The study of single station inverting the sea surface current by HF ground wave radar based on adjoint assimilation technology

This paper introduces the assimilation technology in an ocean dynamics model and discusses the feasibility of inverting the sea surface current in the detection zone by assimilating the sea current radial velocity detected by single station HF ground wave radar in ocean dynamics model. Based on the adjoint assimilation and POM model, the paper successfully inverts the sea surface current through single station HF ground wave radar in the Zhoushan sea area. The single station HF radar inversion results are also compared with the bistatic HF radar composite results and the fixed point measured results by Annderaa current meter. The error analysis shows that acquisition of flow velocity and flow direction data from the single station HF radar based on adjoint assimilation and POM model is viable and the data obtained have a high correlation and consistency with the flow field observed by HF radar.     

顾及DEM误差空间自相关的地形变化检测方法

传统的地形变化检测方法忽略了DEM误差的空间自相关性,针对此问题,本文提出了顾及DEM误差空间自相关的地形变化检测方法。首先,通过2期DEM相减得到差值DEM（DoD）,并通过蒙特卡罗方法评估DEM的误差空间分布;其次,基于DEM误差空间分布图,通过误差传播公式计算DoD误差,并使用半变异函数分析其空间自相关程度;最后,在误差空间自相关分析和显著性检测的基础上计算地形变化量（体积）和对应的误差限。本文在4个黄土小流域进行了实验,结果表明：无人机摄影测量DEM的高程误差存在一定程度的空间自相关,通过光束平差蒙特卡罗方法可以模拟无人机摄影测量DEM的误差空间分布;在进行地形变化检测时,使用误差空间分布代替中误差进行地形变化检测有效降低了检测结果对显著性阈值的敏感性;显著性阈值从68%提高到95%时,使用误差空间分布的检测结果损失的观测值比使用中误差低5.39%~6.75%。顾及空间自相关的地形变化检测方法能够更加科学、精确地量化地形变化特征,也可有效地应用于地表变形监测、流域侵蚀监测、输沙量评估等领域。     

一种新的基于模糊分析观测信息的局地化方法

地球表层系统是一个极其复杂的巨系统,为了更精确地表达地球表层系统各种过程的动态演进,解决数据同化系统观测误差的估计与处理已经成为地球科学领域备受关注的问题之一。在地球科学系统数值模拟中,一般采用集合数据同化来探讨地学变量预报时的各种误差。集合类卡尔曼滤波通常会由于集合数过小而带来欠采样、协方差低估、滤波发散和远距离虚假相关等问题。针对背景误差协方差被低估问题,局地分析方法（Local Analysis, LA）在一定程度上能起到抑制作用,但无法彻底解决背景误差协方差的虚假相关问题。因此,本文在集合卡尔曼滤波的算法框架下提出了一种与模糊逻辑控制算法相耦合的局地化分析方法（Fuzzy Analysis, FA）。在强非线性Lorenz-96模型中,对不同模型误差下的LA和FA方法进行了性能优劣方面的探讨,并比较分析了2种方法在集合数、观测数和观测位置、放大因子以及强迫参数变化时的同化性能。实验采用均方根误差作为算法评判依据,同时用功率谱密度（Power Spectral Density, PSD）更直接地对2种算法性能优劣作出了评价。结果表明：在完美模型下,FA相对于LA降低了17.5%的均方根误差（Root Mean Square Error, RMSE）;随着模型误差增大,RMSE减小的百分比和减小幅度都在降低;在严重模型误差下,FA降低了8.6%的RMSE。总体而言,新算法FA的有效性和鲁棒性都得到了验证,并且在EnKF同化基础下有效改进了传统的局地化分析方案,优化了观测误差处理,为今后的数据同化研究提供了一个较为全面的观测误差研究平台。     

A New Multigrid 3D-VAR Optimization Method for Bottom Friction Using HF Radar Current Observation

