Elimination of Computational Systematic Errors and Improvements of Weather and Climate System Models in Relation to Baroclinic Primitive Equations

The design of a total energy conserving semi-implicit scheme for the multiple-level baroclinic primitive equation has remained an unsolved problem for a long time. In this work, however, we follow an energy perfect conserving semi-implicit scheme of a European Centre for Medium-Range Weather Forecasts (ECMWF) type sigma-coordinate primitive equation which has recently successfully formulated. Some real-data contrast tests between the model of the new conserving scheme and that of the ECMWF-type of global spectral semi-implicit scheme show that the RMS error of the averaged forecast Height at 850 hPa can be clearly improved after the first integral week. The reduction also reaches 50 percent by the 30th day. Further contrast tests demonstrate that the RMS error of the monthly mean height in the middle and lower troposphere also be largely reduced, and some well-known systematical defects can be greatly improved. More detailed analysis reveals that part of the positive contributions comes from improvements of the extra-long wave components. This indicates that a remarkable improvement of the model climate drift level can be achieved by the actual realizing of a conserving time-difference scheme, which thereby eliminates a corresponding computational systematic error source/sink found in the currently-used traditional type of weather and climate system models in relation to the baroclinic primitive equations.

Separation of systematic errors in processing high precision GPS baselines

The research is based on the double difference observations and semi-parametric model. Systematic errors are considered as the parameters to be estimated, and brought into the GPS observation equations. High precision baselines are obtained after separating systematic errors. The crucial steps are choosing regularizer and regularization parameters in processing GPS systematic errors by using the semi-parametric model. We propose a new regularizer and apply it to dealing with systematic errors. Also, we compare it with one proposed by other researchers. This comparison is done when all the regularization parameters equal to one. The computation result of the example shows that two regularizers correspond well and they can separate systematic errors successfully. Thus, we can get high precision baselines. Compared with R=QK-1Q′, our regularizer R=GTG is simple, so, the process of resolving the high precision baselines is relatively simple.

Penalized total least squares method for dealing with systematic errors in partial EIV model and its precision estimation

When the total least squares(TLS)solution is used to solve the parameters in the errors-in-variables(EIV)model,the obtained parameter estimations will be unreliable in the observations containing systematic errors.To solve this problem,we propose to add the nonparametric part(systematic errors)to the partial EIV model,and build the partial EIV model to weaken the influence of systematic errors.Then,having rewritten the model as a nonlinear model,we derive the formula of parameter estimations based on the penalized total least squares criterion.Furthermore,based on the second-order approximation method of precision estimation,we derive the second-order bias and covariance of parameter estimations and calculate the mean square error(MSE).Aiming at the selection of the smoothing factor,we propose to use the U curve method.The experiments show that the proposed method can mitigate the influence of systematic errors to a certain extent compared with the traditional method and get more reliable parameter estimations and its precision information,which validates the feasibility and effectiveness of the proposed method.

Track-to-Track Association Technique in Radar Network in the Presence of Systematic Errors

The presence of systematic measuring errors complicates track-to-track association, spatially separates the tracks that correspond to the same true target, and seriously decline the performances of traditional track-to-track association algorithms. Consequently, the influence of radar systematic errors on tracks from different radars, which is described as some rotation and translation, has been analyzed theoretically in this paper. In addition, a novel approach named alignment-correlation method is developed to estimate and reduce this effect, align and correlate tracks accurately without prior registration using phase correlation technique and statistic binary track correlation algorithm. Monte-Carlo simulation results illustrate that the proposed algorithm has good performance in solving the track-to-track association problem with systematic errors in radar network and could provide effective and reliable associated tracks for the next step of registration.

