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| 1 | Latest Progress of the Chinese Meteorological Satellite Program and Core Data Processing Technologies显示文摘In this paper,the latest progress,major achievements and future plans of Chinese meteorological satellites and the core data processing techniques are discussed.First,the latest three FengYun(FY)meteorological satellites(FY-2H,FY-3D,and FY-4A)and their primary objectives are introduced Second,the core image navigation techniques and accuracies of the FY meteorological satellites are elaborated,including the latest geostationary(FY-2/4)and polar-orbit(FY-3)satellites.Third,the radiometric calibration techniques and accuracies of reflective solar bands,thermal infrared bands,and passive microwave bands for FY meteorological satellites are discussed.It also illustrates the latest progress of real-time calibration with the onboard calibration system and validation with different methods,including the vicarious China radiance calibration site calibration,pseudo invariant calibration site calibration,deep convective clouds calibration,and lunar calibration.Fourth,recent progress of meteorological satellite data assimilation applications and quantitative science produce are summarized at length.The main progress is in meteorological satellite data assimilation by using microwave and hyper-spectral infrared sensors in global and regional numerical weather prediction models.Lastly,the latest progress in radiative transfer,absorption and scattering calculations for satellite remote sensing is summarized,and some important research using a new radiative transfer model are illustrated. | Peng ZHANG Qifeng LU Xiuqing HU Songyan GU Lei YANG Min MIN Lin CHEN Na XU Ling Sun Wenguang BAI Gang MA Di XIAN | 2019 | Advances in Atmospheric Sciences2019，36，9： | 26 |
| 2 | The bZIP transcription factor MdHY5 regulates anthocyanin accumulation and nitrate assimilation in apple显示文摘The basic leucine zipper(bZIP)transcription factor HY5 plays a multifaceted role in plant growth and development.Here the apple MdHY5 gene was cloned based on its homology with Arabidopsis HY5.Expression analysis demonstrated that MdHY5 transcription was induced by light and abscisic acid treatments.Electrophoretic mobility shift assays and transient expression assays subsequently showed that MdHY5 positively regulated both its own transcription and that of MdMYB10 by binding to E-box and G-box motifs,respectively.Furthermore,we obtained transgenic apple calli that overexpressed the MdHY5 gene,and apple calli coloration assays showed that MdHY5 promoted anthocyanin accumulation by regulating expression of the MdMYB10 gene and downstream anthocyanin biosynthesis genes.In addition,the transcript levels of a series of nitrate reductase genes and nitrate uptake genes in both wild-type and transgenic apple calli were detected.In association with increased nitrate reductase activities and nitrate contents,the results indicated that MdHY5 might be an important regulator in nutrient assimilation.Taken together,these results indicate that MdHY5 plays a vital role in anthocyanin accumulation and nitrate assimilation in apple. | Jian-Ping An Feng-Jia Qu Ji-Fang Yao Xiao-Na Wang Chun-Xiang You Xiao-Fei Wang Yu-Jin Hao | 2017 | Horticulture Research2017，4，1： | 26 |
| 3 | Canopy and leaf gas exchange of Haloxylon ammodendron under different soil moisture regimes显示文摘In order to reveal the drought resistance and adaptation of the C4 desert plant Haloxylon ammodendron under artificially controlled soil moisture regimes,representative plants were selected to measure canopy photosynthesis using canopy photosynthetic measurement system.The results showed that appropriate soil moisture significantly enhances the canopy and leaf photosynthetic capacity,and extremely high soil moisture is not conducive to the photosynthesis of H.ammodendron. | GAO Song,SU PeiXi,YAN QiaoDi & DING SongShuang Linze Inland River Basin Research Station,Plant Stress Ecophysiology and Biotechnology Laboratory,Cold and Arid Regions Environmental and Engineering Research Institute,Chinese Academy of Sciences,Lanzhou 730000,China | 2010 | Science China(Life Sciences)2010，53，6： | 15 |