This paper proposes a new method for data assimilation of the surface radial current observed by High Frequency ground wave radar and optimization of the bottom friction coefficient. In this method, the shallow water wave equation is introduced into the cost function of the multigrid three-dimensional variation data assimilation method as the weak constraint term, the surface current and the bottom friction coefficient are defined as the analytical variables, and the high spatiotemporal resolution surface radial flow observed by the high-frequency ground wave radar is used to optimize the surface current and bottom friction coefficient. This method can effectively consider the spatiotemporal correlation of radar data and extract multiscale information from surface radial flow data from long waves to short waves. Introducing the shallow water wave equation into the cost function as a weak constraint condition can adjust both the momentum and mass fields simultaneously to obtain more reasonable analysis information. The optimized bottom friction coefficient is introduced into the regional ocean numerical model to carry out numerical experiments. The test results show that the bottom friction coefficient obtained by this method can effectively improve the accuracy of the numerical simulation of sea surface height in the offshore area and reduce the simulation error.     

Deriving Changjiang coastal zone wind from C-band SAR and its application to salinity simulation

Wind plays an important role in hydrodynamic processes such as the expansion of Changjiang （Yangtze） River Diluted Water （CDW）, and shelf circulation in the Changjiang estuary. Thus, it is essential to include wind in the numerical simulation of these phenomena. Synthetic aperture radar （SAR） with high resolution and wide spatial coverage is valuable for measuring spatially inhomogeneous ocean surface wind fields. We have collected 87 ERS-2 SAR images with wind-induced streaks that cover the Cbangjiang coastal area, to verify and improve the validity of wind direction retrieval using the 2D fast Fourier transform method. We then used these wind directions as inputs to derive SAR wind speeds using the C-band model. To demonstrate the applicability of the algorithms, we validated the SAR-retrieved wind fields using QuikSCAT measurements and the atmospheric Weather Research Forecasting model. In general, we found good agreement between the datasets, indicating the reliability and applicability of SAR- retrieved algorithms under different atmospheric conditions. We investigated the main error sources of this process, and conducted sensitivity analyses to estimate the wind speed errors caused by the effect of speckle, uncertainties in wind direction, and inaccuracies in the normalized radar cross section. Finally, we used the SAR-retrieved wind fields to simulate the salinity distribution off the Changjiang estuary. The findings of this study will be valuable for wind resource assessment and the development of future numerical ocean models based on SAR images.     

SWOT宽刈幅干涉测高卫星数值模拟：以南海海平面变化监测为例

以中国南海及周边区域为例,利用ECCO2海洋模式数据模拟的SWOT观测数据评估SWOT的海平面长期观测能力。分析SWOT模拟误差表明,相位误差和横滚误差占主导,并且距离星下点越远误差越大。通过空间平滑对模拟的误差进行消除,南海地区SWOT的观测与海洋模式真值的均方根误差从4 cm降低到2 cm。对SWOT的观测和海洋模式信号进行分析发现,SWOT观测误差的空间分布基本呈南北条带状,这主要受卫星宽刈幅沿轨观测方式的影响,与海平面变化信号强度无关。进一步提取SWOT一条轨迹进行滤波和10 km×10 km网格插值,结果表明,2 km空间分辨率的地转流估计结果受噪声影响较大,而10 km分辨率结果更接近真值。     

A methodology for estimating Leaf Area Index by assimilating remote sensing data into crop model based on temporal and spatial knowledge

In this paper,a methodology for Leaf Area Index(LAI) estimating was proposed by assimilating remote sensed data into crop model based on temporal and spatial knowledge.Firstly,sensitive parameters of crop model were calibrated by Shuffled Complex Evolution method developed at the University of Arizona(SCE-UA) optimization method based on phenological information,which is called temporal knowledge.The calibrated crop model will be used as the forecast operator.Then,the Taylor′s mean value theorem was applied to extracting spatial information from the Moderate Resolution Imaging Spectroradiometer(MODIS) multi-scale data,which was used to calibrate the LAI inversion results by A two-layer Canopy Reflectance Model(ACRM) model.The calibrated LAI result was used as the observation operator.Finally,an Ensemble Kalman Filter(EnKF) was used to assimilate MODIS data into crop model.The results showed that the method could significantly improve the estimation accuracy of LAI and the simulated curves of LAI more conform to the crop growth situation closely comparing with MODIS LAI products.The root mean square error(RMSE) of LAI calculated by assimilation is 0.9185 which is reduced by 58.7% compared with that by simulation(0.3795),and before and after assimilation the mean error is reduced by 92.6% which is from 0.3563 to 0.0265.All these experiments indicated that the methodology proposed in this paper is reasonable and accurate for estimating crop LAI.     