The Influence of Systematic Errors on the Asian Summer Monsoon Circulation

The systematic errors of wind field associated with the prediction of Asian summer monsoon and their impact on the monsoon circulation have been studied in this paper. The daily operational analyses and fore-casts (up to day-5) of the National Centre for Medium Range Weather Forecasting (NCMRWF), India, over the Asian summer monsoon domain for the period June, July and August of 1995 are made use for the purpose. The systematic errors associated with the low level flow delineate, reduction in the strength of trade winds leading to weakening of cross equatorial flow as well as westerly flow over Indian Ocean. The upper level errors connote weakening of Tibetan anticyclone and reduction in the strength of return flow into the Southern Hemisphere. Further, these errors evince growing tendency with increase in the forecast period. Apart from the general underestimation of kinetic energy budget terms, the model forecasts fail to represent the transient eddies. The forecasts show increasing trend in the conversion of eddy to mean kinetic energy. These errors enfeeble Asian summer monsoon circulation with increase in the forecast period. Key words Monsoon - Systematic errors - Kinetic energy budget The author is grateful to the NCMRWF for providing data and computing facilities to carry out the present study.

A Radiotherapy Treatment Margin Formula When Systematic Positioning Errors are Relatively Small Compared to Random Positioning Errors: A First-Order Approximation

A radiotherapy treatment margin formula has been analytically derived when a standard deviation (SD) of systematic positioning errors Ʃis relatively small compared to an SD of random positioning errors σ. The margin formula for 0 ≤ Ʃ≤ σwas calculated by linearly interpolating two boundaries at Ʃ= 0 and Ʃ= σ, assuming that the van Herk margin approximation of k1Ʃ+ k2σis valid at Ʃ= σ. It was shown that a margin formula for 0 ≤ Ʃ≤ σmay be approximated by k1σ+ k2Ʃ, leading to a more general form of k1 max(Ʃ,σ) + k2 min(Ʃ,σ) which is a piecewise linear approximation for any values of Ʃand σ.

STUDY OF THE EFFECTS OF REDUCING SYSTEMATIC ERRORS ON MONTHLY REGIONAL CLIMATE DYNAMICAL FORECAST

A nested-model system is constructed by embedding the regional climate model RegCM3 into a general circulation model for monthly-scale regional climate forecast over East China. The systematic errors are formulated for the region on the basis of 10-yr (1991-2000) results of the nested-model system, and of the datasets of the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) and the temperature analysis of the National Meteorological Center (NMC), U.S.A., which are then used for correcting the original forecast by the system for the period 2001-2005. After the assessment of the original and corrected forecasts for monthly precipitation and surface air temperature, it is found that the corrected forecast is apparently better than the original, suggesting that the approach can be applied for improving monthly-scale regional climate dynamical forecast.

Systematic error suppression scheme of the weak equivalence principle test by dual atom interferometers in space based on spectral correlation

Systematic error suppression and test data processing are very important in improving the accuracy and sensitivity of the atom interferometer(AI)-based weak-equivalence-principle(WEP) test in space. Here we present a spectrum correlation method to investigate the test data of the AI-based WEP test in space by analyzing the characteristics of systematic errors and noises. The power spectrum of the Eotvos coefficient η, systematic errors, and noises in AI-based WEP test in space are analyzed and calculated in detail. By using the method, the WEP violation signal is modulated from direct current(DC) frequency band to alternating current(AC) frequency band. We find that the signal can be effectively extracted and the influence of systematic errors can be greatly suppressed by analyzing the power spectrum of the test data when the spacecraft is in an inertial pointing mode. Furthermore, the relation between the Eotvos coefficient η and the number of measurements is obtained under certain simulated parameters. This method will be useful for both isotopic and nonisotopic AI-based WEP tests in space.

Autonomous relative optical navigation based on unified modeling of external systematic errors

To solve the problem that external systematic errors of the optical camera cannot be fully estimated due to limited computing resources,a unified dimensionality reduction representation method for the external systematic errors of the optical camera is proposed,and autonomous relative optical navigation is realized.The camera translational and misalignment errors are converted into a three-dimensional rotation error,whose differential model can be established through specific attitude control and appropriate assumption.Then,the rotation error and the relative motion state are jointly estimated in an augmented Kalman filter framework.Compared with the traditional method that estimates the camera translational and misalignment errors,the proposed method reduces the computational complexity in that the estimated state dimension is reduced.Furthermore,as demonstrated by numerical simulation,the estimation accuracy is improved significantly.