| 4 | An improvement on summer regional climate simulation over East China: Importance of data assimilation of soil moisture显示文摘The Newtonian relaxation is used to assimilate data from the Second Global Soil Wetness Project (GSWP2) into the initial field for soil moisture in a regional climate model (i.e., BCC_RegCM 1.0, hereinafter called RegCM). The results show that different nudging parameters can improve the simulation of the air temperature and the precipitation to some extent in summertime season over East China. When the nudging intensity is 0.5 and nudging duration is 5 days, the result is desirable. Introducing the data assimilation of soil moisture into RegCM, the amelioration is not only in the spatial distribution pattern but also in the magnitude of the temperature and the precipitation. More specifically, the assimilation experiments have corrected the systematical cold bias of the air temperature and the precipitation on the low side, which is much closer to the observation compared with the control experiment. On the whole, the assimilation experiments shed light on the fact that the simulated bias in the original RegCM may be affected by the description of soil moisture in the land surface process. Therefore, the effect of soil moisture in RegCM should be paid more attention in the future. | HU YaMin1,2,3, DING YiHui4 & LIAO Fei2 1 Institute of Tropical and Marine Meteorology, China Meteorological Administration, Guangzhou 510080, China 2 Guangdong Climate Center, Guangzhou 510080, China 3 Chinese Academy of Meteorological Sciences, Beijing 100081, China 4 National Climate Center, China Meteorological Administration, Beijing 100081, China | 2010 | Chinese Science Bulletin2010，55，9： | 13 |
| 5 | Full waveform inversion based on the ensemble Kalman filter method using uniform sampling without replacement显示文摘Full waveform inversion(FWI) has been increasingly more and more important in seismology to better understand the interior structure of the Earth. FWI, by taking advantage of both the traveltime and amplitude in the data, provides high-resolution model parameters of the earth which can produce images with high resolution. However, this inversion method conventionally suffers from non-uniqueness due to many local minima of the objective function and large computing costs. In this study, we propose a new FWI method in a semi-random framework by integrating the ensemble Kalman filter and uniform sampling without replacement. Numerical results demonstrate that the new method can achieve highresolution results and a wider convergence domain. Accordingly, the new method overcomes the disadvantage of conventional FWIs that depend strongly on the initial model. | Jian Wang Dinghui Yang Hao Jing Hao Wu | 2019 | Science Bulletin2019，64，5： | 13 |
| 6 | A land surface soil moisture data assimilation framework in consideration of the model subgrid-scale heterogeneity and soil water thawing and freezing显示文摘The Ensemble Kalman Filter (EnKF) is well known and widely used in land data assimilation for its high precision and simple operation. The land surface models used as the forecast operator in a land data assimilation system are usually designed to consider the model subgrid-heterogeneity and soil water thawing and freezing. To neglect their effects could lead to some errors in soil moisture assimilation. The dual EnKF method is employed in soil moisture data assimilation to build a soil moisture data as- similation framework based on the NCAR Community Land Model version 2.0 (CLM 2.0) in considera- tion of the effects of the model subgrid-heterogeneity and soil water thawing and freezing: Liquid volumetric soil moisture content in a given fraction is assimilated through the state filter process, while solid volumetric soil moisture content in the same fraction and solid/liquid volumetric soil moisture in the other fractions are optimized by the parameter filter. Preliminary experiments show that this dual EnKF-based assimilation framework can assimilate soil moisture more effectively and precisely than the usual EnKF-based assimilation framework without considering the model subgrid-scale heteroge- neity and soil water thawing and freezing. With the improvement of soil moisture simulation, the soil temperature-simulated precision can be also improved to some extent. | TIAN XiangJun XIE ZhengHui | 2008 | Science China Earth Sciences2008，51，7： | 11 |
