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以一维水温垂直分布数值模型为例,探索 Kalman 滤波法在海温观测数据同化中的应用。文中给出了在 165°E 赤道海域将连续观测的海温资料同化到模型中的 Kalman 滤波法试验,计算结果表明该同化方法对改进海温数值计算是十分有效的。 相似文献
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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
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为了提高近岸精细化海温预报精度,利用神经网络方法,分析了海温数值预报及观测数据在释用中的作用,研究了定点近岸海温影响因子的最优配置方案,建立了定点海温精细化数值预报释用模型,评估了释用模型性能。误差分析结果显示,数值海温产品及其观测在建模中起到了降低和稳定模型误差的作用;释用模型将定点数值预报的误差从2.2°C减少至0.7°C;预报误差较调训误差略高,但考虑到预报误差的稳定性,数值释用与人工经验预报水平持平,因此,该方法具有十分广阔的拓展空间和应用前景。 相似文献
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基于变分理论算法实现了METOP-A卫星AVHRR传感器探测数据的海洋表面温度变分反演,进行了连续1个月的海表温度反演试验,并分别从全球、分纬度带和天气系统活跃区域3个方面,将变分反演结果(VAR SST)与利用统计回归方法反演相同卫星得到的海表温度产品(GBL SST)、其他海温融合产品(OISST)及实际浮标观测数据等进行一系列评估。从全球评估指标看出,以OISST为参照,VAR SST要优于GBL SST;以浮标观测为参照,VAR SST略逊于GBL SST,而且VAR SST还改进了GBL SST随时间波动大的缺点;从分纬度带对比看出,在与OISST对比时,VAR SST在低纬度地区和北半球中纬度地区的质量要优于GBL SST,海温反演精度较高。研究还表明,由于变分方法考虑了大气状态的变化,能够更加有效订正卫星遥感过程中大气的削弱作用,从而反演出精度更高的海表温度,尤其在天气系统较为复杂的区域效果明显。 相似文献
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尝试利用卫星遥感高分辨率海表温度资料GHRSST (Group for High Resolution Sea Surface Temperature) 与海表温度(sea surface temperature, SST)数值预报产品之间的误差, 建立一种南海SST模式预报订正方法。首先, 利用南海的Argo浮标上层海温数据对GHRSST 海温数据进行验证, 结果表明两者之间均方根误差约为0.3℃, 相关系数为0.98, GHRSST 海温数据可用于南海业务化数值预报SST的订正。预报订正后的SST与Argo浮标海温数据相比, 24h、48h和72h的均方根误差均由0.8℃左右下降到0.5℃以内。与GHRSST 海温数据相比, 南海北部海域(110°E—121°E, 13°N—23°N)订正后的24h、48h和72h的SST预报空间误差均显著减小, 在冷空气影响南海期间或中尺度涡存在的过程中, SST预报订正效果也较为显著。因此, 该方法可考虑在南海业务化SST数值预报系统中应用。 相似文献
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数据同化利用观测信息对模型状态场调整的同时也可以对数值模型中的不确定参数进行估计,从而改进数值模型,提高数值模拟的精度。本文基于集合调整卡尔曼滤波方法,采用广义坐标系统的美国普林斯顿大学海洋模式的外模式开展了渤海和部分黄海海域M2分潮模拟中的水深估计研究。理想数据同化试验结果表明,集合调整卡尔曼滤波方法能很好地降低模式模拟的水位误差并反演出“真实”的水深参数。而在NAO.99Jb和验潮站数据的实际数据同化试验中,与验潮站数据相比较,水深参数估计后,模式模拟的M2分潮振幅与迟角误差分别降低了40.27%和49.19%。 相似文献
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V. B. Zalesny A. V. Gusev S. N. Moshonkin 《Izvestiya Atmospheric and Oceanic Physics》2013,49(6):642-658
A numerical primitive-equation model of the hydrodynamics of the Black Sea and the Sea of Azov in σ-coordinates is proposed. The model has a resolution of ~4 × 4 km in horizontal coordinates with 40-σ levels in the vertical and includes the four-dimensional variational initialization of temperature and salinity fields. A numerical initialization algorithm combines splitting methods and adjoint equations. Flow, temperature, sea level, and salinity fields driven by atmospheric forcing are calculated for the year 2008. The calculations are made in a variational initialization — prediction regime. Temperature and salinity fields are initialized at the end of each month. The optimality system includes forward and adjoint transport-diffusion equations for heat and salt that are linearized on the assimilation interval. Results of three numerical experiments with different sets of assimilated data in comparison with the prediction obtained from the forward model are discussed. 相似文献
