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1.
This study explored the impact of coastal radar observability on the forecast of the track and rainfall of Typhoon Morakot(2009)using a WRF-based ensemble Kalman filter(EnKF)data assimilation(DA)system.The results showed that the performance of radar EnKF DA was quite sensitive to the number of radars being assimilated and the DA timing relative to the landfall of the tropical cyclone(TC).It was found that assimilating radial velocity(Vr)data from all the four operational radars during the 6 h immediately before TC landfall was quite important for the track and rainfall forecasts after the TC made landfall.The TC track forecast error could be decreased by about 43% and the 24-h rainfall forecast skill could be almost tripled.Assimilating Vr data from a single radar outperformed the experiment without DA, though with less improvement compared to the multiple-radar DA experiment.Different forecast performances were obtained by assimilating different radars, which was closely related to the first-time wind analysis increment, the location of moisture transport, the quasi-stationary rainband, and the local convergence line.However, only assimilating Vr data when the TC was farther away from making landfall might worsen TC track and rainfall forecasts.Besides, this work also demonstrated that Vr data from multiple radars, instead of a single radar, should be used for verification to obtain a more reliable assessment of the EnKF performance.  相似文献   

2.
This study evaluates the impact of atmospheric observations from the Tropospheric Airborne Meteorological Data Reporting (TAMDAR) observing system on numerical weather prediction of hurricane Ike (2008) using three-dimensional data assimilation system for the Weather Research and Forecast (WRF) model (WRF 3D-Var). The TAMDAR data assimilation capability is added to WRF 3D-Var by incorporating the TAMDAR observation operator and corresponding observation processing procedure. Two 6-h cycling data assimilation and forecast experiments are conducted. Track and intensity forecasts are verified against the best track data from the National Hurricane Center. The results show that, on average, assimilating TAMDAR observations has a positive impact on the forecasts of hurricane Ike. The TAMDAR data assimilation reduces the track errors by about 30 km for 72-h forecasts. Improvements in intensity forecasts are also seen after four 6-h data assimilation cycles. Diagnostics show that assimilation of TAMDAR data improves subtropical ridge and steering flow in regions along Ike’s track, resulting in better forecasts.  相似文献   

3.
基于WRF中尺度模式,采用集合卡尔曼滤波方法同化中国岸基多普勒天气雷达径向速度资料,对2015年登陆台风彩虹（1522）进行数值试验。从台风强度、路径、结构等方面验证了同化效果,并对不同区域雷达观测资料的同化敏感性进行讨论。试验结果表明:在同化窗内同化分析场台风位置误差相比未同化平均减小15 km,最多时刻减小38 km,同化资料时次越多,确定性预报路径误差越小。同化雷达资料后较好地反映出台风彩虹（1522）近海加强过程,台风中心最低气压同化分析和预报误差相比未同化最大减小超过25 hPa,台风眼的尺度、眼墙处对流非对称结构相比未同化与观测更加接近。试验还表明:台风内核100 km范围内的雷达观测对同化效果影响最大,仅同化这部分资料（约占总量的20%）各方面效果与同化全部资料相近,而仅同化100 km以外资料效果明显不及同化所有资料。仅同化台风内核雷达观测资料可以在不影响同化效果的前提下,使集合同化计算机时减小为原来的1/3,该策略可为台风实际业务预报提供一定参考。  相似文献   

4.
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   

5.
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   

6.
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   

7.
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   

8.
陆续  马旭林  王旭光 《大气科学》2015,39(6):1112-1122
随着气旋内部资料(Inner core data)在热带气旋预报中的使用,其重要性逐渐受到人们越来越多的关注。为了研究该资料中尾部机载雷达(Tail Doppler Radar,TDR)资料在业务系统中的应用效果,本文利用2012年飓风等级热带气旋Isaac期间的TDR资料,采用业务HWRF(Weather Research and Forecasting model for Hurricane)数值模式与业务GSI(Grid-point Statistical Interpolation system)三维变分同化(Three-Dimensional Variational Data Assimilation, 3DVar)系统对TDR资料进行了同化,展开了一系列预报试验,并对其效果进行了分析和研究。结果表明与HWRF的业务预报相比,GSI系统同化TDR资料后对热带气旋的路径和强度预报有明显改进;但其同化效果同时也表明业务三维变分中的静态背景误差协方差在TDR资料的应用中仍需要进一步的改进。  相似文献   

