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1.
为了评估同化ATOVS卫星微波资料在台风数值预报中的影响,利用中尺度模式WRF和三维变分同化系统WRFDA,采用国家卫星气象中心接收处理的卫星微波温度计AMSU-A辐射率L1c数据集,针对在2008年台风季中影响我国大陆的8个台风典型,开展批量卫星资料同化和数值预报试验。对同化效果的检验和对同化前、后西太平洋副热带高压的分析表明:AMSU-A资料对台风预报有改进作用,在44%的48 h预报样本中同化后路径有改善;同化微波资料后,副热带高压的改变直接影响台风路径。   相似文献   

2.
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   

3.
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   

4.
为加强国内卫星资料在同化系统中的应用,在自主构建的新一代WRF-EnSRF同化系统中,采用RTTOV辐射传输模式作为观测算子,并建立卫星资料读取、偏差订正及质量控制等子模块,构建出WRF-EnSRF卫星资料同化系统.运用该同化系统,同时同化NOAA-16的AMSU-A和AMSU-B的辐射率资料,进行华南暴雨过程的卫星资料同化数值模拟试验.试验结果表明:偏差订正后亮温资料拟合结果基本位于主对角线上,偏差有所降低.从TS评分看,同化试验对中雨及大雨部分的降水落区以及暴雨级别以上的降水强度的模拟效果有改善.试验证明,建立的卫星同化系统是可运行的.  相似文献   

5.
本研究利用WRF模式及其三维变分同化系统实现了对NOAA-16 AMSU-A微波资料的直接同化,针对2010年6月19日江西地区的一次强降水过程开展模拟与同化试验,并利用中国区域土壤湿度同化系统(CLSMDAS—China Land Soil Moisture Data Assimilation System)输出的土壤湿度值替换NCEP(National Centers for Environmental Prediction)资料中的土壤湿度,研究土壤湿度初值对辐射率资料直接同化中观测场与背景场偏差调整的影响。结果表明:采用CLSMDAS输出土壤湿度初值条件下模拟的亮温值与实际观测值更为接近,经过质量控制和偏差订正后更多的观测资料能够进入到同化系统中,说明改进的土壤湿度初值条件下观测算子的计算值得到正的调整,对低层地表通道的改进效果明显,尤其以50.3 GHz的窗区通道3的结果最为理想;针对此次强降水过程中24 h累积降水分布的模拟结果,CLSMDAS输出土壤湿度初值条件下同化AMSU-A资料,能够较为准确的把握整个雨带的走向、大雨以上级别降水的落区范围、降水中心落区及强度等。说明准确的土壤湿度初值能够改进卫星辐射率资料的同化结果,进而提高数值模式的模拟预报能力。  相似文献   

6.
为提高卫星资料在同化系统中的利用率及验证卫星微波资料对区域数值预报效果的影响,本文以2008年8月1-31日为研究时段,利用WRF模式及其WRF-3DVAR同化模块,设计并构建了卫星微波资料的快速循环同化方案,分析循环同化方案对数值预报的改进效果.结果表明,相比于单时次同化,循环同化方案使各预报要素的相关系数在一定程度上得到改善,均方差也呈现减小的趋势.此外,对研究时段内暴雨和台风个例的具体分析显示,循环同化方案能够有效改善降水和台风路径的预报.  相似文献   

7.
卫星云导风资料应用于伴随同化系统的数值试验研究   总被引:1,自引:1,他引:1  
以2002年6月14日00时至15日00时发生在江南、华南一带的暴雨过程为例,利用MM5伴随模式同化系统,同化常规观测资料以及卫星云导风资料,研究MM5伴随模式对降水预报的改善以及云导风资料对于提高暴雨预报的作用。设计了4种数值试验方案,试验结果表明:MM5伴随同化系统对降水预报有较好的改善作用;GMS-5卫星云导风资料的加入增加了高空风场资料,将其同化到伴随同化系统中能有效改善模式初始场,提高了降水预报质量,特别对暴雨强降水的预报起到了较好的改善作用。  相似文献   

