变分同化框架通过背景误差协方差构建动力平衡约束的研究进展   总被引：1，自引：1，他引：0  

王瑞春  龚建东 《气象》2016,42(9):1033-1044

通过背景误差协方差构建动力平衡约束是变分同化框架设计的重要环节。它不仅帮助实现变量间的协同分析,提高观测使用效率,还能改善变分极小化问题的性状。本文在系统梳理通过背景误差协方差引入动力平衡约束的方式、流程的基础上,对求解目前全球和有限区域变分同化系统普遍采用的准地转平衡和静力平衡约束的共性问题和存在的不足作了归纳总结。分析了求解准地转平衡约束的三类方案:动力平衡方程方案、统计方案和动力-统计相结合方案的优缺点。对照比较了不同垂直离散方案下求解静力平衡约束时遇到的欠定问题的表现以及解决途径。最后,展望了基于背景误差协方差构建动力平衡约束在赤道等特殊地区、高分辨率同化系统、以及集合-变分混合同化系统发展中面临的挑战和机遇。  相似文献   

东中国海黑潮海洋锋的季节变化特征及其成因   总被引：1，自引：0，他引：1  

张然  徐海明  张百超 《气象科学》2016,36(2):203-211

利用高分辨率海洋和大气再分析资料研究了东中国海黑潮海洋锋的季节变化特征及其成因。研究表明,东海黑潮海洋锋存在明显的季节变化,从冬季到次年春季逐渐增强,并在春季达到最强,初夏以后强度逐渐减弱,9—10月达到全年最弱。通过诊断混合层热流量方程发现,东海黑潮区一年四季均表现为暖的温度平流,有利于海洋锋的形成和维持,该暖平流也存在季节变化并在春季达到最大,对海洋锋在春季达到最强起了重要作用。海气界面净热通量在秋冬季对海洋锋的形成有促进作用,有利于海洋锋增强,而在春夏季则起抑制作用,促进海洋锋消亡。温度垂直输送全年对海洋锋起一定程度的抑制作用。总之,在海温水平平流和海表净热通量的共同作用下导致海洋锋春季达到最强,而夏秋季海表净热通量和温度垂直输送作用的共同作用致使海洋锋减弱并最后消失。因此,海洋的动力和热力共同作用导致了东海黑潮海洋锋的季节变化,其中海温水平平流和海表净热通量对海洋锋的季节变化起主要作用,而温度垂直输送项对海洋锋的发展起抑制作用,但影响相对较小。  相似文献   

EnSRF雷达资料同化在一次飑线过程中的应用研究   总被引：3，自引：1，他引：2  

高士博  闵锦忠  黄丹莲 《大气科学》2016,40(6):1127-1142

本文利用包含复杂冰相微物理过程的WRF（Weather Research and Forecasting）模式,针对2007年4月23日发生在我国华南地区的一次典型飑线天气过程,分别进行了确定性预报和集合预报试验,发现确定性预报能大致捕捉到飑线系统的发生发展过程,但对飑线后部的层云区模拟效果较差。集合预报能够有效地减少模式的不确定性,大部分集合成员对飑线的模拟效果优于确定性预报。进一步将集合预报得到的40个成员作为背景场,采用EnSRF（Ensemble Square Root Filter）同化多普勒天气雷达资料,并将分析得到的集合作为初始场进行集合预报,通过与未同化雷达资料的集合对比,考察了EnSRF同化多部雷达资料对飑线系统的影响。结果表明:EnSRF雷达资料同化增加了模式初始场的中小尺度信息,大部分集合成员的分析场能够较准确地再现飑线的热力场、动力场和微物理场的细致特征,并且模拟出飑线后部的层云结构。通过对EnSRF分析的集合进行模拟发现,大部分集合成员较未同化雷达资料时模拟效果有明显改善。同化后的集合预报ETS（Equitable Threat Score）评分最高,其次是未同化的集合预报,确定性预报的最低。  相似文献   

Landscape pattern and transition under natural and anthropogenic disturbance in an arid region of northwestern China     