Systematic error real-time registration based onmodified input estimation

In order to estimate the systematic error in the processof maneuvering target adaptive tracking, a new method is proposed.The proposed method is a linear tracking scheme basedon a modified input estimation approach. A special augmentationin the state space model is considered, in which both the systematicerror and the unknown input vector are attached to thestate vector. Then, an augmented state model and a measurementmodel are established in the case of systematic error, andthe corresponding filter formulas are also given. In the proposedscheme, the original state, the acceleration and the systematicerror vector can be estimated simultaneously. This method can notonly solve the maneuvering target adaptive tracking problem in thecase of systematic error, but also give the system error value inreal time. Simulation results show that the proposed tracking algorithmoperates in both the non-maneuvering and the maneuveringmodes, and the original state, the acceleration and the systematicerror vector can be estimated simultaneously.

Reduction of Systematic Error in Radiopharmaceutical Activity by Entropy Based Mutual Information

The quality of the radiation dose depends upon the gamma count rate of the radionuclide used. Any reduction in error in the count rate is reflected in the reduction in error in the activity and consequently on the quality of dose. All the efforts so far have been directed only to minimize the random errors in count rate by repetition. In the absence of probability distribution for the systematic errors, we propose to minimize these errors by estimating the upper and lower limits by the technique of determinant in equalities developed by us. Using the algorithm we have developed based on the tech- nique of determinant inequalities and the concept of maximization of mutual information (MI), we show how to process element by element of the covariance matrix to minimize the correlated systematic errors in the count rate of 113 mIn. The element wise processing of covariance matrix is so unique by our technique that it gives experimentalists enough maneuverability to mitigate different factors causing systematic errors in the count rate and consequently the activity of 113 mIn.

SYSTEMATIC ERROR FROM Th/U RATIO IN LUMINESCENCE AND ESR DATING

In luminescence and ESR dating methods,total count rate from thick source alpha counting is commonly used fox estimating annual dose with assumption of equal activities for both uranium and thorium decay chains.This is equal to a Th/U weight ratio of 3.2.The systematic error in total dose rate due to uncertainty of the ratio is calculated.It is found that the error is insignificant for uniformly distributed samples such as sediment,but can be significant for some extreme circumstances.

Different Policies to Different Errors

Making of errors is an inevitable and indeed necessary part of the learning process.We should have positive attitude towards errors and the policies towards error correction should be flexible and adaptable.Teachers should have different policies towards different errors.For example,pre-systematic error should be tolerated.The immediate correction is ineffective.The systematic error should be corrected immediately,with the help of the teacher.And the teacher should encourage the student to discover and correct the post-systematic error by themselves.

飞行器轨迹的半参数估计方法

提出一种基于半参数建模的飞行器轨迹估计新方法,通过抑制不可参数建模的测量系统误差提高轨迹的估计精度。利用不等距节点B样条函数建立飞行器轨迹的参数模型,将轨迹参数模型代入测量模型中,并将测量模型中不可参数建模的系统误差表示为非参数,进而建立包含轨迹参数待估量和系统误差非参数待估量的半参数回归模型。采用轨迹参数估计和系统误差分离交替迭代的方式求解该半参数回归模型,利用非线性最小二乘法估计轨迹参数,通过小波分析从残差数据中分离系统误差。理论分析和仿真结果表明,半参数估计方法的轨迹估计精度优于忽略测量系统误差的参数估计方法。

粗差和系统误差显著性检验统计量统一推导新方法

基于均值平移模型的数据探测法和附加系统参数的平差法是目前处理粗差和系统误差的重要方法,其函数模型形式一致,故关于二者的显著性检验统计量理论上可做统一推导。不同于已有文献,文中提出一种统一推导的新方法。新方法的思路更符合数理统计中构造显著性检验统计量的一般思路,具有简洁且易于理解的特点。此外,新方法还具有较强的普适性,除参数平差外,需要时还可用于其他平差方法的粗差与系统误差显著性检验统计量推导。

伏安法测电阻的待测电阻选择方法

研究了伏安法测电阻的基于中学物理实验标配电表参量选择待测电阻的方法,结果表明:既要依据相对系统误差,又要依据匹配条件,综合选择待测电阻;给出了方法运用的实例,深化了伏安法测电阻的认识,奠定了精准设计实验教学的基础.

