地利用变化产生的外强迫效应,显示在长期对于地表温度起主要作用的可能为上述强迫;1965~2005年降水年际变化仅在淮河及长江下游检测到上述强迫效应,且在长江下游效应占主导。在1965~1984年间,地表温度的年际变化在海河流域检测到由于地下水取水灌溉产生的外强迫效应,并且该效应占主导。在1982~2005年径流年际变化中,在淮河、长江下游及黄河下游处检测到了由于温室气体排放、气溶胶人为排放、臭氧变化及土地利用变化等产生的外强迫效应但无法有效分离,显示该信号在这些地区可能不为主导效应;1982~2005年间的蒸散发年际变化在珠江、长江下游同样检测到了上述强迫效应,并且该效应在长江下游占主导效应。     

数值天气预报和气候预测可预报性研究的若干动力学方法

简要回顾了数值天气预报和气候预测可预报性研究的若干动力学方法,包括用于研究第一类可预报性问题的线性奇异向量（LSV）和条件非线性最优初始扰动（CNOP-I）方法,以及Lyapunov指数和非线性局部Lyapunov指数方法。前两种方法用于研究预报或预测的预报误差问题,可以用于估计天气预报和气候预测的最大预报误差,而且根据导致最大预报误差的初始误差结构的信息,这两种方法可以用于确定预报或预测的初值敏感区。应该指出的是,LSV是基于线性化模式,对于描述非线性大气和海洋的运动具有局限性。因而,对于非线性模式,应该选择使用CNOP-I估计最大预报误差。Lyapunov指数和非线性局部Lyapunov指数可以用于研究第一类可预报性问题中的预报时限问题,前者是基于线性模式,不能解释非线性对预报时限的影响,而非线性局部Lyapunov指数方法则考虑了非线性的影响,能够较好地估计实际天气和气候的预报时限。第二类可预报性问题的研究方法相对较少,本文仅介绍了由我国科学家提出的关于模式参数扰动的条件非线性最优参数扰动（CNOP-P）方法,该方法可以用于寻找到对预报有最大影响的参数扰动,并可以进一步确定哪些参数最应该利用观测资料进行校准。另一方面,通过对比CNOP-I和CNOP-P对预报误差的影响,可以判断导致预报不确定性的主要误差因子,进而指导人们着力改进模式或者初始场。     

全球海洋资料同化系统ZFL_GODAS的研制和初步评估试验

本研究发展了一个全球海洋资料同化系统ZFL_GODAS。该系统是一个短期气候数值预测业务系统的子系统,为短期气候预测海气耦合模式提供全球海洋初始场。系统能够同化的观测资料包括卫星高度计资料、卫星海表温度(SST)资料,以及Argo、XBT、TAO等各种不同来源的现场温盐廓线资料。系统使用的海洋模式为中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室开发的气候系统海洋模式LICOM1.0,同化方案为集合最优插值(EnOI)方案。系统使用一个由海洋模式自由积分得到的静态样本来估计背景场误差协方差。这样的基于集合样本的背景场误差协方差具有多变量协变、各向异性的特征,且能反映海洋物理过程固有的空间尺度特征。针对EnOI同化程序的特点,开发了一套特色鲜明、负载均衡、高效的并行化同化程序。本文通过与不同类型观测资料的比较,对同化系统的性能进行了评估。通过比较海表温度和海面高度的年际变率,海表温度异常随时间的变化,SST、海面高度异常(SLA)以及次表层温盐预报产品的均方根误差,5年平均温度偏差廓线、平均盐度廓线、平均纬向流速廓线等发现:系统工作正常、同化效果较好;经过同化以后,各变量都更加接近观测,误差更小,与观测场的相关性更好,可以为短期气候预测系统提供较好的海洋初始场,也可以为物理海洋学的研究提供有效的再分析资料。     

Adaptation of the optimal fingerprint method for climate change detection using a well-conditioned covariance matrix estimate

The “optimal fingerprint” method, usually used for detection and attribution studies, requires to know, or, in practice, to estimate the covariance matrix of the internal climate variability. In this work, a new adaptation of the “optimal fingerprints” method is presented. The main goal is to allow the use of a covariance matrix estimate based on an observation dataset in which the number of years used for covariance estimation is close to the number of observed time series. Our adaptation is based on the use of a regularized estimate of the covariance matrix, that is well-conditioned, and asymptotically more precise, in the sense of the mean square error. This method is shown to be more powerful than the basic “guess pattern fingerprint”, and than the classical use of a pseudo-inverted truncation of the empirical covariance matrix. The construction of the detection test is achieved by using a bootstrap technique particularly well-suited to estimate the internal climate variability in real world observations. In order to validate the efficiency of the detection algorithm with climate data, the methodology presented here is first applied with pseudo-observations derived from transient regional climate change scenarios covering the 1960–2099 period. It is then used to perform a formal detection study of climate change over France, analyzing homogenized observed temperature series from 1900 to 2006. In this case, the estimation of the covariance matrix is only based on a part of the observation dataset. This new approach allows the confirmation and extension of previous results regarding the detection of an anthropogenic climate change signal over the country.     

