基于ROMS和4DVAR的沿轨与网格化SSH数据同化效果评价

Remote sensing products are significant in the data assimilation of an ocean model. Considering the resolution and space coverage of different remote sensing data, two types of sea surface height(SSH) product are employed in the assimilation, including the gridded products from AVISO and the original along-track observations used in the generation. To explore their impact on the assimilation results, an experiment focus on the South China Sea(SCS) is conducted based on the Regional Ocean Modeling System(ROMS) and the four-dimensional variational data assimilation(4 DVAR) technology. The comparison with EN4 data set and Argo profile indicates that, the along-track SSH assimilation result presents to be more accurate than the gridded SSH assimilation, because some noises may have been introduced in the merging process. Moreover, the mesoscale eddy detection capability of the assimilation results is analyzed by a vector geometry–based algorithm. It is verified that, the assimilation of the gridded SSH shows superiority in describing the eddy's characteristics, since the complete structure of the ocean surface has been reconstructed by the original data merging.     

Deterministic non-linear wave prediction using probe data

The accurate prediction of non-linear sea states represents a great challenge, with a number of applications in oceanography, marine engineering, security of people and marine transportation, etc. In this paper, we report on the development of two efficient deterministic prediction models for 2D irregular wave-fields. These models are based on the exploitation of wave elevation time series given by one or more probes and on the use of two different numerical models for the wave-fields simulation. Two effective data assimilation processes are developed to improve the wave-field estimates obtained from the study of one or several probe signals, so that we obtain proper initial conditions for the forecast. The assimilation schemes have been validated on the reconstruction of model-generated observations and accurate predictions of the corresponding synthetic wave-fields evolution have been obtained.     

Reconstruction of eddies by assimilating satellite altimeter data into Princeton Ocean Model

An optimal interpolation assimilation model for satellite altimetry data is developed based on Princeton Ocean Model (POM), which is applied in a quasi-global domain, by the method of isotropic correlation between sea level anomaly (SLA) and sea temperature anomaly. The perfor- mance of this assimilation model is validated by the modeled results of SLA and the current patterns. Comparisons between modeling and satellite data show that both the magnitudes and distribution patterns of the simulated SLA are improved by assimilation. The most signiˉcant improvement is that meso-scale systems, e.g., eddies, are well reconstructed. The evolution of an eddy located in the northwest Paciˉc Ocean is traced by using the assimilation model. Model results show that during three months the eddy migrated southwestward for about 6 degrees before merging into the Kuroshio. The three dimensional structure of this eddy on 12 August 2001 is further analyzed. The strength of this warm, cyclonic eddy decreases with the increase of depth. The eddy shows di?erent horizontal patterns at di?erent layers, and the SLA and temperature ˉelds agree with each other well. This study suggests that this kind of data assimilation is economic and reliable for eddy reconstruction, and can be used as a promising technique in further studies of ocean eddies as well as other ˉne circulation structures.     

中国海及邻近海域卫星观测资料同化试验

利用1个基于POMgcs海洋模式和多重网格三维变分同化方法建立的中国海及邻近海域海面高与三维温盐流数值预报模型,通过一系列数值试验,研究了同化卫星测高和卫星遥感海面温度观测资料对该模型预报能力的影响。试验结果表明,同化卫星测高资料可明显改善海面高度与三维温度和盐度的分析预报效果,使1 200 m以上的温度预报误差减小0.16℃,并能有效提高对海洋中尺度现象的预报能力;同化卫星遥感海面温度对100 m以上的温度和盐度的预报效果有所改善,可使海面温度的预报误差减小10%。     

集合卡尔曼滤波在流域水文模型流量预报中的应用

针对流域降雨入渗过程,引入集合卡尔曼滤波(EnKF)理论,视整个边坡流域为一个随机动态系统,将边坡流域流量观测值作为系统的输出,用集合卡尔曼滤波模型来描述系统的状态;结合流域流量计算方法,实现水文模型参数的随机动态估计,在有效获得待估参数的同时还给出估计值的不确定性.通过数值算例表明,集合卡尔曼滤波可以有效地对含噪声的量测数据进行处理,能够跟踪水文模型的动态变化.相对于常用最优化算法,集合卡尔曼滤波同时给出反演结果和先验知识的后验分布,显示出更好的实时性和可靠性.     

