共查询到19条相似文献，搜索用时 687 毫秒
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以WRF(V3. 7)中尺度模式及其三维变分同化系统(WRF-3Dvar)为平台,GFS(0. 5°×0. 5°)提供模式背景场,对AMSU-A微波辐射资料进行循环同化试验,研究台风数值模拟中AMSU-A资料的可用性及循环同化方法的可行性。以2014年第19号台风"黄蜂"为例,开展了控制试验和多组同化试验。同化试验主要包括循环同化常规观测资料和不同卫星测得的AMSU-A微波辐射资料。在对各试验初始场进行对比的基础上,比较了不同同化试验方案的模拟效果,结果表明:1) AMSU-A资料同化能有效地调整初始场,模拟的台风路径和强度都有一定的改善; 2)不同卫星探测的AMSU-A资料同化效果存在较大的差异,其中NOAA-15资料同化模拟台风"黄蜂"的路径和强度与实况最为接近; 3)循环同化是增加数值模式中资料使用量、改善台风模拟效果的有效方法。 相似文献
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为了研究“二阶差分法”反演的晴空区风矢同化在台风分析和预报中的作用,以1509号台风“灿鸿”和1211号台风“海葵”为例,首先利用WRF-3DVAR系统对晴空风矢进行同化,探讨了晴空风矢的引入对模式初始场的影响。然后利用WRF模式对两个个例分别进行48 h的预报试验。通过对比控制试验和同化试验,结果表明,同化晴空风矢资料能够对初始风场和位势高度场进行合理的调整,在台风周围引导气流的作用下,台风路径与实况更靠近,从而提高了台风路径的预报效果。除此之外,同化晴空风矢对台风强度以及风场预报也有一定的改善作用,还可更准确地预报出降水的落区及雨强,提高降水预报质量。因此,晴空风矢的引入,有利于改善模式的初始场,从而提高WRF模式对台风的预报能力。 相似文献
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利用AMSU辐射率资料和常规观测资料,采用自行模拟的区域背景误差协方差(B)的WRFDA同化系统和中尺度数值模式WRF预报系统,对2007年7月8—9日发生在江淮流域的一次暴雨过程进行了模拟研究,设计了4组试验方案,对比分析了不同方案的模拟结果。结果表明,连续同化AMSU辐射率资料,可以改善降水预报效果,尤其是降水强度;通过连续使用AMSU资料,可以改进影响暴雨系统的大尺度环境场;AMSU-A资料对温度场有较为明显的影响,而AMSU-B资料对湿度场的调整有较大的贡献。 相似文献
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利用美国环境预报中心(NCEP)的GSI(Gridpoint Statstical Interpolation)业务同化系统,采用三维变分同化方法(3DVAR)和三维变分混合同化方法(3DVAR-Ensemble),针对2013年5月8日发生在我国华南地区的一次强降水天气过程进行了数值模拟试验研究,设计了不同组试验方案,将常规观测资料和AMSU-A\MHS\ATMS辐射率亮温资料直接同化进入区域大气模式WRF中,对比分析不同同化试验方案对模式初始场及降水预报效果的影响。数值试验结果表明:从初始时刻的同化增量来看,各试验组均改变了初始场结构,但增量的大小和分布却不同。加入ATMS微波资料的分析增量要小于同化AMSU-A+MHS的;Hybrid同化方法使用具有"流依赖"的背景误差协方差在一定程度上减小了模拟区域周围的虚假增量,使初始场的分布更真实和合理。从降水模拟的强度和空间分布评估结果来看,使用Hybrid方法同化ATMS的资料可以比较准确预报出降水中心的位置。综合而言,采用Hybrid的方法同化ATMS的资料最优。 相似文献
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AMSR2辐射率资料同化对台风“山神”分析和预报的影响研究 总被引：3，自引：2，他引：1
在WRFDA-3DVar（Weather Research and Forecasting model's 3-dimensional variational data assimilation）的框架下,添加了新的探测器AMSR2（Advanced Microwave Scanning Radiometer 2）微波辐射率资料的同化模块,实现了AMSR2辐射率资料在中小尺度同化系统中的有效使用。台风"山神"（Son-Tinh）直接同化AMSR2资料的个例试验结果表明,AMSR2资料可以很好的探测出台风的形态,并且与没有同化该资料的控制试验相比,同化AMSR2辐射率资料可以有效提高模式分析场的质量,进一步提高了台风中心气压,最大风速和台风路径的预报。 相似文献
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台风涡旋循环初始化方法及其在GRAPES-TCM中的应用 总被引：6，自引：1，他引：5
由于观测资料的缺乏,全球数值模式中台风涡旋一般较弱.但在区域数值模式中由于能使用更高的分辨率,采用适合台风的物理过程计算方案,因此区域模式中的台风涡旋能得到更好的发展.通常情况下,由于区域模式每次预报都使用全球模式的预报结果作为背景场,因此在区域模式中得到发展的台风涡旋并不能出现在下一次预报的初始场中.本研究结合BDA和涡旋重定位方法,采用MC-3DVar技术将台风涡旋初始化与资料同化技术结合起来,提出了循环初始化技术.在该技术中,提取区域模式6 h预报的台风涡旋周围的廓线资料,并根据台风观测位置将这些廓线资料平移到正确位置进行同化,从而使得台风涡旋在区域模式中得到循环发展.个例试验的结果表明循环初始化方案能更准确地刻画初始台风的强度和结构,相比控制试验,其初始台风强度更接近实况,结构更为合理,而且与观测更为接近,相应的,台风路径和强度预报也有很大的改善.对超强台风"蔷薇"的22次预报的总体结果表明,相对控制试验,循环初始化方案使得试验的总体路径预报距离误差从24 h的113 km降低到89 km,从48 h的188 km降低到184 km.另一方面,循环初始化方案对强度预报也有很大改善,24 h中心气压均方根误差从控制试验的32 hPa降到22 hPa.2009年汛期开始,以循环初始化方案为基础的GRAPES-TCM投入准业务试验,在对2009年2、3、4和6号热带气旋的准业务运行的预报结果的分析表明,新的方案较之采用涡旋重定位的GRAPES-TCM业务系统在路径和强度预报能力方面均有较大改善. 相似文献
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云雨条件下AMSR2微波成像资料同化试验及其在台风预报中的应用 总被引：2，自引：1，他引：1
采用WRF-ARW和WRFDA的3.8版本进行云雨条件下AMSR2(Advanced Microwave Scanning Radiometer 2)卫星微波成像资料的同化试验,并选择2014年7月第9号台风"威马逊"为研究对象,检验同化云雨条件下的AMSR2资料对台风预报结果的影响。结果表明:(1)云雨条件下的质量控制方案所保留的像元明显多于晴空条件下质量控制方案,且亮温模拟结果更加接近观测;(2)云雨影响的加入使得风场、高度场和海平面气压场的模拟结果好于晴空条件下模拟,且对台风中心有增温、增湿的作用。(3)云雨条件下模拟对台风的路径和强度预报均有改善。 相似文献
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利用WRF(Weather Research and Forecast)模式及WRFDA(WRF model data assimilation system)系统,针对2017年台风“天鸽”个例通过同化雷达径向速度(Vr)和反射率因子(RF),研究水凝物控制变量的雷达资料同化对台风分析预报的影响。研究表明：雷达径向速度的直接同化有效地改进了模式初始场中台风涡旋区的中小尺度信息,分析场中产生了气旋性的风场增量,对模式背景场中的台风有显著增强作用。通过在传统控制变量中扩展针对水凝物的控制变量可有效地同化雷达反射率因子资料,对初始场的水物质进行调整,并对随后确定性预报的台风路径和强度都有一定的正效果。此外,相比没有水凝物控制变量的雷达同化试验,加入了水凝物控制变量的雷达资料同化试验降水预报效果更好。这为将我国近海的地基多普勒天气雷达用于台风初始化分析和预报提供了一定的技术支撑和保障。 相似文献