| 7 | An explicit four-dimensional variational data assimilation method显示文摘A new data assimilation method called the explicit four-dimensional variational (4DVAR) method is proposed. In this method, the singular value decomposition (SVD) is used to construct the orthogonal basis vectors from a forecast ensemble in a 4D space. The basis vectors represent not only the spatial structure of the analysis variables but also the temporal evolution. After the analysis variables are ex-pressed by a truncated expansion of the basis vectors in the 4D space, the control variables in the cost function appear explicitly, so that the adjoint model, which is used to derive the gradient of cost func-tion with respect to the control variables, is no longer needed. The new technique significantly simpli-fies the data assimilation process. The advantage of the proposed method is demonstrated by several experiments using a shallow water numerical model and the results are compared with those of the conventional 4DVAR. It is shown that when the observation points are very dense, the conventional 4DVAR is better than the proposed method. However, when the observation points are sparse, the proposed method performs better. The sensitivity of the proposed method with respect to errors in the observations and the numerical model is lower than that of the conventional method. | QIU ChongJian ZHANG Lei SHAO AiMei | 2007 | Science China Earth Sciences2007，50，8： | 11 |
| 8 | A soil moisture assimilation scheme based on the ensemble Kalman filter using microwave brightness temperature显示文摘This study presents a soil moisture assimilation scheme, which could assimilate microwave brightness temperature directly, based on the ensemble Kalman filter and the shuffled complex evolution method (SCE-UA). It uses the soil water model of the land surface model CLM3.0 as the forecast operator, and a radiative transfer model (RTM) as the observation operator in the assimilation system. The assimilation scheme is implemented in two phases: the parameter calibration phase and the pure soil moisture assimilation phase. The vegetation optical thickness and surface roughness parameters in the RTM are calibrated by SCE-UA method and the optimal parameters are used as the final model parameters of the observation operator in the assimilation phase. The ideal experiments with synthetic data indicate that this scheme could significantly improve the simulation of soil moisture at the surface layer. Further- more, the estimation of soil moisture in the deeper layers could also be improved to a certain extent. The real assimilation experiments with AMSR-E brightness temperature at 10.65 GHz (vertical polariza- tion) show that the root mean square error (RMSE) of soil moisture in the top layer (0―10 cm) by as- similation is 0.03355 m3·m-3, which is reduced by 33.6% compared with that by simulation (0.05052 m3·m-3). The mean RMSE by assimilation for the deeper layers (10―50 cm) is also reduced by 20.9%. All these experiments demonstrate the reasonability of the assimilation scheme developed in this study. | BingHao Jia ZhengHui Xie XiangJun Tian ChunXiang Shi | 2009 | Science China Earth Sciences2009，52，11： | 10 |