Impact of 4DVAR assimilation of rainfall data on the simulation of mesoscale precipitation systems in a mei-yu heavy rainfall event

The multi-scale weather systems associated with a mei-yu front and the corresponding heavy precipitation during a particular heavy rainfall event that occurred on 4 5 July 2003 in east China were successfully simulated through rainfall assimilation using the PSU/NCAR non-hydrostatic, mesoscale, numerical model （MM5） and its four-dimensional, variational, data assimilation （4DVAR） system. For this case, the improvement of the process via the 4DVAR rainfall assimilation into the simulation of mesoscale precipitation systems is investigated. With the rainfall assimilation, the convection is triggered at the right location and time, and the evolution and spatial distribution of the mesoscale convective systems （MCSs） are also more correctly simulated. Through the interactions between MCSs and the weather systems at different scales, including the low-level jet and mei-yu front, the simulation of the entire mei-yu weather system is significantly improved, both during the data assimilation window and the subsequent 12-h period. The results suggest that the rainfall assimilation first provides positive impact at the convective scale and the influences are then propagated upscale to the meso- and sub-synoptic scales.
Through a set of sensitive experiments designed to evaluate the impact of different initial variables on the simulation of mei-yu heavy rainfall, it was found that the moisture field and meridional wind had the strongest effect during the convection initialization stage, however, after the convection was fully triggered, all of the variables at the initial condition seemed to have comparable importance.     

数据同化在海洋生态模型中的应用和研究进展

将数据同化方法引入海洋生态系统动力学模型研究,利用现有的观测数据,获得最佳的模式参数、初始场或提高状态模拟,是当前多学科交叉研究的热门领域。本文依据国内外研究进展,主要就海洋生态模型研究中所采用的变分伴随、卡尔曼滤波、模拟退火法方法进行了介绍,总结了数据同化在我国的海洋生态系统研究中的现状和发展趋势。     

内蒙古区域数值预报对探空和地面观测资料的敏感性试验研究

基于内蒙古睿图预报系统的低分辨率版本和WRFDA-FSO诊断工具,评估2021年7月现有探空和地面观测对内蒙古睿图预报系统预报的影响。该方法计算代价相对低廉,并允许根据观测变量、观测类型、气压层次、地理区域等观测的子集对观测影响进行划分。代价函数为以干总能量为度量的背景场和分析场的预报误差之间的差异。结果表明:观测影响的总体总和为负,观测对预报起正贡献作用。对12 h预报误差减小贡献最大的观测来自探空观测的动力变量(U、V风分量)。而单时次单位数量平均观测影响,探空观测的贡献约为地面观测的1/2。探空观测对12 h预报误差减小从近地面层至模式层顶均保持正贡献作用,并在对流层中低层和对流层高空急流层存在两个极大值区域;地面观测在850 hPa以下低层正贡献占比明显。探空观测在被同化系统同化时均总体具有有利的影响,也反映出探空观测数据稳定、质量较高的特征;地面观测对12 h预报误差减小起正贡献作用次数最多的区域在河套地区尤为显著。同时,探讨了需进一步提高地面观测资料同化率的问题。     

The REM Adjoint System and Its 4DVar Data Assimilation Experiments

The Regional Eta-coordinate Model(REM) has performed well in forecasting heavy rainfalls in China in recent years.A four-dimensional variational assimilation system(4DVar) is developed to improve the forecast skill of the REM.The tangent linear model and adjoint model codes are written according to thecode to coderule,and the establishment of the REM adjoint modeling system is introduced in detail in this paper.The tangent linear and adjoint models of the REM are validated against the observational data,...     

Application of FY-2C Cloud Drift Winds in a Mesoscale Numerical Model

Statistical tests and error analysis of cloud drift winds(CDWs) from the FY-2C satellite were made by using radiosonde observations.According to the error characteristics of the CDW,a bias correction using the thermal wind theory was applied in the data quality control.The CDW data were then assimilated into the GRAPES-meso model via the GRAPES-3DVar.A torrential rain event that occurred in northwestern China during 1-2 July 2005 was simulated.The results indicate that the CDW data were mainly distribute...