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1.
Part 1's localization method, Ensemble COrrelations Raised to A Power (ECO-RAP), is incorporated into a Local Ensemble Transform Kalman Filter (LETKF). Because brute force incorporation would be too expensive, we demonstrate a factorization property for Part 1's Covariances Adaptively Localized with ECO-rap (CALECO) forecast error covariance matrix that, together with other simplifications, reduces the cost. The property inexpensively provides a large CALECO ensemble whose covariance is the CALECO matrix. Each member of the CALECO ensemble is an element-wise product between one raw ensemble member and one column of the square root of the ECO-RAP matrix. The LETKF is applied to the CALECO ensemble rather than the raw ensemble. The approach enables the update of large numbers of variables within each observation volume at little additional computational cost. Under plausible assumptions, this makes the CALECO and standard LETKF costs similar. The CALECO LETKF does not require artificial observation error inflation or vertically confined observation volumes both of which confound the assimilation of non-local observations such as satellite observations. Using a 27 member ensemble from a global Numerical Weather Prediction (NWP) system, we depict four-dimensional (4-D) flow-adaptive error covariance localization and test the ability of the CALECO LETKF to reduce analysis error. 相似文献
2.
传统的四维变分数据同化方法在同化观测资料的同时可以对数值模式参数进行优化,然而传统的四维变分方法需要针对不同的数值模式编写特有的伴随模式,因此算法的可移植性差,同时计算时耗费大量资源。本文提出了一种新的基于解析四维集合变分的参数优化方法,该方法以迭代搜索得到的模式参数为基准展开扰动并构建样本集合,由此显式地计算协方差矩阵,并得到代价函数极小值的解析解,从而避免了伴随模式的使用。基于Lorenz-63模型对该方法进行单参数和多参数数值试验和优化效果检验,并在不同的同化时间窗口长度和观测采样间隔情况下,采用传统四维变分方法与之进行对比,结果显示,新方法表现出与传统四维变分相同的优化性能,都能有效收敛到真值,而新方法不需要计算伴随模式,可移植性好。本文还测试了不同的集合成员个数和模式参数真值的情况下新方法的同化效果,结果表明,新方法对集合样本个数及模型参数真值不敏感,采用较少的集合样本即可完成数据同化。 相似文献
3.
An ensemble Kalman filter (EnKF) is used to assimilate data onto a non-linear chaotic model, coupling two kinds of variables. The first kind of variables of the system is characterized as large amplitude, slow, large scale, distributed in eight equally spaced locations around a circle. The second kind of variables are small amplitude, fast, and short scale, distributed in 256 equally spaced locations. Synthetic observations are obtained from the model and the observational error is proportional to their respective amplitudes. The performance of the EnKF is affected by differences in the spatial correlation scales of the variables being assimilated. This method allows the simultaneous assimilation of all the variables. The ensemble filter also allows assimilating only the large-scale variables, letting the small-scale variables to freely evolve. Assimilation of the large-scale variables together with a few small-scale variables significantly degrades the filter. These results are explained by the spurious correlations that arise from the sampled ensemble covariances. An alternative approach is to combine two different initialization techniques for the slow and fast variables. Here, the fast variables are initialized by restraining the evolution of the ensemble members, using a Newtonian relaxation toward the observed fast variables. Then, the usual ensemble analysis is used to assimilate the large-scale observations. 相似文献
4.
The article proposes parallel implementation of the Ensemble Optimal Interpolation (EnOI) data assimilation (DA) method in eddy-resolving World Ocean circulation model. The results of DA experiments in North Atlantic with ARGO drifters are compared with the multivariate optimal interpolation (MVOI) DA scheme. The sensitivity of the model error, i.e., the difference between the model and observations depending on the number of ensemble elements, is also assessed and presented. The effectiveness of this method over the MVOI scheme is confirmed. The model outputs with and without assimilation are also compared with independent sea surface temperature data from ARMOR 3d. 相似文献
5.