| 9 | Towards reliable Arctic sea ice prediction using multivariate data assimilation显示文摘Rapid declines in Arctic sea ice have captured attention and pose significant challenges to a variety of stakeholders. There is a rising demand for Arctic sea ice prediction at daily to seasonal time scales, which is partly a sea ice initial condition problem. Thus, a multivariate data assimilation that integrates sea ice observations to generate realistic and skillful model initialization is needed to improve predictive skill of Arctic sea ice. Sea ice data assimilation is a relatively new research area. In this review paper, we focus on two challenges for implementing multivariate data assimilation systems for sea ice forecast. First, to address the challenge of limited spatiotemporal coverage and large uncertainties of observations, we discuss sea ice parameters derived from satellite remote sensing that(1) have been utilized for improved model initialization, including concentration, thickness and drift, and(2) are currently under development with the potential for enhancing the predictability of Arctic sea ice, including melt ponds and sea ice leads. Second, to strive to generate the ‘‘best' estimate of sea ice initial conditions by combining model simulations/forecasts and observations, we review capabilities and limitations of different data assimilation techniques that have been developed and used to assimilate observed sea ice parameters in dynamical models. | Jiping Liu Zhiqiang Chen Yongyun Hu Yuanyuan Zhang Yifan Ding Xiao Cheng Qinghua Yang Lars Nerger Gunnar Spreen Radley Horton Jun Inoue Chaoyuan Yang Ming Li Mirong Song | 2019 | Science Bulletin2019，64，1： | 10 |
| 10 | Application of altimetry data assimilation on mesoscale eddies simulation显示文摘Mesoscale eddy plays an important role in the ocean circulation. In order to improve the simulation accuracy of the mesoscale eddies, a three-dimensional variation (3DVAR) data assimilation system called Ocean Variational Analysis System (OVALS) is coupled with a POM model to simulate the mesoscale eddies in the Northwest Pacific Ocean. In this system, the sea surface height anomaly (SSHA) data by satellite altimeters are assimilated and translated into pseudo temperature and salinity (T-S) profile data. Then, these profile data are taken as observation data to be assimilated again and produce the three-dimensional analysis T-S field. According to the characteristics of mesoscale eddy, the most appropriate assimilation parameters are set up and testified in this system. A ten years mesoscale eddies simulation and comparison experiment is made, which includes two schemes: assimilation and non-assimilation. The results of comparison between two schemes and the observation show that the simulation accuracy of the assimilation scheme is much better than that of non-assimilation, which verified that the altimetry data assimilation method can improve the simulation accuracy of the mesoscale dramatically and indicates that it is possible to use this system on the forecast of mesoscale eddies in the future. | GAO Shan WANG Fan LI MingKui CHEN YongLi YAN ChangXiang ZHU Jiang | 2008 | Science China Earth Sciences2008，51，1： | 10 |
| 11 | 热带风压场平衡特征及其对GRAPES系统中同化预报的影响研究Ⅱ:动力与统计混合平衡约束方案的应用显示文摘研究I的结果表明:线性平衡方程(LBE)在热带地区不适用,而进一步改进方向是削弱LBE在该区域的约束程度。本文以此为基础,在GRAPES(global/regional assimilation and prediction system)全球变分同化系统中引入动力与统计混合平衡约束方案。新方案在逐层求解LBE的基础上增加垂直方向的线性回归,回归系数随纬度和高度变化。针对背景误差协方差的分析表明,新方案可以更好的保证独立分析变量间预报误差不相关的基本要求,并大幅度减小热带地区平衡气压预报误差方差的量值和占总方差的比例。单点试验结果表明,与LBE方案相比,新方案对中、高纬影响很小,但在热带地区成功实现了风、压场分析的解耦,两者分析更为独立。并且,虽未考虑具体波动模态,但新方案给出的风、压场协相关结构与研究I的理论分析结果相近。一个月的同化循环与预报结果表明,引入新方案后,赤道外地区的同化预报效果为中性偏正,而热带地区风场的同化预报效果显著提高,LBE方案中平流层低层的风场同化预报异常被基本消除。 | 王瑞春 龚建东 张林 陆慧娟 | 2015 | 大气科学2015，39，6： | 10 |
| 12 | Conjugate Gradient Algorithm in the Four-Dimensional Variational Data Assimilation System in GRAPES显示文摘Minimization algorithms are singular components in four-dimensional variational data assimilation(4DVar).In this paper,the convergence and application of the conjugate gradient algorithm(CGA),which is based on the Lanczos iterative algorithm and the Hessian matrix derived from tangent linear and adjoint models using a non-hydrostatic framework,are investigated in the 4DVar minimization.First,the influence of the Gram-Schmidt orthogonalization of the Lanczos vector on the convergence of the Lanczos algorithm is studied.The results show that the Lanczos algorithm without orthogonalization fails to converge after the ninth iteration in the 4DVar minimization,while the orthogonalized Lanczos algorithm converges stably.Second,the convergence and computational efficiency of the CGA and quasi-Newton method in batch cycling assimilation experiments are compared on the 4DVar platform of the Global/Regional Assimilation and Prediction System(GRAPES).The CGA is 40%more computationally efficient than the quasi-Newton method,although the equivalent analysis results can be obtained by using either the CGA or the quasi-Newton method.Thus,the CGA based on Lanczos iterations is better for solving the optimization problems in the GRAPES 4DVar system. | Yongzhu LIU Lin ZHANG Zhihua LIAN | 2018 | Journal of Meteorological Research2018，32，6： | 9 |
