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1.
Extending an earlier study, the best track minimum sea level pressure (MSLP) data are assimilated for landfalling Hurricane Ike (2008) using an ensemble Kalman filter (EnKF), in addition to data from two coastal ground-based Doppler radars, at a 4-km grid spacing. Treated as a sea level pressure observation, the MSLP assimilation by the EnKF enhances the hurricane warm core structure and results in a stronger and deeper analyzed vortex than that in the GFS (Global Forecast System) analysis; it also improves the subsequent 18-h hurricane intensity and track forecasts. With a 2-h total assimilation window length, the assimilation of MSLP data interpolated to 10-min intervals results in more balanced analyses with smaller subsequent forecast error growth and better intensity and track forecasts than when the data are assimilated every 60 minutes. Radar data are always assimilated at 10-min intervals. For both intensity and track forecasts, assimilating MSLP only outperforms assimilating radar reflectivity (Z) only. For intensity forecast, assimilating MSLP at 10-min intervals outperforms radar radial wind (Vr) data (assimilated at 10-min intervals), but assimilating MSLP at 60-min intervals fails to beat Vr data. For track forecast, MSLP assimilation has a slightly (noticeably) larger positive impact than Vr(Z) data. When Vr or Z is combined with MSLP, both intensity and track forecasts are improved more than the assimilation of individual observation type. When the total assimilation window length is reduced to 1h or less, the assimilation of MSLP alone even at 10-min intervals produces poorer 18-h intensity forecasts than assimilating Vr only, indicating that many assimilation cycles are needed to establish balanced analyses when MSLP data alone are assimilated; this is due to the very limited pieces of information that MSLP data provide.  相似文献   

2.
Atmospheric Infra Red Sounder(AIRS) measurements are a valuable supplement to current observational data, especially over the oceans where conventional data are sparse. In this study, two types of AIRS-retrieved temperature and moisture profiles, the AIRS Science Team product(Sci Sup) and the single field-of-view(SFOV) research product, were evaluated with European Centre for Medium-Range Weather Forecasts(ECMWF) analysis data over the Atlantic Ocean during Hurricane Ike(2008) and Hurricane Irene(2011). The evaluation results showed that both types of AIRS profiles agreed well with the ECMWF analysis, especially between 200 h Pa and 700 h Pa. The average standard deviation of both temperature profiles was approximately 1 K under 200 h Pa, where the mean AIRS temperature profile from the AIRS Sci Sup retrievals was slightly colder than that from the AIRS SFOV retrievals. The mean Sci Sup moisture profile was slightly drier than that from the SFOV in the mid troposphere. A series of data assimilation and forecast experiments was then conducted with the Advanced Research version of the Weather Research and Forecasting(WRF) model and its three-dimensional variational(3DVAR) data assimilation system for hurricanes Ike and Irene. The results showed an improvement in the hurricane track due to the assimilation of AIRS clear-sky temperature profiles in the hurricane environment. In terms of total precipitable water and rainfall forecasts, the hurricane moisture environment was found to be affected by the AIRS sounding assimilation.Meanwhile, improving hurricane intensity forecasts through assimilating AIRS profiles remains a challenge for further study.  相似文献   

3.
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4.
The present study is conducted to verify the short-range forecasts from mesoscale model version5 (MM5)/weather research and forecasting (WRF) model over the Indian region and to examine the impact of assimilation of quick scatterometer (QSCAT) near surface winds, spectral sensor microwave imager (SSM/I) wind speed and total precipitable water (TPW) on the forecasts by these models using their three-dimensional variational (3D-Var) data assimilation scheme for a 1-month period during July 2006. The control (without satellite data assimilation) as well as 3D-Var sensitivity experiments (with assimilating satellite data) using MM5/WRF were made for 48 h starting daily at 0000 UTC July 2006. The control run is analyzed for the intercomparison of MM5/WRF short-range forecasts and is also used as a baseline for assessing the MM5/WRF 3D-Var satellite data sensitivity experiments. As compared to the observation, the MM5 (WRF) control simulations strengthened (weakened) the cross equatorial flow over southern Arabian sea near peninsular India. The forecasts from MM5 and WRF showed a warm and moist bias at lower and upper levels with a cold bias at the middle level, which shows that the convective schemes of these models may be too active during the simulation. The forecast errors in predicted wind, temperature and humidity at different levels are lesser in WRF as compared to MM5, except the temperature prediction at lower level. The rainfall pattern and prediction skill from day 1 and day 2 forecasts by WRF is superior to MM5. The spatial distribution of forecast impact for wind, temperature, and humidity from 1-month assimilation experiments during July 2006 demonstrated that on average, for 24 and 48-h forecasts, the satellite data improved the MM5/WRF initial condition, so that model errors in predicted meteorological fields got reduced. Among the experiments, MM5/WRF wind speed prediction is most benefited from QSCAT surface wind and SSM/I TPW assimilation while temperature and humidity prediction is mostly improved due to latter. The largest improvement in MM5/WRF rainfall prediction is due to the assimilation of SSM/I TPW. The assimilation of SSM/I wind speed alone in MM5/WRF degraded the humidity and rainfall prediction. In summary the assimilation of satellite data showed similar impact on MM5/WRF prediction; largest improvement due to SSM/I TPW and degradation due to SSM/I wind speed.  相似文献   