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提出了利用共轭方程研究海洋对于局域大气平均气温的作用的方法。在现今海洋基本动力方程基础上导出了球坐标系下的海水温度共辊方程。分析了海水共轭温度的意义,其量值(或垂直梯度量值)表征了不同区域海洋对于局域气温的相应贡献,它在全球海洋中的分布对于局域气候形成与变化研究具有重要意义。 相似文献
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A new method of assimilating sea surface height (SSH) data into ocean models is introduced and tested. Many features observable by satellite altimetry are approximated by the first baroclinic mode over much of the ocean, especially in the lower (but non-equatorial) and mid latitude regions. Based on this dynamical trait, a reduced-dynamics adjoint technique is developed and implemented with a three-dimensional model using vertical normal mode decomposition. To reduce the complexity of the variational data assimilation problem, the adjoint equations are based on a one-active-layer reduced-gravity model, which approximates the first baroclinic mode, as opposed to the full three-dimensional model equations. The reduced dimensionality of the adjoint model leads to lower computational cost than a traditional variational data assimilation algorithm. The technique is applicable to regions of the ocean where the SSH variability is dominated by the first baroclinic mode. The adjustment of the first baroclinic mode model fields dynamically transfers the SSH information to the deep ocean layers. The technique is developed in a modular fashion that can be readily implemented with many three-dimensional ocean models. For this study, the method is tested with the Navy Coastal Ocean Model (NCOM) configured to simulate the Gulf of Mexico. 相似文献
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利用伴随法优化非线性潮汐模型的开边界条件Ⅱ.黄海、东海潮汐资料的同化试验 总被引:16,自引:4,他引:12
本研究基于最优控制理论,采用变分数据同化法,通过建立伴随模型,把观测资料同化到陆架海域潮汐数值模型中去,优化开边界条件,以便提高数值预报的精度.潮汐模型的控制方程为考虑平流项、非线性底摩擦和侧向涡动粘性项的非线性浅水方程组.在第Ⅰ部分建立伴随模型和进行“孪生”数值试验的基础上,给出利用验潮站的水位资料以及TOPEX/Poseidon卫星测高数据在黄海、东海进行变分数据同化试验的数值结果.试验表明利用上述资料对模型进行变分同化校正是可行的. 相似文献
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Motoyoshi Ikeda 《Journal of Oceanography》2003,59(1):79-86
An approximate variational method is proposed to assimilate an oceanographic data set with a numerical ocean model. In the
approximate method, the adjoint equation to a governing equation is derived and then converted to a finite difference form,
in contrast to the ordinary, exact variational method which is composed of a finite difference equation adjoint to the finite
difference governing equation. A cumbersome derivation of the adjoint equation is avoided, and finite difference schemes used
for the original governing equation are easily utilized for the adjoint equation. This method has been verified with twin
experiments. The flow field in the twin experiments is composed of dipole eddies in a two-layer quasi-geostrophic model. Initial
and boundary conditions are control variables. The descent converges towards the exact field within 50 iterations, showing
that the fundamental problem of the method (an unstable descent with a large number of iterations) does not appear. The approximate
method is promising and should be tried with real data.
This revised version was published online in July 2006 with corrections to the Cover Date. 相似文献