《International Journal of Applied Earth Observation and Geoinformation》2016

There is a pressing need to determine the relationships between driving variables and landscape transformations. Human activities shape landscapes and turn them into complex assemblages of highly diverse structures. Other factors, including climate and topography, also play significant roles in landscape transitions, and identifying the interactions among the variables is critical to environmental management. This study analyzed the configurations and spatial-temporal processes of landscape changes from 1998 to 2011 under different anthropogenic disturbances, identified the main variables that determine the landscape patterns and transitions, and quantified the relationships between pairs of driver sets. Landsat images of Baicheng and Tekes from 1998, 2006 and 2011 were used to classify landscapes by supervised classification. Redundancy analysis (RDA) and variation partitioning were performed to identify the main driving forces and to quantify the unique, shared, and total explained variation of the sets of variables. The results indicate that the proportions of otherwise identical landscapes in Baicheng and Tekes were very different. The area of the grassland in Tekes was much larger than that of the cropland; however, the differences between the grassland and cropland in Baicheng were not as pronounced. Much of the grassland in Tekes was located in an area that was near residents, whereas most of the grassland in Baicheng was far from residents. The slope, elevation, annual precipitation, annual temperature, and distance to the nearest resident were strong driving forces influencing the patterns and transitions of the landscapes. The results of the variation partitioning indicated complex interrelationships among all of the pairs of driver sets. All of the variable sets had significant explanatory roles, most of which had both unique and shared variations with the others. The results of this study can assist policy makers and planners in implementing sustainable landscape management and effective protection strategies.  相似文献   

Estimating winter wheat biomass by assimilating leaf area index derived from fusion of Landsat-8 and MODIS data     

《International Journal of Applied Earth Observation and Geoinformation》2016

A sufficient number of satellite acquisitions in a growing season are essential for deriving agronomic indicators, such as green leaf area index (GLAI), to be assimilated into crop models for crop productivity estimation. However, for most high resolution orbital optical satellites, it is often difficult to obtain images frequently due to their long revisit cycles and unfavorable weather conditions. Data fusion algorithms, such as the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and the Enhanced STARFM (ESTARFM), have been developed to generate synthetic data with high spatial and temporal resolution to address this issue. In this study, we evaluated the approach of assimilating GLAI into the Simple Algorithm for Yield Estimation model (SAFY) for winter wheat biomass estimation. GLAI was estimated using the two-band Enhanced Vegetation Index (EVI2) derived from data acquired by the Operational Land Imager (OLI) onboard the Landsat-8 and a fusion dataset generated by blending the Moderate-Resolution Imaging Spectroradiometer (MODIS) data and the OLI data using the STARFM and ESTARFM models. The fusion dataset had the temporal resolution of the MODIS data and the spatial resolution of the OLI data. Key parameters of the SAFY model were optimised through assimilation of the estimated GLAI into the crop model using the Shuffled Complex Evolution-University of Arizona (SCE-UA) algorithm. A good agreement was achieved between the estimated and field measured biomass by assimilating the GLAI derived from the OLI data (GLAI_L) alone (R² = 0.77 and RMSE = 231 g m⁻²). Assimilation of GLAI derived from the fusion dataset (GLAI_F) resulted in a R² of 0.71 and RMSE of 193 g m⁻² while assimilating the combination of GLAI_L and GLAI_F led to further improvements (R² = 0.76 and RMSE = 176 g m⁻²). Our results demonstrated the potential of using the fusion algorithms to improve crop growth monitoring and crop productivity estimation when the number of high resolution remote sensing data acquisitions is limited.  相似文献   

MASNUM-WAM海浪模式集合Kalman滤波同化研究-I.风场扰动对海浪模拟影响   总被引：1，自引：1，他引：0  

孙盟  尹训强  杨永增  吴克俭 《海洋与湖沼》2016,47(6):1091-1100

模式集合样本的代表性和观测信息的可靠性是制约数据同化效果的重要因素,而前者对海浪模式同化的影响尤为显著。由于海浪模式对初始场的敏感性较弱,来自大气的风输入源函数是海浪的重要能量输入,如何合理地对风输入进行扰动,构造海浪的集合模式运行,是实现和改进海浪模式集合Kalman滤波同化的关键问题。为了实现海浪模式集合运行,本文提出了风场的三种集合扰动方案,分别为：纯随机数、随机场和时间滞后的风场扰动方法。本研究利用2014年1月ECMWF全球风场,基于这三种风场扰动方法开展了集合海浪模式的集合运行实验,并统计分析了海浪特征要素（有效波高）和二维波数谱对风场扰动的响应。结果表明,随机场集合扰动方案所构造的风场集合效果最佳,所得海浪模拟结果的集合样本发散度适中,能够较为合理地反映背景误差的统计特征,可用于进一步的集合Kalman滤波海浪数据同化实验。  相似文献   