连续波核磁共振实验中外扫描测量法的改进

本文对连续波核磁共振实验中外扫描法测横向弛豫时间误差的主要来源进行了分析,对系统误差的大小进行了定量估算.在此基础上,对外扫描法中横向弛豫时间的测量提出了相应的改进措施,通过计算确定了共振信号半高宽测量时共振信号应在的位置.结果表明,外扫描法测量中,通过x方向的相位调节把共振信号移到偏离中心适当距离的位置上来测量其半高宽,可有效降低非线性扫描电压引起的系统误差.此外,通过对误差大小及共振信号测量位置的计算,能加深学生对横向弛豫时间及外扫描测量法原理的理解.

学术期刊评价中DEA方法的系统误差研究

[目的/意义]DEA分析在学术期刊评价中得到了广泛应用,但其系统误差问题却没有得到足够重视。因此,深入研究该问题的根源及其解决策略,可以更为精确地揭示学术期刊的真实水平。[方法/过程]本文将系统误差理论引入到DEA分析中,在理论分析的基础上,对学术期刊评价中DEA方法的系统误差的产生机制及其影响进行深度探究,并在此基础上提出有效预防和消减系统误差的方法。[结果/结论]研究发现,我国DEA学术期刊评价仍处于探索阶段,学术期刊评价中DEA方法的系统误差的产生原因包括评价目的确定的系统误差、投入产出变量选取的系统误差、评价方法适用性系统误差、模型设定误差与结果公布系统误差,评价指标选取与方法选择是学术期刊评价中DEA方法的系统误差产生的主要原因,并提出了预防和消除学术期刊DEA效率分析系统误差的解决方案:认真选择学术期刊效率评价投入产出指标,保证评价对象数量达到一定规模,结合评价目的选择评价方法,不宜滥用复杂的DEA模型,采用专家赋权法设定权重。科技评价效率分析同样存在系统误差问题,需因地制宜进行处理,对于具有公共物品属性的学术评价应适度采用DEA方法。

单/双站辅助的干涉仪标校与选站方法

传统的固定基线干涉仪多误差联合标校方法需要三个以上的标校站才能实现干涉仪的在轨实时标校,但是在标校站数量不足时传统方法性能将降低甚至失效。针对标校站数量不足的情况,本文提出一种固定基线干涉仪单/双站标校算法。在干涉仪与标校站之间存在相对运动的条件下,首先通过多次测量获得一组标校信号相位差,其次利用所得相位差列出关于干涉仪各项系统误差的方程组,最后使用Penrose逆矩阵辅助的迭代最小二乘法求解出各项系统误差值。仿真结果验证了所提算法的可行性。在此基础上,针对标校站选址对标校后干涉仪定位性能影响的问题,分解标校站选址的各项指标,通过数值仿真的方式,定性分析了标校站选址的各个参数对干涉仪定位精度的影响。分析结果表明,单站情况下位于星下点附近的标校站或双站情况下相距较远的两个标校站均能让标校后的干涉仪获得更优的定位性能。

基于EEMD与曲面重构的自由曲面加工误差分解与补偿

为了减小自由曲面零件的加工误差和提高加工精度,提出了集合经验模态分解(Ensemble Empirical Mode Decomposition, EEMD)与曲面重构结合对加工误差进行分解和补偿的方法。利用EEMD对在机检测得到的第一次切削加工后的加工误差进行分解,得到若干固有模态函数(Intrinsic Mode Functions, IMFs);根据系统误差特征,通过设置相关系数阈值筛选出加工误差中含有系统误差的IMFs分量(即分解出的系统误差);根据该系统误差,利用曲面重构法得到新的加工曲面,并生成新的NC代码,再次进行切削加工,对系统误差进行补偿。通过EEMD加工误差分解仿真分析可以得出,EEMD具有较为理想的加工误差分解能力。自由曲面零件加工实例结果显示,采用本文提出的方法对加工误差进行补偿后的最大绝对加工误差由0.0632mm降为0.0139mm,平均绝对加工误差由0.0491mm降为0.0052mm,加工精度提高了89.4%,证明了该方法在自由曲面零件加工误差补偿方面的有效性。