8.
ATOVS资料同化方案对暴雨模拟效果的影响   总被引:4,自引:2,他引:2  
张斌  张立凤  熊春晖 《大气科学》2014,38(5):1017-1027
本文利用WRF 模式及其3DVar 同化系统,以2009 年6 月29 日00 时到30 日00 时的湖北鹤峰暴雨为研究个例,对ATOVS 探测器的AMSU-A、AMSU-B 和HIRS 三类资料进行了不同的同化方案试验。结果表明:同化ATOVS 三类资料对暴雨模拟的影响不同,HIRS 资料对暴雨模拟效果改进最大,AMSU-B 次之,AMSU-A 最小。同时同化ATOVS 三类资料时,AMSU-A 资料起主要作用,其同化效果与同时同化ATOVS 三类资料相近,优化组合同化AMSU-B 和HIRS 资料的效果最好。同化ATOVS 不同资料对初始要素场的影响不同,AMSU-A 资料主要影响大气温度场,AMSU-B 资料对中高空要素场的影响较大,HIRS 资料对低空湿度场及风场的协同改变最有利于降水模拟的改善。同时ATOVS 资料的稀疏分辨率也是影响同化效果的一个因子,在模式分辨率不变时,同化资料稀疏分辨率可能存在最佳选择。  相似文献   

9.
风云三号(03)批是我国第二代极轨业务气象卫星的第三个批次,由上午、下午、晨昏和降水测量四颗业务卫星组成。其中,我国首发的降水测量卫星计划装载双频降水测量雷达、微波成像仪、GNSS掩星探测仪和光学成像仪。通过仿真技术,分析风云三号降水测量卫星的功能、性能和设计指标,探讨其降水探测能力。分析表明,风云三号降水测量卫星装载的降水测量雷达从设计层面分析,与美日第二代降水测量卫星GPM搭载的降水雷达DPR性能相当;风云三号降水测量卫星的轨道设计覆盖了南、北纬50°范围内的热带和中纬地区,对影响我国区域的台风系统结构具有三维探测能力;风云三号降水测量卫星上装载的被动微波辐射计相比GPM搭载的微波成像仪增加了50~60和118GHz双氧吸收通道,对陆地弱降水反演等具有应用潜力。总之,风云三号降水测量卫星加上同星配置的其他载荷,整星的降水探测能力优于美日第二代降水测量卫星GPM。  相似文献   

10.
MWHS/FY-3资料同化在四川盆地暴雨预报中的应用研究   总被引:1,自引:0,他引:1       下载免费PDF全文
为了研究同化风云三号B星(FY-3B)和C星(FY-3C)的微波湿度计(MWHS及MWHS-2)观测资料在四川暴雨数值预报中的影响,本文基于Weather Research and Forecasting Model(WRF)及其三维变分同化系统Weather Research Forecast Variatinal Data Assimilation System(WRFDA),实现了对MWHS/FY-3B和MWHS-2/FY-3C观测资料的直接同化。针对2018年7月的一次四川盆地区域性暴雨过程的同化试验结果表明:同化风云三号系列卫星的微波湿度计观测资料对试验开始时刻均有改善,对相对湿度和矢量风场等物理量场有一定的正向调整作用,尤其是同化MWHS-2/FY-3C资料对风场的调整较为明显。同化试验对龙门山北部降水有较明显的改善作用,改善了降水的分布与落区,其中同化MWHS/FY-3B对盆地中部到东北部的降水量级的预报更接近实况,雨区更为连续。同化试验证明了同化风云三号系列卫星的微波湿度计观测资料对于四川盆地暴雨数值预报有一定的业务应用价值。   相似文献   

11.
The Advanced Microwave Sounding Unit-A(AMSU-A) onboard the NOAA satellites NOAA-18 and NOAA-19 and the European Organization for the Exploitation of Meteorological Satellites(EUMETSAT)Met Op-A, the hyperspectral Atmospheric Infrared Sounder(AIRS) onboard Aqua, the High resolution Infra Red Sounder(HIRS) onboard NOAA-19 and Met Op-A, and the Advanced Technology Microwave Sounder(ATMS) onboard Suomi National Polar-orbiting Partnership(NPP) satellite provide upper-level sounding channels in tropical cyclone environments. Assimilation of these upper-level sounding channels data in the Hurricane Weather Research and Forecasting(HWRF) system with two different model tops is investigated for the tropical storms Debby and Beryl and hurricanes Sandy and Isaac that occurred in 2012. It is shown that the HWRF system with a higher model top allows more upper-level microwave and infrared sounding channels data to be assimilated into HWRF due to a more accurate upper-level background profile. The track and intensity forecasts produced by the HWRF data assimilation and forecast system with a higher model top are more accurate than those with a lower model top.  相似文献   