| 13 | Current Status and Future Challenges of Weather Radar Polarimetry: Bridging the Gap between Radar Meteorology/Hydrology/Engineering and Numerical Weather Prediction显示文摘After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve weather observations,quantification, forecasting, and warnings. The weather radar networks in China and other countries are also being upgraded with dual-polarization capability. Now, with radar polarimetry technology having matured, and PRD available both nationally and globally, it is important to understand the current status and future challenges and opportunities. The potential impact of PRD has been limited by their oftentimes subjective and empirical use. More importantly, the community has not begun to regularly derive from PRD the state parameters, such as water mixing ratios and number concentrations, used in numerical weather prediction(NWP) models.In this review, we summarize the current status of weather radar polarimetry, discuss the issues and limitations of PRD usage, and explore potential approaches to more efficiently use PRD for quantitative precipitation estimation and forecasting based on statistical retrieval with physical constraints where prior information is used and observation error is included. This approach aligns the observation-based retrievals favored by the radar meteorology community with the model-based analysis of the NWP community. We also examine the challenges and opportunities of polarimetric phased array radar research and development for future weather observation. | Guifu ZHANG Vivek N.MAHALE Bryan J.PUTNAM Youcun QI Qing CAO ANDrew D.BYRD Petar BUKOVCIC Dusan S.ZRNIC Jidong GAO Ming XUE Youngsun JUNG Heather D.REEVES Pamela L.HEINSELMAN AlexANDer RYZHKOV Robert D.PALMER Pengfei ZHANG Mark WEBER Greg M.MCFARQUHAR Berrien MOORE III Yan ZHANG Jian ZHANG J.VIVEKANANDAN Yasser AL-RASHID Richard L.ICE Daniel S.BERKOWITZ Chong-chi TONG Caleb FULTON Richard J.DOVIAK | 2019 | Advances in Atmospheric Sciences2019，36，6： | 9 |
| 14 | GLDAS和CMIP5产品的中国土壤湿度-降水耦合分析及变化趋势显示文摘利用GLDAS同化产品和12个CMIP5模式的输出结果,从土壤湿度对降水影响的两个中间环节出发,通过分析陆面耦合指数ILH、潜热通量—抬升凝结高度耦合指数ILCL以及抬升凝结高度ZLCL间接研究中国区域土壤湿度与降水间耦合特征,并对1958~2013年及RCP4.5辐射强迫情景下50年(2006~2055年)的4个代表性区域夏季耦合强度的年代际变化特征进行分析。研究发现:1958~2013年期间,内蒙古阴山山脉附近、新疆和青海的部分地区为夏季中国土壤湿度与降水耦合的最强区域;陆面耦合指数ILH变化幅度从高到低依次出现在华北、华南、内蒙古中部和西北地区,并在20世纪70年代中到80年代中发生转折。2006~2055年的平均而言,预估内蒙古阴山山脉附近仍为耦合最强区;与历史时期(1958~2005年)比较,新疆中部和内蒙古阴山山脉附近的耦合指数ILH增大,而广西和广东地区的则减小;对于耦合指数ILH的年代际变化(2006~2055年),2026~2035年间华北最大而华南最小,西北地区变化不大,而内蒙古中部地区的耦合强度逐渐增大。 | 张述文 刘源 曹帮军 李少英 | 2016 | 气候与环境研究2016，0，2： | 9 |
| 15 | The Application of ARGO Data to the Global Ocean Data Assimilation Operational System of NCC显示文摘In this paper, we have preliminarily studied the application of ARGO (Array for Real-time Geostrophic Oceanography) data to the Global Ocean Data Assimilation System of National Climate Center of China (NCC-GODAS), which mainly contains 4 sub-systems such as data preprocessing, real-time wind stress calculating, variational analysis and interpolating, and ocean dynamic model. For the sake of using ARGO data, the relevant adjustment and improvement have been made at the corresponding aspects in the sub- systems. Using the observation data from 1981 to 2003 including the ARGO data of 2001 to July. 2003, we have performed a series of numerical experiments on this system. Comparing with the corresponding results of NCEP, It is illustrated that using ARGO data can improve the results of NCC-GODAS in the region of the Middle Pacific, for instance SST, SSTA (SST anomalies), Nino index, sea sub-surface temperature, etc. Furthermore, it is obtained that NCC-GODAS benefits from ARGO data in the other regions such as Atlantic Ocean, Indian Ocean, and extratropical Pacific Ocean much more than in the tropical Pacific. | 刘益民 张人禾 殷永红 牛涛 | 2005 | Acta meteorologica Sinica2005，19，3： | 9 |