地下水动态观测网优化设计研究

本文采用状态空间分析法,通过对地下水流系统输入变量、输出变量及地下水动态测量值的研究,提出了地下水流系统确定一随机性数值模型。运用该模型的模拟解,进行地下水动态观测网优化设计。该方法把地下水动态观测网密度、位置及观测频率优化与地下水流系统结合起来研究。为了克服该模型计算量大的缺陷,本文提出了一种改进算法,使这一观测网优化方法适于在微机上实现,减少了计算工作量。该方法曾用于陕西某地区地下水位动态观测网的优化设计,取得了显著经济效益。     

有序样品聚类的最优分割应用程序开发

在地层划分、蚀变、矿化、圈定矿体的研究中，有序样品聚类的最优分割法——数学处理方法是一个十分有效的方法，而该方法的数据处理是一个复杂而繁琐的过程。为了有志于地质研究的爱好者，根据最优分割的数学处理原理，将最优分割法编制成易于为非计算机专业人员所利用的处理软件，并免费共享。该程序使用方便，操作简单，只要按文中说明加以编辑，即可投入使用。     

Minimum conformal mapping distortion according to Chebyshev’s principle: a case study over peninsular Spain

Defining the distortion of a conformal map projection as the oscillation of the logarithm of its infinitesimal-scale σ, Chebyshev’s principle states that the best (minimum distortion) conformal map projection over a given region Ω of the ellipsoid is characterized by the property that σ is constant on the boundary of that region. Starting from a first map of Ω, we show how to compute the distortion δ₀(Ω) of this Chebyshev’s projection. We prove that this minimum possible conformal mapping distortion associated with Ω coincides with the absolute value of the minimum of the solution of a Dirichlet boundary-value problem for an elliptic partial differential equation in divergence form and with homogeneous boundary condition. If the first map is conformal, the partial differential equation becomes a Poisson equation for the Laplace operator. As an example, we compute the minimum conformal distortion associated with peninsular Spain. Using longitude and isometric latitude as coordinates, we solve the corresponding boundary-value problem with the finite element method, obtaining δ₀(Ω)=0.74869×10⁻³. We also quantify the distortions δ_l and δ_utm of the best conformal conic and UTM (zone 30) projections over peninsular Spain respectively. We get δ_l=2.30202×10⁻³ and δ_utm=3.33784×10⁻³.     

An Optimal Adaptive Kalman Filter

In a robustly adaptive Kalman filter, the key problem is to construct an adaptive factor to balance the contributions of the kinematic model information and the measurements on the state vector estimates, and the corresponding learning statistic for identifying the kinematic model biases. What we pursue in this paper are some optimal adaptive factors under the particular conditions that the state vector can or cannot be estimated by measurements. Two optimal adaptive factors are derived, one of which is deduced by requiring that the estimated covariance matrix of the predicted residual vector equals the corresponding theoretical one. The other is obtained by requiring that the estimated covariance matrix of the predicted state vector equals its theoretical one. The two related optimal adaptive factors are given. These are analyzed and compared in theory and in an actual example. This shows, through the actual computations, that the filtering results obtained by optimal adaptive factors are superior to those obtained by adaptive factors based on experience.     

Optimal design of a regional seismological network for the Arab countries

The Arab countries cover a large portion of the African and Arabian plates, a region characterized by seismic activity along complex continental collision zones, active seafloor spreading, rifting, and intraplate earthquakes. Establishing a standardized regional seismic network in these countries, then, is of great importance. Considerable effort of some Arab countries and UNESCO under project PAMERAR is under way to achieve this goal. A design for the spatial distribution of a regional seismic network in the area, based on a D-optimal planning criterion, is proposed in this paper. The method, which involves optimizing the geographical locations of stations, is based on the probability of earthquake occurrence at a given point in the seismic region, travel times of seismic waves, and minimization of the ellipsoid volume of earthquake location errors.     

汾渭地震带及晋陕豫交界区的地震活动分期

本文应用“最优分割法”,分别对汾渭地震带及晋陕豫交界区的地震活动进行了分期,并对结果进行了讨论。