5.
The system of the cyclic assimilation of data on atmospheric conditions used in the West Siberian Administration for Hydrometeorology and Environmental Monitoring is described. It is based on the WRF-ARW mesoscale atmospheric model and on the WRF 3D-Var system of the three-dimensional variational analysis of data. The system is verified when the first approximation data (6-hour forecast) and WRF-ARW forecasts with the lead time up to 24 hours are compared with the observational data. The problems of assimilation of observations from the AMSU-A and AIRS satellite instruments are considered. The effect of using AMSU-A and AIRS for the analysis in the Novosibirsk region is estimated. The experiments demonstrated that the cyclic data assimilation system operates successfully. The AMSU-A observations improve the quality of analyses and forecasts in winter. In summer the impact of satellite observations on the forecast skill scores is ambiguous. Good short-term forecasts are provided by the initial conditions obtained using the system of detailing of the NCEP large-scale analysis.  相似文献   

6.
Specifying physically consistent and accurate initial conditions is one of the major challenges of numerical weather prediction (NWP) models. In this study, ground-based global positioning system (GPS) integrated water vapor (IWV) measurements available from the International Global Navigation Satellite Systems (GNSS) Service (IGS) station in Bangalore, India, are used to assess the impact of GPS data on NWP model forecasts over southern India. Two experiments are performed with and without assimilation of GPS-retrieved IWV observations during the Indian winter monsoon period (November–December, 2012) using a four-dimensional variational (4D-Var) data assimilation method. Assimilation of GPS data improved the model IWV analysis as well as the subsequent forecasts. There is a positive impact of ～10 % over Bangalore and nearby regions. The Weather Research and Forecasting (WRF) model-predicted 24-h surface temperature forecasts have also improved when compared with observations. Small but significant improvements were found in the rainfall forecasts compared to control experiments.  相似文献   

7.
An ensemble Kalman filter (EnKF) combined with the Advanced Research Weather Research and Forecasting model (WRF) is cycled and evaluated for western North Pacific (WNP) typhoons of year 2016. Conventional in situ data, radiance observations, and tropical cyclone (TC) minimum sea level pressure (SLP) are assimilated every 6 h using an 80-member ensemble. For all TC categories, the 6-h ensemble priors from the WRF/EnKF system have an appropriate amount of variance for TC tracks but have insufficient variance for TC intensity. The 6-h ensemble priors from the WRF/EnKF system tend to overestimate the intensity for weak storms but underestimate the intensity for strong storms. The 5-d deterministic forecasts launched from the ensemble mean analyses of WRF/EnKF are compared to the NCEP and ECMWF operational control forecasts. Results show that the WRF/EnKF forecasts generally have larger track errors than the NCEP and ECMWF forecasts for all TC categories because the regional simulation cannot represent the large-scale environment better than the global simulation. The WRF/EnKF forecasts produce smaller intensity errors and biases than the NCEP and ECMWF forecasts for typhoons, but the opposite is true for tropical storms and severe tropical storms. The 5-d ensemble forecasts from the WRF/EnKF system for seven typhoon cases show appropriate variance for TC track and intensity with short forecast lead times but have insufficient spread with long forecast lead times. The WRF/EnKF system provides better ensemble forecasts and higher predictability for TC intensity than the NCEP and ECMWF ensemble forecasts.  相似文献   