| 16 | Reproducing past subduction and mantle flow using high-resolution global convection models显示文摘Plate subduction drives both the internal convection and the surface geology of the solid Earth.Despite the rapid increase of computational power,it remains challenging for geodynamic models to reproduce the history of Earth-like subduction and associated mantle flow.Here,based on an adaptive approach of sequential data assimilation,we present a high-resolution global model since the mid-Mesozoic.This model incorporates the thermal structure and surface kinematics of tectonic plates based on a recent plate reconstruction to reproduce the observed subduction configuration and Earth-like convection.Introduction of temperature-and composition-dependent rheology allows for incorporation of many natural complexities,such as initiation of subduction zones,reversal of subduction polarity,and detailed plate-boundary dynamics.The resultant present-day slab geometry well matches Benioff zones and seismic tomography at depths < 1500 km,making it possible to hindcast past subduction dynamics and mantle flow.For example,the model produces a flat Farallon slab beneath North America during the Late Cretaceous to Early Cenozoic,a feature that has been geodynamically challenging to reproduce.This high-resolution model can also capture details of the 4-D evolution of slabs and the ambient mantle,such as temporally and spatially varying mantle flow associated with evolving slab geometry and buoyancy flux,as well as the formation of shallow slab tears due to subduction of young seafloors and the resulting complex mantle deformation.Such a geodynamic framework serves to further constrain uncertain plate reconstruction in the geological past,and to better understand the origin of enigmatic mantle seismic features. | JiaShun Hu LiJun Liu Quan Zhou | 2018 | Earth and Planetary Physics2018，2，3： | 9 |
| 17 | NUMERICAL PREDICTION OF AN EXTREME RAINSTORM OVER THE PEARL RIVER DELTA REGION ON 7 MAY 2017 BASED ON WRF-ENKF显示文摘An ensemble Kalman filter based on the Weather Research and Forecasting Model(WRF-En KF) is used to explore the effectiveness of the assimilation of surface observation data in an extreme local rainstorm over the Pearl River Delta region on 7 May 2017. Before the occurrence of rainstorm, the signals of weather forecasts in this case are too weak to be predicted by numerical weather model, but the surface temperature over the urban area are high. The results of this study show that the wind field, temperature, and water vapor are obviously adjusted by assimilating surface data of 10-m wind, 2-m temperature, and 2-m water vapor mixing ratio at 2300 BST 6 May, especially below the height of 2 km. The southerly wind over the Pearl River Delta region is enhanced, and the convergence of wind over the northern Guangzhou city is also enhanced. Additionally, temperature, water vapor mixing ratio and pseudoequivalent potential temperature are obviously increased over the urban region, providing favorable conditions for the occurrence of heavy precipitation. After assimilation, the predictions of 12-h rainfall amount, temperature, and relative humidity are significantly improved, and the rainfall intensity and distribution in this case can be successfully reproduced. Moreover, sensitivity tests suggest that the assimilation of 2-m temperature is the key to predict this extreme rainfall and just assimilating data of surface wind or water vapor is not workable, implying that urban heat island effect may be an important factor in this extreme rainstorm. | 肖辉 万齐林 刘显通 郑腾飞 冯璐 夏丰 陈景华 | 2019 | Journal of Tropical Meteorology2019，25，3： | 8 |