一次川东暴雨的雷达资料同化试验与诊断分析

为了对大尺度暴雨天气过程的雷达资料四维变分同化效果进行验证,选取2013年6月29日至7月2日发生在川东遂宁地区的一次暴雨天气过程,使用WRF中尺度模式进行雷达资料的同化模拟试验,并使用模式输出进行诊断分析。结果表明,高时空分辨率的雷达资料使短时间窗口的四维变分同化成为可能。同化结果能很好地改善由地形和初始场误差等因素带来的模拟缺陷,模拟输出场能完整再现整个暴雨的发生发展过程。副高西南侧低空急流带来的海上水汽与南亚季风自南向北带来的水汽共同构成了本次过程稳定的水汽供应通道。中β尺度涡旋的不断生消交替形成了该次暴雨过程的3次降水阶段。垂直方向不稳定能量的快速累积,缓慢释放以及垂直方向强的水汽输送交换,是造成该次过程降水时间长,量级大的主要原因。     

商用飞机气象观测温度、风场随机误差分析

随着我国AMDAR资料（商业飞机气象观测）不断增加并已逐步应用于数值天气预报,AMDAR观测资料的质量影响其在天气预报业务中的应用效果。为评估AMDAR数据的质量,利用统计学方法,通过对选定的AMDAR温度及风场观测数据,进行其质量特性量一随机误差均方根的统计分析。分析结果表明：温度的随机误差均方根为0．90℃,风速的观测随机误差均方根为1．24m／s。温度观测随机误差均方根、风速观测误差均方根在边界层较大,边界层以上较小。在300hPa-500hPa气压层达到最小,其温度观测随机误差为0．76℃、风速观测随机误差均方根为1．03m／s。     

基于双曲线模型的卡尔曼滤波法在建筑物沉降预测中的应用

利用最小二乘法求出双曲线模型的模型参数,将此参数看作带有动态噪声的状态向量,建立基于双曲线模型的卡尔曼滤波模型,对建筑物的沉降量进行预测。卡尔曼滤波过程中,模型的参数不断发生变化,增强了其适应观测数据的能力,从而减小了拟合误差。计算表明,用基于双曲线模型的卡尔曼滤波模型对建筑物的沉降量进行预测,误差较小,效果较为理想。     

Ka波段雷达弱降水雨量估计方法与试验

毫米波雷达适合降水云的水凝粒子的观测,设备轻便且空间分辨率和角度分辨率较高,可用于机载或星载等对有效载荷要求苛刻且关注云雨探测的应用,因而毫米波雷达在气象科学研究中备受关注。在成都地区进行了Ka波段雷达弱降水累积雨量的观测,采用了HTI(高度时间显示)观测模式,分析了雷达测量降水的方法,联合雨量计对比了Z-R关系与衰减法计算累计降水量的效果,并通过测量误差拟合调整经验参数,减小了估测误差。     

A background error covariance model of significant wave height employing Monte Carlo simulation

The quality of background error statistics is one of the key components for successful assimilation of observations in a numerical model.The background error covariance(BEC) of ocean waves is generally estimated under an assumption that it is stationary over a period of time and uniform over a domain.However,error statistics are in fact functions of the physical processes governing the meteorological situation and vary with the wave condition.In this paper,we simulated the BEC of the significant wave height(SWH) employing Monte Carlo methods.An interesting result is that the BEC varies consistently with the mean wave direction(MWD).In the model domain,the BEC of the SWH decreases significantly when the MWD changes abruptly.A new BEC model of the SWH based on the correlation between the BEC and MWD was then developed.A case study of regional data assimilation was performed,where the SWH observations of buoy 22001 were used to assess the SWH hindcast.The results show that the new BEC model benefits wave prediction and allows reasonable approximations of anisotropy and inhomogeneous errors.     