State-of-the-art process-based models have shown to be applicable to the simulation and prediction of coastal morphodynamics. On annual to decadal temporal scales, these models may show limitations in reproducing complex natural morphological evolution patterns, such as the movement of bars and tidal channels, e.g. the observed decadal migration of the Medem Channel in the Elbe Estuary, German Bight. Here a morphodynamic model is shown to simulate the hydrodynamics and sediment budgets of the domain to some extent, but fails to adequately reproduce the pronounced channel migration, due to the insufficient implementation of bank erosion processes. In order to allow for long-term simulations of the domain, a nudging method has been introduced to update the model-predicted bathymetries with observations. The model-predicted bathymetry is nudged towards true states in annual time steps. Sensitivity analysis of a user-defined correlation length scale, for the definition of the background error covariance matrix during the nudging procedure, suggests that the optimal error correlation length is similar to the grid cell size, here 80–90 m. Additionally, spatially heterogeneous correlation lengths produce more realistic channel depths than do spatially homogeneous correlation lengths. Consecutive application of the nudging method compensates for the (stand-alone) model prediction errors and corrects the channel migration pattern, with a Brier skill score of 0.78. The proposed nudging method in this study serves as an analytical approach to update model predictions towards a predefined ‘true’ state for the spatiotemporal interpolation of incomplete morphological data in long-term simulations. 相似文献
6.
The spatial correlation length (SCL), or the scale of fluctuation, is a parameter for describing the spatial variability of soil and one of the important parameters used in random field theory. Studies reporting the spatial correlation length based on real field data of offshore/nearshore sea bottom soils are rather limited in the literature, so in this study, the vertical spatial correlation length is determined using site investigation data from two sites of the southern coast of Turkey. Based on quite extensive data, the vertical spatial correlation length is estimated using four different autocovariance functions. The values are within typical ranges reported in the literature for similar soil groups, both onshore and offshore. It is also noted that the widely-used exponential function almost always gives the lowest value of spatial correlation length. The results of this study add to the database of spatial correlation lengths based on real data and could be useful for future studies on reliability assessment of offshore foundations using random finite element method. 相似文献
7.
Temporal evolution of innovation and residual statistics in the ECMWF variational data assimilation systems 总被引：1，自引：0，他引：1
HEIKKI JÄRVINEN 《地球，A辑:动力气象学与海洋学》2001,53(3):333-347
The temporal evolution of innovation and residual statistics of the ECMWF 3D‐ and 4D‐Var data assimilation systems have been studied. First, the observational method is applied on an hourly basis to the innovation sequences in order to partition the perceived forecast error covariance into contributions from observation and background errors. The 4D‐Var background turns out to be ignificantly more accurate than the background in the 3D‐Var. The estimated forecast error variance associated with the 4D‐Var background trajectory increases over the assimilation window. There is also a marked broadening of the horizontal error covariance length scale over the assimilation window. Second, the standard deviation of the residuals, i.e., the fit of observations to the analysis is studied on an hourly basis over the assimilation window. This fit should, in theory, reveal the effect of model error in a strong constraint variational problem. A weakly convex curve is found for this fit implying that the perfect model assumption of 4D‐Var may be violated with as short an assimilation window as six hours. For improving the optimality of variational data assimilation systems, a sequence of retunes are needed, until the specified and diagnosed error covariances agree. 相似文献
8.
The isotropic correlations of forecast errors in the HIRLAM system are investigated for different horizontal grid sizes in order to achieve an improved representation of the structure functions for high-resolution surface analysis. The investigation is performed for 2 metre temperature and relative humidity and makes use of operational forecasts from DMI-HIRLAM at the Danish Meteorological Institute (DMI), which can support the background for a surface analysis in three different horizontal resolutions. Two different well-known methods for determining isotropic forecast error correlations are applied. The first method compares forecasts to observations (the Observation Method), while the second makes use of two different forecasts valid for the same time (the NMC Method). The latter method is also used to investigate isotropy as well as the influence of land–sea contrast and orography. A comparison of the two mentioned methods reveals a good correspondence between them, and the investigation of monthly changes shows some seasonal tendencies. The isotropy assumption is shown to be acceptable to a first approximation, despite a slight dependency on the predominant flow. The results further suggest a decrease in the background error correlation scales when going to higher horizontal resolution in the forecast model. 相似文献
9.