8.
文中采用WRF非静力数值预报模式及其三维变分同化系统(WRF3D-Var),对2006年1月13—14日发生在华北地区及山东半岛的一次大雾过程进行了包括GTS(Global Telecommunication System)资料、AMDAR(Aircraft Meteorological Data Relay)资料和9210资料的不同资料组合的三维变分同化试验,以及时间间隔分别为6、3和1h不同时间频率的循环同化试验,并以同化分析场为初始场进行了36h的模拟试验。对同化分析场和模拟结果进行了分析,分析结果表明,采用三维变分方法同化AMDAR等多种非常规观测资料后,分析场均有明显的改变,对雾区的模拟结果也有局部不同程度的修正。进一步分析起修正作用的原因得知同化资料后对低层的湿度和层结趋稳性有所改善。同化GTS资料对低层的增湿贡献明显,但对层结趋稳性贡献不大;而同化AMDAR资料主要使层结趋稳性明显,对增湿无贡献;9210资料对低层湿度和层结趋稳性均有贡献。不同时间间隔的循环同化试验表明,多时次的循环同化比单时次的同化分析增量要大,逐时循环同化与6和3h循环同化相比,可明显改善模拟效果。  相似文献   

9.
自动站资料在WRF 3DVAR中的同化敏感性试验   总被引：1，自引：0，他引：1  
为了了解国家级地面自动观测站不同观测要素对数值预报作用,利用WRF三维变分同化系统对自动站资料的不同观测要素开展同化＆预报试验。两个月的数值预报检验结果表明：1）只同化自动站温度观测对位势高度、温度和相对湿度场预报的影响作用最大,且主要为负作用,而同化气压或风向风速观测对上述要素预报影响作用比同化温度小,但会改善位势高度预报和部分温度预报,对相对湿度预报改善作用不明显;2）对于降水预报,同化风向风速方案的评分结果最差,同化温度的方案次之,同化气压的方案可以改善24h降水预报结果。由此看出用WRF 3DVAR同化地面观测资料时,气压观测十分重要,同时也说明要想用好地面观测资料,让其为数值预报提高发挥最大作用仍需开展很多研究工作。  相似文献   

10.
雷达反射率资料的三维变分同化研究   总被引：6，自引：3，他引：3  
范水勇  王洪利  陈敏  高华 《气象学报》2013,71(3):527-537
应用天气研究和预报模式(WRF)三维变分系统中一种新的雷达反射率资料间接同化方法来进行反射率资料的三维变分同化研究,评估雷达反射率资料对夏季短时定量降水预报的作用.该方法不直接同化雷达反射率资料,而是同化由反射率资料反演出的雨水和估计的水汽.以2009年夏季北京地区发生的4次强降水过程为例,考察了北京市气象局业务运行的快速更新循环同化预报系统对京津冀地区雷达网的雷达反射率资料的同化性能以及雷达反射率资料和径向风资料同时同化的效果.数值试验结果表明:(1)同化反演雨水或水汽都能改善降水预报,但同化反演水汽对降水预报效果的改善起了更重要的作用;(2)同化反射率资料能极大地提高短时降水预报的效果,其稳定的正面效果可以延伸到6h的预报时效,而同化径向风资料不能得到稳定的正效果;(3)同化雷达资料时,应用快速更新循环同化预报系统是提高短时定量降水预报的一个有效途径.  相似文献   

11.
In this study, the impact of various types of observations on the track forecast of Tropical Cyclone (TC) Jangmi (200815) is examined by using the Weather Research and Forecasting (WRF) model and the corresponding three-dimensional variational (3DVAR) data assimilation system. TC Jangmi is a recurving typhoon that is observed as part of the THORPEX Pacific Asian Regional Campaign (T-PARC). Conventional observations from the Korea Meteorological Administration (KMA) and targeted dropsonde observations from the Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR) were used for a series of observation system experiments (OSEs). We found that the assimilation of observations in oceanic areas is important to analyze environmental flows (such as the North Pacific high) and to predict the recurvature of TC Jangmi. The assimilation of targeted dropsonde observations (DROP) results in a significant impact on the track forecast. Observations of ocean surface winds (QSCAT) and satellite temperature soundings (SATEM) also contribute positively to the track forecast, especially two- to three-day forecasts. The impact of sensitivity guidance such as real-time singular vectors (SVs) was evaluated in additional experiments.  相似文献   

12.
The Weather Research and Forecasting (WRF-ARW) model and its three-dimensional variational data assimilation (3D-Var) system are used to investigate the impact of the Advanced Microwave Sounding Unit-A (AMSU-A) radiances on the prediction of Indian Ocean tropical cyclones. Three tropical cyclones are selected for this study: cyclone Mala (April 2006; Bay of Bengal), cyclone Gonu (June 2007; Arabian Sea), and cyclone Sidr (November 2007; Bay of Bengal). For each case, observing system experiments are designed, by producing two sets of analyses from which forecasts are initialized. Both sets of analyses contain all conventional and satellite observations operationally used, including, but not limited to, Quick Scatterometer (QuikSCAT) surface winds, Special Sensor Microwave/Imager (SSM/I) surface winds, Meteosat-derived atmospheric motion vectors (AMVs), and differ only in the exclusion (CNT) or inclusion (EXP) of AMSU-A radiances. Results show that the assimilation of AMSU-A radiances changes the large-scale thermodynamic structure of the atmosphere, and also produce a stronger warm core. These changes cause large forecast track improvements. In particular, without AMSU-A assimilation, most forecasts do not produce landfall. On the contrary, the forecasts initialized from improved EXP analyses in which AMSU-A data are included produce realistic landfall. In addition, intensity forecast is also improved. Even if the analyzed cyclone intensity is not affected by the assimilation of AMSU-A radiances, the predicted intensity improves substantially because of the development of warm cores which, through creation of stronger gradients, helps the model in producing intense low centre pressure.  相似文献   