9.
探索了基于WRF模式的集合卡尔曼滤波同化方法（WRF-EnKF,简称EnKF）在近海有可能达到更强台风连续循环同化中国大陆高时空分辨率多普勒天气雷达径向风观测资料的效果,同时检验台风Vicente（2012）的三维结构演变及其动力学特征。通过短期集合预报得到跟随当前流场变化着的背景误差协方差的台风涡旋和动力学结构。研究发现,EnKF同化预报系统能有效地同化高时空分辨率雷达径向速度观测资料,显著改善初始场中台风Vicente的中小尺度内核结构,同时提高对台风Vicente的路径和强度及其相伴随的短期强降水预报。在台风最强时刻同化雷达径向风观测能快速（1~2 h）得到真实的暖核台风结构,同时进一步提高台风路径和强度的预报。另外,EnKF同化雷达径向风观测资料还能有效提高短期降水预报,1 h和3 h累积降水的分布、降水中心以及降水随时间演变都能得到显著改善,这与改善台风路径、结构和强度有密切关系。因此,对中国东南沿海有可能达到较强的台风进行同化雷达径向风观测资料可改善登陆台风的预报水平,这为利用我国地基多普勒天气雷达观测资料改善模式的初始场从而提高台风预报提供一定的指示作用。   相似文献   

10.
An hourly-cycling ensemble Kalman filter (EnKF) working at 2.5?km horizontal grid spacing is implemented over southern Ontario (Canada) to assimilate Meteorological Terminal Aviation Routine Weather Reports (METARs) in addition to the observations assimilated operationally at the Canadian Meteorological Centre. This high-resolution EnKF (HREnKF) system employs ensemble land analyses and perturbed roughness length to prevent an ensemble spread that is too small near the surface. The HREnKF then performs continuously for a four-day period, from which twelve-hour ensemble forecasts are launched every six hours. The impact on analyses and short-term forecasts of assimilating METAR data is given special attention.

It is shown that using ensemble land surface analyses increases near-surface ensemble spreads for temperature and specific humidity. Perturbing roughness length enlarges the spread for surface wind. Given sufficient ensemble spread, the four-day case study shows that the near-surface model state is brought closer to surface observations during the cycling process. The impact of assimilating surface data can also be seen at higher levels by using aircraft reports for verification. The ensemble forecast verification suggests that METAR data assimilation improves ensemble forecasts of air temperature and dewpoint near the surface up to a lead time of six hours or even longer. However, only minor improvement is found in surface wind forecasts.  相似文献   

11.
We applied the multigrid nonlinear least-squares four-dimensional variational assimilation(MG-NLS4DVar) method in data assimilation and prediction experiments for Typhoon Haikui(2012) using the Weather Research and Forecasting(WRF) model. Observation data included radial velocity(V_r) and reflectivity(Z) data from a single Doppler radar, quality controlled prior to assimilation. Typhoon prediction results were evaluated and compared between the NLS-4DVar and MG-NLS4DVar methods. Compared with a forecast that began with NCEP analysis data, our radar data assimilation results were clearly improved in terms of structure, intensity, track, and precipitation prediction for Typhoon Haikui(2012). The results showed that the assimilation accuracy of the NLS-4DVar method was similar to that of the MG-NLS4DVar method,but that the latter was more efficient. The assimilation of V_r alone and Z alone each improved predictions of typhoon intensity, track, and precipitation; however, the impacts of V_r data were significantly greater that those of Z data.Assimilation window-length sensitivity experiments showed that a 6-h assimilation window with 30-min assimilation intervals produced slightly better results than either a 3-h assimilation window with 15-min assimilation intervals or a 1-h assimilation window with 6-min assimilation intervals.  相似文献   