| 18 | Application and improvement of an adaptive ensemble Kalman filter for soil moisture data assimilation显示文摘Accurate assignment of model and observation errors is crucial for the successful application of land surface data assimilation algorithms. Poorly-specified model and observation errors can significantly degrade assimilation results. In 2008, Reichle et al. developed an operational procedure to adaptively tune model and observation errors. In this paper, we modified and applied Reichle's procedure in the Noah land surface model to assimilate observed surface soil moisture data. Numerical simulations showed that: (1) the best estimate of model and observation errors appears when the empirical factor β equals 1.02; (2) the Reichle procedure can be deployed to adaptively tune errors if their true values change slowly; and (3) convergence of the Reichle procedure was improved using better initial errors achieved by iterative computations. | Shi XiaoKang Wen Jun Liu JianWen Tian Hui Wang Xin Li YaoDong | 2010 | Science China Earth Sciences2010，53，11： | 8 |
| 19 | Improving the estimation of hydrothermal state variables in the active layer of frozen ground by assimilating in situ observations and SSM/I data显示文摘The active layer of frozen ground data assimilation system adopts the SHAW (Simulteneous Heat and Water) model as the model operator. It employs an ensemble kalman filter to fuse state variables predicted by the SHAW model with in situ observation and the SSM/I 19 GHz brightness temperature for the purpose of optimizing model hydrothermal state variables. When there is little water movement in the frozen soil during the winter season, the unfrozen water content depends primarily on soil temperature. Thus, soil temperature is the crucial state variable to be improved. In contrast, soil moisture is heavily influenced by precipitation during the summer season. The simulation accuracy of soil moisture has a strong and direct impact on the soil temperature. In this case, the crucial state variable to be improved is soil moisture. One-dimensional assimilation experiments that have been carried out at AMDO station show that land data assimilation method can improve the estimation of hydrothermal state variables in the soil by fusing model information and observation information. The reasonable model error covariance matrix plays a key role in transferring the optimized surface state information to the deep soil, and it provides improved estimations of whole soil state profiles. After assimilating the 4-cm soil temperature by in situ observation, the soil temperature RMSE (Root Mean Square Error) of each soil layer decreased by 0.96℃ on average relative to the SHAW simulation. After assimilating the 4-cm soil moisture in situ observation, the soil moisture RMSE of each soil layer decreased by 0.020 m3·m-3. When assimilating the SSM/I 19 GHz brightness temperature, the soil temperature RMSE of each soil layer during the winter decreased by 0.76℃, while the soil moisture RMSE of each soil layer during the summer decreased by 0.018 m3·m-3. | JIN Rui LI Xin | 2009 | Science China Earth Sciences2009，52，11： | 7 |
| 20 | SST data assimilation experiments using an adaptive variational method显示文摘An adaptive variational data assimilation method is proposed by Zhu and Kamachi[1]. This method can adaptively adjust the model state without knowing explicitly the model error covariance matrix. The method enables very flexible ways to form some reduced order problems. A proper reduced order problem not only reduces computational burden but also leads to corrections that are more consistent with the model dynamics that trends to produce better forecast. These features make the adaptive variational method a good candidate for SST data assimilation because the model error of an ocean model is usually difficult to estimate. We applied this method to an SST data assimilation problem using the LOTUS data sets and an ocean mixed layer model (Mellor-Yamada level 2.5). Results of assimilation experiments showed good skill of improvement subsurface temperatures by assimilating surface observation alone. | ZHU Jiang WANG Hui ZHOU Guangqing | 2002 | Chinese Science Bulletin2002，47，23： | 7 |
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