13.
为评价静止卫星大气温度廓线产品资料同化对飓风预报的影响,以2018年飓风“迈克尔”为例,选用GOES-16温度廓线产品,开展静止卫星资料同化及其对飓风预报影响的研究。首先,通过评估温度廓线产品精度,选取质量较好的高度层并以统计的各层均方根误差作为观测误差用于同化试验;然后,利用WRF-3DVar系统进行不同稀疏化及不同同化频次的循环同化敏感性试验;最后,利用WRF模式开展24 h数值预报。试验结果表明,在飓风“迈克尔”期间温度廓线在200~1 000 hPa之间的误差在2 K以内,将水平分辨率稀疏化为模式分辨率的6倍且循环同化频次为6 h时同化该资料对模式的初始场有最为合理的改进,从大尺度环境场上看使模式具备更合理的环流形势,能够有效提高对飓风的路径及强度的预报效果,更准确地模拟降水落区及美国佛罗里达州等降水关键区域的雨强。   相似文献   

14.
同化多普勒雷达风资料的两种方法比较   总被引：11，自引：5，他引：11  
以美国新近研发的天气研究预报模式(WRF)配置的三维变分同化系统WRF 3D-Var为平台,比较了两种不同的同化多普勒雷达径向风资料的方法。一种是WRF 3D-Var系统现有的径向风资料直接同化方法;另一种是首先用两步变分法由多普勒资料反演出水平风,再同化反演风场。针对2003年7月4~5日的一次淮河暴雨过程进行的同化试验结果表明,同化了雷达风资料后得到的水平风场包含了更多的中尺度特征;从降水预报评分和预报的雷达回波来看,两种方法都能够明显改进降水预报,这种正作用能维持6 h左右;相对而言,同化反演的水平风场的效果略优于直接同化雷达径向风的效果。  相似文献   

15.
The impact of applying three-dimensional variational data assimilation (3D-Var DA) on convective-scale forecasts is investigated by using two mesoscale models, the Weather Research and Forecasting model (WRF-ARW) and the Hirlam and Aladin Research Model On Non-hydrostatic-forecast Inside Europe (HARMONIE-AROME). One month (1 to 30 December 2013) of numerical experiments were conducted with these two models at 2.5 km horizontal resolution, in order to partly resolve convective phenomena, on the same domain over a mountainous area in Iran and neighboring areas. Furthermore, in order to estimate the domain specific background error statistics (BES) in convective scales, two months (1 November to 30 December 2017) of numerical experiments were carried out with both models by downscaling operational ECMWF forecasts. For setting the numerical experiments in an operational scenario, ECMWF operational forecast data were used as initial and lateral boundary conditions (ICs/LBCs). In order to examine the impact of data assimilation, the 3D-Var method in cycling mode was adopted and the forecasts were verified every 6 hours up to 36 hours for selected meteorological variables. In addition, 24 h accumulated precipitation forecasts were verified separately. Generally, the WRF and HARMONIE-AROME exhibit similar verification statistics for the selected forecast variables. The impact of DA on the numerical forecast shows some evidence of improvement in both models, and this effect decreases severely at longer lead times. Results from verifying the 24 h convective-scale precipitation forecasts from both models with and without DA suggest the superiority of the WRF model in forecasting more accurately the occurred precipitation over the simulation domain, even for the downscaling run.  相似文献   