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同化IASI资料对台风“红霞”和“莫兰蒂”预报的影响研究 总被引：2，自引：2，他引：2
红外高光谱大气探测仪IASI可提供高精度的大气垂直温度和湿度信息,能够探测台风结构特征,有效弥补台风影响区域观测资料稀缺的不足。以WRFDA三维变分同化系统为基础构建IASI同化试验平台,实现McNally提出的MW云检测方法,并调整参数形成大阈值的LMW云检测方法,以超强台风“红霞”（1506）和“莫兰蒂”（1614）为试验个例,对IASI观测资料进行同化对比试验。对于台风“红霞”,MW云检测方案对于高层通道299保留的观测数目仅为大阈值LMW云检测的16.2%和WRFDA系统默认的MMR云检测的9.2%,对于底层通道921分别为3.3%和2.6%。但是MW试验分析场强度最强,获得的72 h台风路径预报最接近真实路径,路径误差最小。两个台风个例试验结果相似,表明有效的云检测过程能提高IASI资料同化分析场的准确性,同化IASI资料有利于改善台风预报技巧。 相似文献
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ATOVS 不同卫星资料在台风模拟中的同化试验研究 总被引：5，自引：1，他引：4
利用美国国家大气研究中心(NCAR)开发的中尺度模式WRF(ARW)V3.2 及其三维变分同化系统WRF-3DVAR,以1011 号超强台风“ 凡亚比” 为个例,采用连续循环同化的方法对ATOVS 卫星资料进行同化试验,探讨了同化ATOVS 不同卫星资料对“ 凡亚比” 模拟的影响。结果表明,强度影响方面:同化ATOVS不同资料均可有效改善台风强度,台风中心海平面气压平均偏差从42 hPa 下降到18 hPa,但不同资料间的差异并不显著,平均在6 hPa 以内,这表明仅同化ATOVS 资料对台风强度的改善相对有限。路径影响方面:(1)不同卫星的同一种传感器资料效果略有不同,同化NOAA-18 和NOAA-15 的AMSU-A 资料效果较好,NOAA-16 的AMSU-A 效果较差;同化NOAA-15 和NOAA-16 的AMSU-B 资料效果相当,且均优于AMSU-A 资料。(2) 同一颗卫星不同传感器资料的差异较大,同化AMSU-B 资料的改善较为明显,HIRS-3 次之,AMSU-A较差,而同时同化不同资料并没有带来更为明显的改善。(3) 同时同化多颗卫星ATOVS 资料的试验表明,将多种资料引入到同化系统的同时,也带来相应的累积误差,因而仅同化一颗卫星可能比同时同化两颗或三颗卫星ATOVS 资料的效果要好。 相似文献
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Based on the newly developed Weather Research and Forecasting model(WRF)and its three-dimensional variational data assimilation(3DVAR)system,this study constructed twelve experiments to explore the impact of direct assimilation of different ATOVS radiance on the intensity and track simulation of super-typhoon Fanapi(2010)using a data assimilation cycle method.The result indicates that the assimilation of ATOVS radiance could improve typhoon intensity effectively.The average bias of the central sea level pressure(CSLP)drops to 18 hPa,compared to 42 hPa in the experiment without data assimilation.However,the influence due to different radiance data is not significant,which is less than 6hPa on average,implying limited improvement from sole assimilation of ATOVS radiance.The track issue is studied in the following steps.First,the radiance from the same sensor of different satellites could produce different effect.For the AMSU-A,NOAA-15 and NOAA-18,they produce equivalent improvement,whereas NOAA-16 produces slightly poor effect.And for the AMSU-B,NOAA-15 and NOAA-16,they produce equivalent and more positive effect than that provided by the AMSU-A.Second,the assimilation radiance from different sensors of the identical satellites could also produce different effect.The assimilation of AMSU-B produces the largest improvement,while the ameliorating effect of HIRS/3assimilation is inferior to that of AMSU-B assimilation,while the AMSU-A assimilation exhibits the poorest improvement.Moreover,the simultaneous assimilation of different radiance could not produce further improvement.Finally,the experiments of simultaneous assimilation radiance from multiple satellites indicate that such assimilation may lead to negative effect due to accumulative bias when adding various radiance data into the data assimilation system.Thus the assimilation of ATOVS radiance from a single satellite may perform better than that from two or three satellites. 相似文献
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Impact of Assimilating Radiances with the WRFDA ETKF/3DVAR Hybrid System on Prediction of Two Typhoons in 2012 