在集合数据同化中,协方差局地化（covariance localization,CL）方法的使用存在限制。集合转换卡尔曼滤波（ensemble transform Kalman filter,ETKF）作为集合平方根滤波的变种方法,是一种应用较广、计算高效的数据同化方法。本文分析了CL方法应用于ETKF方法的困难,从而改进CL方法使其可以适用于ETKF方法。另外,结合浅水方程,利用Askey函数作为多元局地化函数,提出了一种适用于多元数值模型的CL方法。通过具体实验验证,得到了较好的分析结果。 相似文献
10.
High-resolution models can reproduce mesoscale dynamics and the variability in the Gulf of Mexico (GOM), but cannot provide accurate locations of currents without data assimilation (DA). We use the computationally cheap Ensemble Optimal Interpolation (EnOI) in conjunction with the Hybrid Coordinate Ocean Model (HYCOM) model for assimilating altimetry data. The covariance matrix extracted from a historical ensemble, is three-dimensional and multivariate. This study shows that the multivariate correlations with sea level anomaly are coherent with the known dynamics of the area at two locations: the central part of the GOM and the upper slope of the northern shelf. The correlations in the first location are suitable for an eddy forecasting system, but the correlations in the second location show some limitations due to seasonal variability. The multivariate relationships between variables are reasonably linear, as assumed by the EnOI. Our DA set-up produces little noise that is dampened within 2 d, when the model is pulled strongly towards observations. Part of it is caused by density perturbations in the isopycnal layers, or artificial caballing. The DA system is demonstrated for a realistic case of Loop Current eddy shedding, namely Eddy Yankee. 相似文献
11.
12.
随机抽取100只同龄疣荔枝螺(Thais clavigera Kuster),开展其形态性状与体质量和软体部质量的相关与通径分析。实验选取并测量了壳长(X1)、壳宽(X2)、壳厚(X3)、壳口长(X4)和壳口宽(X5)等5项形态性状以及体质量(Y)和软体部质量(Z)等2项质量性状,运用相关分析、通径分析和多元回归分析等方法分析了各形态性状对体质量和软体部质量的影响。相关分析表明,疣荔枝螺各项性状间的相关均呈极显著(P<0.01)。通径分析表明,形态性状对体质量直接影响大小的顺序为壳长(0.459)>壳宽(0.277)>壳厚(0.209)>壳口宽(0.140);壳长对体质量的直接决定系数最大(0.220),是影响体质量的主要因素。通过多元回归分析,建立了形态性状对体质量的回归方程:Y=-9.714+0.220X1+0.204X2+0.195X3+0.151X5。 相似文献
13.
Yukio Fujinawa 《Journal of Oceanography》1974,30(1):10-22
A method is proposed to estimate the true directional spectrum of wind waves by making use of more than four wave detectors. The true spectrum of wind waves whose wave lengths lie between about 1.1 and 2.6 times the largest span between the wave gauges can be recovered with an error less than 0.5 %. An additional wave gauge with fixed maximum span extends its effectivity to shorter wave lengths, but does not effect the upper limit of wave length.The method is based on the fact that the spectrum estimated byBarber (1961) is connected with true directional spectrum by the Fredholm integral equation of the first kind if the wave component satisfies the dispersion relation. Solving the equation by using the Fourier series method, we can get true spectrum. 相似文献
14.
气候模式是我们理解、模拟和预报气候演变的重要工具。然而即使是目前最先进的耦合模式,其模拟和预报与大气/海洋的真实状态相比,仍存在较大偏差,这是由于在模式的倾向方程中不可避免地存在系统性的误差(倾向误差)。因此,减小模式倾向误差对改进模式的模拟和预报效果具有重要意义。该研究首先发展了一种新的计算模式倾向误差的估计算法——基于局地集合变换卡尔曼滤波器(local ensemble transform kalman filter, LETKF)同化技术的倾向误差估计算法。在此基础上,将新发展的算法应用到Zebiak-Cane (ZC)模式,通过同化海表面温度异常(sea surface temperature anomaly, SSTA)数据,估计随时空变化的倾向误差,并使用计算得到的倾向误差订正模式,进行积分模拟。结果表明: (1)倾向误差和ZC模式的模拟偏差具有高度相关性; (2)订正后的模式改善了对厄尔尼诺-南方涛动(El Niño-Southern Oscillation, ENSO)的一些重要特征的模拟。这说明新发展的模式倾向误差估计算法十分有效且在ENSO模拟中具有较好的应用价值,此外,这种新的模式倾向误差估计算法,计算高效简便,可便捷地应用于各模式中,利于推广。 相似文献
15.