12.
The impact of assimilating Infrared Atmospheric Sounding Interferometer (IASI) radiance observations on the analyses and forecasts of Hurricane Maria (2011) and Typhoon Megi (2010) is assessed using Weather Research and Forecasting Data Assimilation (WRFDA). A cloud-detection scheme (McNally and Watts 2003) was implemented in WRFDA for cloud contamination detection for radiances measured by high spectral resolution infrared sounders. For both Hurricane Maria and Typhoon Megi, IASI radiances with channels around 15-μm CO2 band had consistent positive impact on the forecast skills for track, minimum sea level pressure, and maximum wind speed. For Typhoon Megi, the error reduction appeared to be more pronounced for track than for minimum sea level pressure and maximum wind. The sensitivity experiments with 6.7-μm H2O band were also conducted. The 6.7-μm band also had some positive impact on the track and minimum sea level pressure. The improvement for maximum wind speed forecasts from the 6.7-μm band was evident, especially for the first 42 h. The 15-μm band consistently improved specific humidity forecast and we found improved temperature and horizontal wind forecast on most levels. Generally, assimilating the 6.7-μm band degraded forecasts, likely indicating the inefficiency of the current WRF model and/or data assimilation system for assimilating these channels. IASI radiance assimilation apparently improved depiction of dynamic and thermodynamic vortex structures.  相似文献   

13.
Valuable dropsonde data were obtained from multiple field campaigns targeting tropical cyclones, namely Higos,Nangka, Saudel, and Atsani, over the western North Pacific by the Hong Kong Observatory and Taiwan Central Weather Bureau in 2020. The conditional nonlinear optimal perturbation(CNOP) method has been utilized in real-time to identify the sensitive regions for targeting observations adhering to the procedure of real-time field campaigns for the first time. The observing system experiments...  相似文献   

14.
基于集合Kalman滤波数据同化的热带气旋路径集合预报研究   总被引：1，自引：2，他引：1  
构建了一个基于集合Kalman滤波数据同化的热带气旋集合预报系统，通过积云参数化方案和边界层参数化方案的9个不同组合，采用MM5模式进行了不同时间的短时预报。对预报结果使用“镜像法”得到18个初始成员，为同化提供初始背景集合。将人造台风作为观测场，同化后的结果作为集合预报的初值，通过不同参数组合的MM5模式进行集合预报。对2003～2004年16个台风个例的分析表明，初始成员产生方法能够对热带气旋的要素场、中心强度和位置进行合理扰动。同化结果使台风强度得到加强，结构更接近实际。基于同化的集合路径预报结果要优于未同化的集合预报。使用“镜像法”增加集合成员提高了预报准确度，路径预报误差在48小时和72小时分别低于200 km和250 km。  相似文献   

15.
Intensity forecasting is one of the most challenging aspects of tropical cyclone (TC) forecasting. This work examines the impact of assimilating high-resolution all-sky infrared radiance observations from geostationary satellite GOES-13 on the convection-permitting initialization and prediction of Hurricane Joaquin (2015) with an ensemble Kalman filter (EnKF) based on the Weather Research and Forecasting (WRF) model. Given that almost all operational global and regional models struggled to capture Hurricane Joaquin (2015)’s intensity, this study examines the potential in improving Joaquin’s prediction when assimilating all-sky infrared radiances from GOES-13’s water vapor channel. It is demonstrated that, after a few 3-hour cycles assimilating all-sky radiance, the WRF model was able to forecast reasonably well Joaquin’s intensity, including its rapid intensification (RI). The improvement was largely due to a more realistic initial hurricane structure with a stronger, warmer, and more compact inner-core. Ensemble forecasts were used to further explore the important physical mechanisms driving the hurricane’s RI. Results showed that the RI forecasts were greatly impacted by the initial inner-core vortex structure.  相似文献   