基于选权迭代的总体最小二乘算法在三维坐标转换中的应用

提出一种基于选权迭代的TLS算法,通过IGG I函数进行定权,降低含粗差观测值的权值,在进行三维坐标转换时能有效地处理观测值粗差。实例证明,该算法可以获取更高精度的三维坐标转换参数。     

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相邻历元误差相关的抗差卡尔曼滤波算法分析

根据卡尔曼滤波理论以及抗差理论,本文推导出了相邻历元误差相关的抗差卡尔曼滤波模型,其对观测值中含有粗差有良好的抗差性。通过对含有粗差的变形监测数据分析,与相邻历元误差相关的卡尔曼滤波模型进行比较,采用本文构造的抗差卡尔曼滤波模型处理数据,无论是否有粗差存在观测值里,变形计算结果与实际结果大体一致,粗差对计算结果的影响不敏感。在对变形监测数据分析时,可得出卡尔曼滤波方法估计的状态向量,没有寄存大量的以往观测数据,而是使用最近的观测数据,经过不断的预测和改正,把新的状态展示在系统中。     

基于TRMM降水数据的空间降尺度模拟

本研究以黑河流域为例,通过在不同空间尺度上建立降水与影响因素的关系并选择最优尺度以此进行降尺度,建立了基于地理加权回归（GWR）与高精度曲面建模方法（HASM）相结合的跨尺度统计降尺度方法,对TRMM降水数据进行了降尺度模拟。最后,结合站点观测数据采用交叉验证法对降尺度结果进行了验证。结果表明,与传统的降尺度方法相比,考虑最优尺度的降尺度方法在一定程度上提高了降尺度结果的精度,同时表明对跨尺度过程中产生的误差进行修正可进一步提高结果精度。本研究所提出的方法可用于粗分辨率降水数据的降尺度模拟,可为站点稀疏地区或地形复杂地区高分辨率高精度降水数据的获取提供方法上的支持。     

土地变更调查数据库质量评价及其错误空间自相关分析——以河北省为例

评价土地变更调查数据库质量,研究数据库错误产生的原因是变更调查工作中的关键问题。本文采用对比分析法定量分析3年间数据库质量变化,并运用全局Moran's I系数、局部Moran's I系数,从县域尺度分析数据库错误的空间自相关格局,揭示数据库错误空间分布变化和局部异常特征。研究结果表明：(1)从错误数量、缺陷等级、错误分布图层和空间分布方面进行评估,河北省2012年数据库质量相较于2010年和2011年得到明显改善;(2)河北省各区县错误分布保持高度自相关,聚集程度波动变化,而局部显著性异常区域的出现主要源于人为误操作。通过研究数据库质量3年间变化情况及空间分布格局,能客观地评价数据库质量状况,有效地分析错误产生的原因,为新一轮土地变更调查工作提供建设性意见。     

观测质量对北斗系统集中式实时自主导航的影响分析

介绍集中式实时自主导航参数分解滤波的基本原理及星间链路观测值的仿真方法。基于仿真北斗系统全星座的星间链路测量数据，进行60 d的集中式实时自主导航解算，论证观测噪声及残余系统误差对北斗系统3类卫星自主导航精度的影响。结果表明，观测噪声对自主导航精度无显著影响；残余系统误差中的固定偏差为影响自主导航精度的主要成分，且残余系统误差对自主导航精度影响较大，需要对其认真检校。另外，观测噪声及残余系统误差的变化对北斗系统3类卫星自主导航精度的影响无显著差异。     

三维坐标转换的稳健加权总体最小二乘算法

针对当前加权对称相似变换中仅考虑观测值含有随机误差,而不考虑观测值含有粗差的情况,基于加权对称相似变换进一步验证其不具有抗差性,并在此基础上采用选权迭代法进行稳健加权对称相似变换。由中位数法求解具有抗差性的单位权中误差,构造标准化残差,求解权因子,进而求得可靠的参数解。实验结果表明,当观测值含有4~6个粗差时,采用该方法能够探测出更多可能存在粗差的数据,给出的权因子更合理,所得参数解精度更高、稳定性更强。