In order to reconstruct the large-scale temperature and salinity fields by the method of optimal interpolation of the archival
data, we compute the correlation functions and analyze the space and time variations of the statistical structure of the fields.
On the sea surface, the thermohaline fields are spatially inhomogeneous. Thus, the correlation functions are anisotropic in
the region of the northwest shelf and close to isotropic in the inner parts of the sea. The values of correlation length vary
from season to season. In the layer of pycnocline, the temperature and salinity fields are anisotropic. In the zonal direction,
the correlation length is 2–3 times greater than in the meridional direction. The indicated anisotropy becomes stronger in
the winter season and weaker in the summer season as a consequence of the seasonal variability of large-scale circulation.
We study the dependence of the error of reconstruction of the fields by the method of optimal interpolation on the form of
approximation of the correlation functions with regard for anisotropy.
__________
Translated from Morskoi Gidrofizicheskii Zhurnal, No. 1, pp. 51–65, January–February, 2008. 相似文献
16.
基于ROMS模式利用集合最优插值同化沿轨海表面高度异常数据的研究 总被引：2，自引：1，他引：1
The ensemble optimal interpolation （EnOI） is applied to the regional ocean modeling system （ROMS） with the ability to assimilate the along-track sea level anomaly （TSLA）. This system is tested with an eddy-resolving system of the South China Sea （SCS）. Background errors are derived from a running seasonal ensemble to account for the seasonal variability within the SCS. A fifth-order localization function with a 250 km localization radius is chosen to reduce the negative effects of sampling errors. The data assimilation system is tested from January 2004 to December 2006. The results show that the root mean square deviation （RMSD） of the sea level anomaly decreased from 10.57 to 6.70 cm, which represents a 36.6% reduction of error. The data assimilation reduces error for temperature within the upper 800 m and for salinity within the upper 200 m, although error degrades slightly at deeper depths. Surface currents are in better agreement with trajectories of surface drifters after data assimilation. The variance of sea level improves significantly in terms of both the amplitude and position of the strong and weak variance regions after assimilating TSLA. Results with AGE error （AGE） perform better than no AGE error （NoAGE） when considering the improvements of the temperature and the salinity. Furthermore, reasons for the extremely strong variability in the northern SCS in high resolution models are investigated. The results demonstrate that the strong variability of sea level in the high resolution model is caused by an extremely strong Kuroshio intrusion. Therefore, it is demonstrated that it is necessary to assimilate the TSLA in order to better simulate the SCS with high resolution models. 相似文献
17.
Surface currents measured by high frequency （HF） radar arrays are assimilated into a regional ocean model over Qingdao coastal waters based on Kalman filter method. A series of numerical experiments are per- formed to evaluate the performance of the data assimilation schemes. In order to optimize the analysis pro- cedure in the traditional ensemble Kalman filter （ENKF）, a different analysis scheme called quasiensemble Kaman filter （QENKF） is proposed. The comparisons between the ENKF and the QENKF suggest that both them can improve the simulated error and the spatial structure. The estimations of the background error covariance （BEC） are also assessed by comparing three different methods： Monte Carlo method; Canadian quick covariance （CQC） method and data uncertainty engine （DUE） method. A significant reduction of the root-mean-square （RMS） errors between model results and the observations shows that the CQC method is able to better reproduce the error statistics for this coastal ocean model and the corresponding external forcing. In addition, the sensibility of the data assimilation system to the ensemble size is also analyzed by means of different scales of the ensemble size used in the experiments. It is found that given the balance of the computational cost and the forecasting accuracy, the ensemble size of 50 will be an appropriate choice in the Qingdao coastal waters. 相似文献
18.
