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%。     

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。     

时间加密探空观测对分析和预报质量的敏感性研究

探空观测是气象资料同化中最基本的常规观测资料,对同化分析和预报的有效改善具有重要作用。由于现有探空观测站的空间分辨率较低,分布不均匀,且每日仅有两次观测,数量偏少,限制了其分析场对中小尺度大气状态的准确再现能力。自我国L波段雷达-数字探空仪更新换代以来,探空观测具备了获取每日4次、垂直分辨为秒级和分钟级的大气廓线资料。本文利用WRF中尺度数值模式,通过06时（世界时,下同）加密探空资料和12时常规探空资料的有效同化,研究分析了时间加密探空观测资料对同化分析和预报质量的敏感性影响。结果表明：同化06时的时间加密探空资料的午后暴雨预报质量优于12时常规探空观测。具体而言,同化06时的时间加密探空资料预报的大雨和暴雨的预报技巧高于12时常规探空资料;位势高度、温度和风场等预报场的均方根误差在高层的改进效果更加明显;06时的时间加密探空资料的同化对高层的高空急流和低层的水汽通量散度的预报质量贡献更大。批量试验进一步证实了有效同化时间加密探空资料对分析和数值预报效果改进的积极意义。     

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...     

Integration of remote sensing data into hydrological models for reservoir management

Abstract

The purpose of this paper is to present the methodology set up to derive catchment soil moisture from Earth Observation (EO) data using microwave spaceborne Synthetic Aperture Radar (SAR) images from ERS satellites and to study the improvements brought about by an assimilation of this information into hydrological models. The methodology used to derive EO data is based on the appropriate selection of land cover types for which the radar signal is mainly sensitive to soil moisture variations. Then a hydrological model is chosen, which can take advantage of the new information brought by remote sensing. The assimilation of soil moisture deduced from EO data into hydrological models is based principally on model parameter updating. The main assumption of this method is that the better the model simulates the current hydrological system, the better the following forecast will be. Another methodology used is a sequential one based on Kalman filtering. These methods have been put forward for use in the European AIMWATER project on the Seine catchment upstream of Paris (France) where dams are operated to alleviate floods in the Paris area.     

国家气象中心数值预报业务的进展

在最近的１５年中，国家气象中心的数值预报业务高速度发展，预报模式从北半球模式发展为全球谱模式，并配套建立了资料同化系统和用于降水预报的有限区预报模式，暴雨和台风预报模式正在研制中。目前数值预报时效已延至７天，Ｔ６３９３丙上时的预报水平已优于的数值预报产品的应用技术在不断改进，最高（低）气温下两天ＭＯＳ预报精度已接近预报员制作的综合预报结果。     

The Mathematic Models of the Kalman Filtering for Across-Fault Measurement

This paper makes a probe into the application of the Kalman filtering method to the data processing of across-fault measurements.On the basis of statistical regression,the mathematic and stochastic models of filtration are established by combining the regression method with Kalman filtering.In the filtering computation,not only the randomness of fault movements but also the time-dependent variation of environmental effects have been taken into consideration.By use of the adaptive filtering method,an estimation of the dynamic noise variance matrix is obtained through iteration.Models for one measuring line(leveling line or baseline),two measuring lines(both leveling lines or both baselines)and four measuring lines(two leveling lines and two baselines)are derived and established systematically.By means of these models,the data of across-fault measurements can be processed dynamically in real-time to provide the filtered values of height difference between benchmarks or baseline length at different time in     

Uptake of macroelements by the helophytePhalaris arundinacea L.

Helophytes are often incorporated into biological wastewater treatment plants. In favourable situations, they can take up large amounts of nutrients. One helophyte, the reed canarygrass (Phalaris arundinacea L.), is fast growing when supplied with sufficient light and nutrients. Experiments were carried out under natural climatic conditions in small plastic tanks filled with sand with regular additions of a balanced and concentrated nutrient solution. In the growing season (May–October), plant production reached 10.5 kg m^–2 of dry biomass, of which 66% was in the aerial parts. Maximum nutrient uptake capacity was reached just after flowering and before senescence (beginning of October): 49% N, 34% P, 52% K and 34% Mg of the input was fixed in the aerial parts, which are easily harvestable. The corresponding values for the below ground parts were 12%, 10%, 11% and 11% respectively. Excretion of K and Mg has been observed when nutrients are translocated to the storage organs.     

Cost-effective network design for groundwater flow monitoring

The extensive use of groundwater resources has increased the need for developing cost-effective monitoring networks to provide an indication of the degree to which the subsurface environment has been affected by human activities. This study presents a cost-effective approach to the design of groundwater flow monitoring networks. The groundwater network design is formulated with two problem formats: maximizing the statistical monitoring power for specified budget constraint and minimizing monitoring cost for statistical power requirement. The statistical monitoring power constraint is introduced with an information reliability threshold value. A branch and bound technique is employed to select the optimal solution from a discrete set of possible network alternatives. The method is tested to the design of groundwater flow monitoring problem in the Pomona County, California.