16.
针对2018年9月17日发生在广东省佛山市的一次台风龙卷过程,对比分析了EnKF和变分方法同化X波段相控阵雷达得到的风场结构。结果表明,EnKF方法和变分方法在同化了X波段相控阵雷达资料之后,都可以得到龙卷母体风暴的涡旋特征。相比之下,EnKF同化分析的涡旋强度更强,台风龙卷母体风暴及其周边三维风场的结构更加完整,与回波结构匹配更好。变分方法同化得到的流场不够连续,台风龙卷母体风暴的涡旋强度偏弱,弱回波区入流也明显偏弱,并不符合概念模型。而两种方法在没有同化相控阵雷达数据时,都无法产生龙卷母体风暴的流场特征。总体而言,相对于变分方法,EnKF同化系统在同化X波段相控阵雷达数据后可以产生更为合理的涡旋结构,台风龙卷母体风暴及其周边动力场结构更合理,这为以后X波段相控阵雷达的业务应用提供了思路。  相似文献   

17.
为了检验不同观测资料在台风预报中的作用,以美国NCEP (National Centers for Environmental prediction)业务同化系统GSI (Grid Statistical Interpolation)为平台,选取2013年路径较复杂且登陆后降水持续较强的“潭美”台风过程为例,分别加入常规地面和高空观测资料、极轨卫星NOAA18、NOAA19、METOP-A和METOP-B资料,以及多普勒雷达基数据资料,探讨不同观测资料同化对台风的预报效果。同时,对台风采用Bogus初始化方案以及循环资料同化对台风路径和强度预报效果进行了对比分析。结果表明:常规观测资料对台风路径预报改善效果最明显,卫星资料的融入对海上台风路径的修正较好,而雷达资料则对台风登陆后的路径预报有改善;并且多源资料的融入效果最好。同时,采用Bogus方案可有效调整初始台风的位置和强度,从而对后期台风路径和强度预报有正效应。采用间隔6 h资料循环同化方法,可有效利用各时段资料,对台风路径和强度预报有较好的改善。   相似文献   

18.
The ocean surface wind(OSW) data retrieved from microwave scatterometers have high spatial accuracy and represent the only wind data assimilated by global numerical models on the ocean surface, thus playing an important role in improving the forecast skills of global medium-range weather prediction models. To improve the forecast skills of the Global/Regional Assimilation and Prediction System Global Forecast System(GRAPES＿GFS), the HY-2B OSW data is assimilated into the GRAPES＿GFS four-dimensio...  相似文献   

19.
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   

20.
集合卡尔曼滤波同化多普勒雷达资料的数值试验   总被引：35，自引：10，他引：25  
利用集合卡尔曼滤波(EnKF)在云数值模式中同化模拟多普勒雷达资料,并考察了不同条件下EnKF同化方法的性能.结果显示,经过几个同化周期后,EnKF分析结果非常接近真值.单多普勒雷达资料EnKF同化对雷达位置不太敏感,双雷达资料同化结果在同化的初期阶段比单雷达资料同化结果准确.同化由反射率导出的雨水比直接同化反射率资料更有效,联合同化径向速度和雨水有利于提高同化分析效果.协方差对EnKF同化效果起着非常重要的作用,考虑模式全部预报变量与径向速度协方差的同化效果比仅考虑速度场与径向速度协方差的同化效果好.雷达资料缺值降低了同化效果,此时增加地面常规观测资料的同化可以明显提高同化分析效果.EnKF同化技术对雷达观测资料误差不太敏感.初始集合对同化分析有较大影响.EnKF同化受集合大小和观测资料影响半径.同化对模式误差较敏感.利用EnKF同化双多普勒雷达资料,分析了一次梅雨锋暴雨过程的中尺度结构.结果表明,EnKF同化技术能够从双多普勒雷达资料反演暴雨中尺度系统的动力场、热力场和微物理场,反演的风场是较准确的,反演的热力场和微物理场分布也是基本合理的.中低层切变线是此次暴雨的主要动力特征,对流云表现为低层辐合、高层辐散并有垂直上升运动伴随,其热力特征表现为低层是低压区,高层为高压区,中部为暖区而上、下部为冷区,水汽、云水和雨水分别集中在对流云体内、上升气流区和强回波区.  相似文献   

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