盐度对长江口3种滤食性贝类滤水率、摄食率、同化率的影响   总被引：4，自引：2，他引：2  

吕昊泽  刘健  陈锦辉  沈和定  吴杨平 《海洋科学》2016,40(8):10-17

采用实验生态学方法研究了盐度对长江口缢蛏(Sinonovacula constricta)、河蚬(Corbicula fluminea)和光滑河蓝蛤(Potamocorbula laevis)滤水率、摄食率、同化率的影响。缢蛏组设6个盐度梯度(5,10,15,20,25,30),光滑河蓝蛤组设6个盐度梯度(5,10,15,20,25,30),河蚬组设6个盐度梯度(0,5,10,15,20,25),并测定了此3种滤食性贝类的生物学参数。结果显示,3种滤食性贝类的滤水率、摄食率和同化率随着盐度的上升而增加,当上升到一定盐度时达到峰值,然后随着盐度的升高而降低。盐度20时,缢蛏滤水率、摄食率和同化率达到峰值,分别为0.57L/h、5.38mg POM/h和0.72%。盐度10时,光滑河蓝蛤滤水率和同化率达到峰值,分别为0.46L/h和0.53%,摄食率在盐度15时达到峰值3.80mg POM/h。盐度5时河蚬滤水率和摄食率都达到峰值,分别为0.39 L/h和2.48 mg POM/h,同化率在盐度0时已达到峰值0.51%,并随盐度上升而下降。上述结果表明,盐度对3种滤食性贝类的3个摄食生理指标均有显著影响。  相似文献   

南海中尺度涡强度的季节和年际变化分析     

王文杰  刘宇迪  朱金双  沈俊 《海洋科学》2016,40(12):94-106

为了研究南海中尺度涡强度的季节和年际变化规律,利用Matlab提取50 a(1958~2007年)简单海洋资料同化(Simple Ocean Data Assimilation,SODA)月平均数据集中流场和海表面高度场数据,应用一个涡旋自动探测算法对南海中尺度涡初始生成位置进行分析,并分析了海表面高度异常均方根值的季节变化和年际变化。结果表明:50 a里南海中尺度涡主要分布在吕宋岛西北海域、吕宋岛西南海域和越南以东广大海域,秋、冬季中尺度涡能量较高,春季中尺度涡最弱,中尺度涡强度高值区年际变化明显。从季节变化上看,海面高度异常均方根春、夏季最小,秋冬季最大;从年际变化上看,与同时期Nino3指数有显著负相关,周期大约为3 a。  相似文献   

Assimilation of Polarimetric Radar Data Using an Ensemble Kalman Filter for the Analysis and Forecast of Tropical Storm Ewiniar     

黎慧琦  刘显通  肖辉  万齐林 《热带气象学报(英文版)》2021,27(2):94-108

This study explores the potential for directly assimilating polarimetric radar data (including reflectivity Z and differential reflectivity ZDR) using an ensemble Kalman filter (EnKF) based on the Weather Research and Forecasting (WRF) model to improve analysis and forecast of Tropical Storm Ewiniar (2018). Ewiniar weakened but brought about heavy rainfall over Guangdong, China after its final landfall. Two experiments are performed, one assimilating only Z and the other assimilating both Z and ZDR. Assimilation of ZDR together with Z effectively modifies hydrometeor fields, and improves the intensity, shape and position of rainbands. Forecast of 24-hour extraordinary rainfall ≥250 mm is significantly improved. Improvement can also be seen in the wind fields because of cross-variable covariance. The current study shows the possibility of applying polarimetric radar data to improve forecasting of tropical cyclones, which deserves more researches in the future.  相似文献   

NUMERICAL PREDICTION OF AN EXTREME RAINSTORM OVER THE PEARL RIVER DELTA REGION ON 7 MAY 2017 BASED ON WRF-ENKF     

肖辉  万齐林  刘显通  郑腾飞  冯璐  夏丰  陈景华 《热带气象学报(英文版)》2019,25(3):312-323

An ensemble Kalman filter based on the Weather Research and Forecasting Model (WRF-EnKF) 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.  相似文献