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下载免费PDF全文 XU Dongmei HUANG Xiang-Yu WANG Hongli Arthur P. MIZZI MIN Jinzhong 《Acta Meteorologica Sinica》2015,29(1):28-40
The impacts of AMSU-A and IASI (Infrared Atmospheric Sounding Interferometer) radiances assimila-tion on the prediction of typhoons Vicente and Saola (2012) are studied by using the ensemble transform ... 相似文献
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本文以2015年13号超强台风“苏迪罗”为个例,利用WRF模式及其3DVar同化系统对NOAA15、NOAA18和NOAA19的AMSU-A微波遥感资料分别同化及组合同化,探究同化不同卫星的同一种微波遥感资料对于台风路径模拟效果的影响。结果表明:同化不同卫星的同一种微波遥感资料对于台风路径模拟具有不同的调整,本文中NOAA15的同化效果最好,其次是NOAA18,最后是NOAA19;同时同化NOAA15、NOAA18和NOAA19的AMSU-A资料并没有取得最好的同化效果,而组合NOAA15和NOAA18则取得了最好的同化效果,即不是同化的卫星数量越多,同化效果越好;同化试验3个时刻的增量场表明同化不同卫星的同一种微波遥感资料对物理场具有不同的调整,这与其对台风模拟路径的调整有着较好的对应,相对于温度场、海平面气压场、位势高度场和风场的增量结构与模拟台风路径的调整更为密切。 相似文献
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Direct assimilation of cloud-affected microwave brightness temperatures from AMSU-A into the GSI three-dimensional variational(3D-Var) assimilation system is preliminarily studied in this paper. A combination of cloud microphysics parameters retrieved by the 1D-Var algorithm(including vertical profiles of cloud liquid water content, ice water content, and rain water content) and atmospheric state parameters from objective analysis fields of an NWP model are used as background fields. Three cloud microphysics parameters(cloud liquid water content, ice water content, and rain water content) are applied to the control variable. Typhoon Halong(2014) is selected as an example. The results show that direct assimilation of cloud-affected AMSU-A observations can effectively adjust the structure of large-scale temperature, humidity and wind analysis fields due to the assimilation of more AMSU-A observations in typhoon cloudy areas, especially typhoon spiral cloud belts. These adjustments, with temperatures increasing and humidities decreasing in the movement direction of the typhoon,bring the forecasted typhoon moving direction closer to its real path. The assimilation of cloud-affected satellite microwave brightness temperatures can provide better analysis fields that are more similar to the actual situation. Furthermore, typhoon prediction accuracy is improved using these assimilation analysis fields as the initial forecast fields in NWP models. 相似文献
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Application of ATOVS microwave radiance assimilation to rainfall prediction in Summer 2004 总被引：3，自引：0，他引：3
Experiments are performed in this paper to understand the influence of satellite radiance data on the initial field of a numerical prediction system and rainfall prediction. First, Advanced Microwave Sounder Unit A （AMSU-A） and Unit B （AMSU-B） radiance data are directly used by three-dimensional variational data assimilation to improve the background field of the numerical model. Then, the detailed effect of the radiance data on the background field is analyzed. Secondly, the background field, which is formed by application of Advanced Television and Infrared Observation Satellite Operational Vertical Sounder （ATOVS） microwave radiance assimilation, is employed to simulate some heavy rainfall cases. The experiment results show that the assimilation of AMSU-A （B） microwave radiance data has a certain impact on the geopotential height, temperature, relative humidity and flow fields. And the impacts on the background field are mostly similar in the