12.
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   

13.
基于WRF(Weather Research Forecast)模式和GSI(Gridpoint Statistical Interpolation)同化系统,研究了同化4部多普勒雷达探测资料对"7.21"北京特大暴雨过程中降水预报的改善作用。GSI系统直接同化径向风,而采用云分析的方式间接同化反射率。2012年7月20日21时—21日00时(世界时)雷达探测资料同化试验采用30 min循环同化径向风和反射率资料。结果表明,循环同化雷达探测资料改善了短时(0—6 h)和短期(0—24 h)降水预报,ETS评分提高了约0.2。同化反射率资料增加了初始场的水凝物,改善了温度场分布,直接影响了降水的形成,同时还使650—250 hPa位势高度的均方根误差平均降低了8 gpm。直接同化径向风资料对中尺度风场产生了一定影响。ETS评分结果表明:同化反射率资料的效果要优于同化径向风。  相似文献   

14.
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   

15.
Assimilating satellite radiances into Numerical Weather Prediction (NWP) models has become an important approach to increase the accuracy of numerical weather forecasting. In this study, the assimilation technique scheme was employed in NOAA’s STMAS (Space-Time Multiscale Analysis System) to assimilate AMSU-A radiances data. Channel selection sensitivity experiments were conducted on assimilated satellite data in the first place. Then, real case analysis of AMSU-A data assimilation was performed. The analysis results showed that, following assimilating of AMSU-A channels 5–11 in STMAS, the objective function quickly converged, and the channel vertical response was consistent with the AMSU-A weighting function distribution, which suggests that the channels can be used in the assimilation of satellite data in STMAS. With the case of the Typhoon Morakot in Taiwan Island in August 2009 as an example, experiments on assimilated and unassimilated AMSU-A radiances data were designed to analyze the impact of the assimilation of satellite data on STMAS. The results demonstrated that assimilation of AMSU-A data provided more accurate prediction of the precipitation region and intensity, and especially, it improved the 0–6h precipitation forecast significantly.  相似文献   

16.
In the past, satellite observations of the microwave radiation emitted from the atmosphere have been directly utilized for deriving the climate tends of vertical-layer-averaged atmospheric temperatures. This study presents the 30-year atmospheric temperature trend derived by one-dimensional variational (1D-Var) data assimilation of Microwave Sounding Unit/Advanced Microwave Sounding Unit-A (MSU/AMSU-A) observations. Firstly, the radiance measurements from MSU on board the early National Oceanic and Atmospheric Administration (NOAA)-6 to NOAA-14 and AMSU-A on board NOAA-15 to -19 have been inter-calibrated to form a fundamental climate data record. A 1D-Var method is then employed to establish the thematic climate data record of atmospheric temperature profiles that are appropriate for climate change study. Verification of the MSU/AMSU-A derived temperature profiles with collocated Global Positioning System radio occultation data confirms a reasonable good accuracy of the derived atmospheric temperature profiles in the troposphere and low stratosphere. Finally, the global climate trend of the atmospheric temperature in clear-sky conditions is deduced, showing not only a global warming in the troposphere and a cooling in the stratosphere, but also a stronger warming in the upper troposphere than in the low troposphere.  相似文献   

17.
Summary ?NCEP multi-sensor hourly rainfall data were used for data assimilation and evaluation of quantitative precipitation forecasts (QPFs) through a case study of a squall line on April 5, 1999. Improvements in QPFs were obtained through direct assimilation of these rainfall observations using 4-dimensional variational assimilation (4D-Var). Inclusion of the observed no-rain information was shown to be beneficial to QPFs. While the penalty constraint applying a digital filter was effective in removing high frequency oscillations introduced by rainfall assimilation and produced a smoother “optimal” initial condition, its impact on QPFs is mixed. Sensitivity studies indicated that the adjustments in the moisture and temperature fields resulted from precipitation assimilation played a more important role than those of other state variables for improving QPFs. Received October 27, 2001; accepted January 30, 2002  相似文献   

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