Using a mesoscale ensemble to predict forecast error and perform targeted observation 总被引：2，自引：0，他引：2
Using NCEP short range ensemble forecast（SREF） system,demonstrated two fundamental on-going evolutions in numerical weather prediction（NWP） are through ensemble methodology.One evolution is the shift from traditional single-value deterministic forecast to flow-dependent（not statistical） probabilistic forecast to address forecast uncertainty.Another is from a one-way observation-prediction system shifting to an interactive two-way observation-prediction system to increase predictability of a weather system.In the first part,how ensemble spread from NCEP SREF predicting ensemble-mean forecast error was evaluated over a period of about a month.The result shows that the current capability of predicting forecast error by the 21-member NCEP SREF has reached to a similar or even higher level than that of current state-of-the-art NWP models in predicting precipitation,e.g.,the spatial correlation between ensemble spread and absolute forecast error has reached 0.5 or higher at 87 h（3.5 d） lead time on average for some meteorological variables.This demonstrates that the current operational ensemble system has already had preliminary capability of predicting the forecast error with usable skill,which is a remarkable achievement as of today.Given the good spread-skill relation,the probability derived from the ensemble was also statistically reliable,which is the most important feature a useful probabilistic forecast should have.The second part of this research tested an ensemble-based interactive targeting（E-BIT） method.Unlike other mathematically-calculated objective approaches,this method is subjective or human interactive based on information from an ensemble of forecasts.A numerical simulation study was performed to eight real atmospheric cases with a 10-member,bred vector-based mesoscale ensemble using the NCEP regional spectral model（RSM,a sub-component of NCEP SREF） to prove the concept of this E-BIT method.The method seems to work most effective for basic atmospheric state variables,moderately effective for convective instabilities and least effective for precipitations.Precipitation is a complex result of many factors and,therefore,a more challenging field to be improved by targeted observation. 相似文献
19.
选取北部湾340尾野生日本囊对虾,对其体长、头胸甲长、胸高、胸宽、第一腹节宽、第一腹节高、第三腹节高、额剑上刺数、额剑下刺数和体重等10个性状进行测量.采用逐步回归法分 析体重和形态形状的关系.结果表明,日本囊对虾的体长、头胸甲长、胸宽、胸高、第一腹节宽、第三腹节高和额剑上刺数7个性状与体重的相关系数达到了极显著水平(P<0.01),在上述7个性状中,胸宽对体重的直接影响(0.352)最大,其次为头胸甲长、体长、第一腹节宽、第三腹节高和胸高,额剑上刺数影响较小.单独的决定系数:胸宽对体重的决定系数(12.39%)最大,其次是头胸甲长,额剑上刺数最小.共同决定系数:胸宽与头胸甲长最大为11.54%.通过分析,建立上述7个性状对体重的最优多元回归方程.为日本囊对虾在选育种提供理想的测度指标. 相似文献
20.
中国近海现场海洋观测系统设计评估 总被引：1，自引：0，他引：1
中国科学院正在发展一个在中国近海(包括黄海、东海和南海)现场海洋观测系统。观测系统包括3个沿岸观测站点、4个近海离岸浮标和由观测船只按固定航线做的船舶观测断面。观测站点、浮标和断面的位置已经预先确定,这个计划在2008-2011实施。利用基于卡尔曼理论的样本集合方法对这样一个能够监测大尺度的季节和年季变率的观测系统设计进行了评估。根据卡尔曼滤波理论,用集合样本的方法能够给出经过同化这个观测系统位置的观测资料后能够减少多少分析误差和分析场的不确定性。用2个来自不同模式、不同分辨率的模式的结果作为集合样本来计算静态的背景误差协方差,这2套样本分别是来自分辨率是0.5°×0.5°的模式同化结果和高分辨0.125°×0.125°的模式结果。由这2个不同资料得到的结果是一致的。发现来自3个近岸和4个离岸浮标得到的观测能够有效地减少SST在渤海、黄海、东海和南海中部的分析误差。然而在越南东部和台湾东部海域,分析误差减少的百分比相对要小。最后,给出了中国近海最优的观测位置序列设计。 相似文献