16.
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   

17.
Weather Research and Forecasting (WRF-ARW) model and its three-dimensional variational data assimilation (3D-Var) system are used to investigate the impact of the Quick Scatterometer (QuikSCAT) near surface winds, Special Sensor Microwave/Imager (SSM/I)-derived Total Precipitable Water (TPW), and Meteosat-7-derived Atmospheric Motion Vectors (AMVs) on the track and intensity prediction of tropical cyclones over the North Indian Ocean. The case of tropical cyclone, Gonu (June 2007; Arabian Sea), is first tested and the results show significant improvements particularly due to the assimilation of QuikSCAT winds. Three other cases, cyclone Mala (April 2006; Bay of Bengal), Orissa super cyclone (October 1999; Bay of Bengal), and Very Severe Cyclonic storm (October 1999; Bay of Bengal), are then examined. The prediction of cyclone tracks improved significantly with the assimilation of QuikSCAT winds. The track improvement resulted from the relocation of the initial cyclonic vortices after the assimilation of QuikSCAT wind vectors. After the assimilation of QuikSCAT winds, the mean (for four cyclone cases) track errors for first, second, and third day forecasts are reduced to 72, 101, and 166?km, respectively, from 190, 250, and 381?km of control (without QuikSCAT winds) runs. The assimilation of QuikSCAT winds also shows positive impact on the intensity (in terms of maximum surface level winds) prediction particularly for those cyclones, which are at their initial stages of the developments at the time of data assimilation. The assimilation of SSM/I TPW has significant influence (negative and positive) on the cyclone track. In three of the four cases, the assimilation of the SSM/I TPW resulted in drying of lower troposphere over cyclonic region. This decrease of moisture in TPW assimilation experiment resulted in reduction of cyclonic intensity. In three of the four cyclones, the assimilation of Meteosat-7 AMVs shows negative impact on the track prediction.  相似文献   

18.
Nonhydrostatic mesoscale WRF and its 3D-Var system are used to study a dense fog event occurring in 13-14 January 2006. Three different observation data sets including GTS （Global Telecommunication System）, AMDAR （Aircraft Meteorological Data Relay） data, and 9210 data are assimilated into the initial analysis fields in experiments. Experiments with three different assimilation time intervals （1, 3, and 6 h） are also carried out. Three experiments with different data sets have all modified the temperature and humidity field of initial fields, and therefore show an obvious positive effect on fog simulation. Further study indicates that the humidity and stability of boundary layer are improved obviously in assimilation experiments, although different data sets make different contribution to the analysis fields. The multi-time assimilation cycle experiments show that the analysis increment in experiment with l-h interval is more realistic than that with 3- and 6-h intervals.  相似文献   

19.
采用不同样本集合同化地面观测对一次飑线过程的影响   总被引：2，自引：1，他引：1  
针对夏季黄淮地区一次飑线过程,利用WRF (Weather Research and Forecasting) 模式及其Hybrid ETKF-3DVAR同化系统,考察不同生成方案的样本对同化地面观测的影响。集合样本创建方式包括3类:扰动初始背景场的方案 (RCV)、使用不同的物理参数化方案 (PPMP) 以及前两者集成方案 (BLE)。基于增量场分析,同化地面观测主要调整850 hPa以下水平风和水汽混合比的空间结构,其中RCV方案侧重于改变水平风的空间分布,PPMP方案侧重于改变水汽混合比的空间结构,BLE方案兼具二者特征。同化地面观测可以间接改善6 h降水预报,其中PPMP试验的降水预报最好,尤其是对降水位置和强度的预报。对比雷达回波观测,RCV试验和BLE试验对弓状回波模拟得较好,BLE试验的模拟较多体现RCV特征。PPMP试验和RCV试验还可改变冷池的位置和强度,同时影响飑线出现和消亡时间,相对而言,PPMP试验影响更大。  相似文献   

20.
The impact of assimilating radiances from the Advanced Microwave Sounding Unit-A (AMSU-A) on the track prediction of Typhoon Megi (2010) was studied using the Weather Research and Forecasting (WRF) model and a hybrid ensemble three-dimensional variational (En3DVAR) data assimilation (DA) system. The influences of tuning the length scale and variance scale factors related to the static background error covariance (BEC) on the track forecast of the typhoon were studied. The results show that, in typhoon radiance data assimilation, a moderate length scale factor improves the prediction of the typhoon track. The assimilation of AMSU-A radiances using 3DVAR had a slight positive impact on track forecasts, even when the static BEC was carefully tuned to optimize its performance. When the hybrid DA was employed, the track forecast was significantly improved, especially for the sharp northward turn after crossing the Philippines, with the flow-dependent ensemble covariance. The flow-dependent BEC can be estimated by the hybrid DA and was capable of adjusting the position of the typhoon systematically. The impacts of the typhoon-specific BEC derived from ensemble forecasts were revealed by comparing the analysis increments and forecasts generated by the hybrid DA and 3DVAR. Additionally, for 24 h forecasts, the hybrid DA experiment with use of the full flow-dependent background error substantially outperformed 3DVAR in terms of the horizontal winds and temperature in the lower and mid-troposphere and for moisture at all levels.  相似文献   

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