different months in summer. The heavy rainfall experiments reveal that the application of AMSU-A （B） microwave radiance data can improve the rainfall prediction significantly. In particular, the AMSU-A radiance data can significantly enhance the prediction of rainfall above 10 mm within 48 h, and the AMSU-B radiance data can improve the prediction of rainfall above 50 mm within 24 h. The present study confirms that the direct assimilation of satellite radiance data is an effective way to improve the prediction of heavy rainfall in the summer in China. 相似文献
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The impact of assimilating radiance data from the advanced satellite sensor GMI(GPM microwave imager) for typhoon analyses and forecasts was investigated using both a three-dimensional variational(3DVAR) and a hybrid ensemble-3DVAR method. The interface of assimilating the radiance for the sensor GMI was established in the Weather Research and Forecasting(WRF) model. The GMI radiance data are assimilated for Typhoon Matmo(2014), Typhoon Chan-hom(2015), Typhoon Meranti(2016), and Typhoon Mangkhut(2018) in the Pacific before their landing. The results show that after assimilating the GMI radiance data under clear sky condition with the 3DVAR method, the wind,temperature, and humidity fields are effectively adjusted, leading to improved forecast skills of the typhoon track with GMI radiance assimilation. The hybrid DA method is able to further adjust the location of the typhoon systematically. The improvement of the track forecast is even more obvious for later forecast periods. In addition, water vapor and hydrometeors are enhanced to some extent, especially with the hybrid method. 相似文献
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Kefeng ZHU Ming XUE Yujie PAN Ming HU Stanley G. BENJAMIN Stephen S. WEYGANDT Haidao LIN 《大气科学进展》2019,36(12):1308-1326
A regional ensemble Kalman filter (EnKF) data assimilation (DA) and forecast system was recently established based on the Gridpoint Statistical Interpolation (GSI) analysis system. The EnKF DA system was tested with continuous threehourly updated cycles followed by 18-h deterministic forecasts from every three-hourly ensemble mean analysis. Initial tests showed negative to neutral impacts of assimilating satellite radiance data due to the improper bias correction procedure. In this study, two bias correction schemes within the established EnKF DA system are investigated and the impact of assimilating additional polar-orbiting satellite radiance is also investigated. Two group experiments are conducted. The purpose of the first group is to evaluate the bias correction procedure. Two online bias correction methods based on GSI 3DVar and EnKF algorithms are used to assimilate AMSU-A radiance data. Results show that both variational and EnKF-based bias correction procedures effectively reduce the observation and background radiance differences, achieving positive impacts on forecasts. With proper bias correction, we assimilate full radiance observations including AMSU-A, AMSU-B, AIRS, HIRS3/4, and MHS in the second group. The relative percentage improvements(RPIs) for all forecast variables compared to those without radiance data assimilation are mostly positive, with the RPI of upper-air relative humidity being the largest. Additionally, precipitation forecasts on a downscaled 13-km grid from 40-km EnKF analyses are also improved by radiance assimilation for almost all forecast hours. 相似文献