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1.
Improved tropical cyclone forecasts over north Indian Ocean with direct assimilation of AMSU-A radiances 总被引：1，自引：0，他引：1
Randhir Singh C. M. Kishtawal P. K. Pal P. C. Joshi 《Meteorology and Atmospheric Physics》2012,115(1-2):15-34
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
2.
Tropical cyclone track and intensity prediction: The generation and assimilation of high-density, satellite-derived data 总被引：1，自引：0，他引：1
J. F. Le Marshall L. M. Leslie R. F. Abbey Jr. L. Qi 《Meteorology and Atmospheric Physics》2002,80(1-4):43-57
Summary The impact of recent scientific and technological advances in tropical cyclone track, intensity and structure modeling is
discussed. Since the early 1990s, developments have occurred in remote sensing, data assimilation procedures, numerical models
and high performance computing. In particular, there is now quasi-continuous high spatial and temporal resolution data coverage
over the previously data-sparse oceans where tropical cyclones spend most of their life cycles. There has been a rapid development
of data assimilation methodologies capable of using these data to initialize high-resolution prediction models. Model developments
have reached a stage of maturity where the representation of many of the physical processes necessary for improved tropical
cyclone track and intensity prediction are now included. Finally, available computer power has reached the teraflop range.
Most operational centers have high performance computers capable of tropical cyclone modeling at resolutions necessary for
skillful track and intensity simulations.
This article focuses on combining all of the above developments in a tropical cyclone data analysis and prediction system.
The system has produced statistically significant reductions in the mean forecast error statistics for tropical cyclone track
predictions and resulted in far more realistic simulations of tropical cyclone intensity and structure. A large number of
tropical cyclones have been modeled, with emphasis on those classified as being “difficult” storms to predict accurately.
These difficult storms are most responsible for rapidly growing forecast errors. Our results are illustrated by case studies
of such tropical cyclones.
Received October 9, 2001 Revised December 28, 2001 相似文献
3.
Assimilation of the multisatellite data into the WRF model for track and intensity simulation of the Indian Ocean tropical cyclones 总被引：2，自引：1，他引：1
Randhir Singh C. M. Kishtawal P. K. Pal P. C. Joshi 《Meteorology and Atmospheric Physics》2011,111(3-4):103-119
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
4.
In this study, both reflectivity and radial velocity are assimilated into the Weather Research and Forecasting (WRF) model using ARPS 3DVAR technique and cloud analysis procedure for analysis and very short range forecast of cyclone ÁILA. Doppler weather radar (DWR) data from Kolkata radar are assimilated for numerical simulation of landfalling tropical cyclone. Results show that the structure of cyclone AILA has significantly improved when radar data is assimilated. Radar reflectivity data assimilation has strong influence on hydrometeor structures of the initial vortex and precipitation pattern and relatively less influence is observed on the wind fields. Divergence/convergence conditions over cyclone inner-core area in the low-to-middle troposphere (600–900 hPa) are significantly improved when wind data are assimilated. However, less impact is observed on the moisture field. Analysed minimum sea level pressure (SLP) is improved significantly when both reflectivity and wind data assimilated simultaneously (RAD-ZVr experiment), using ARPS 3DVAR technique. In this experiment, the centre of cyclone is relocated very close to the observed position and the system maintains its intensity for longer duration. As compared to other experiments track errors are much reduced and predicted track is very much closer to the best track in RAD-ZVr experiment. Rainfall pattern and amount of rainfall are better captured in this experiment. The study also reveals that cyclone structure, intensification, direction of movement, speed and location of cyclone are significantly improved and different stages of system are best captured when both radar reflectivity and wind data are assimilated using ARPS 3DVAR technique and cloud analysis procedure. Thus optimal impact of radar data is realized in RAD-ZVr experiment. The impact of DWR data reduces after 12 h forecast and it is due to the dominance of the flow from large-scale global forecast system model. Successful coupling of data assimilation package ARPS 3DVAR with WRF model for Indian DWR data is also demonstrated. 相似文献
5.
本文利用三维变分同化系统（WRFDA）,设计了4个同化试验方案,将ATOVS卫星亮温资料直接同化到中尺度数值模式（WRF）中,研究同化ATOVS不同卫星亮温资料对2009年04号热带风暴“浪卡”数值模拟的影响。结果表明,直接同化卫星亮温资料能够改善初始场结构（大气流场、温度场）,尤其是对西太平洋反气旋系统,进而提高对热带气旋路径的模拟精度。同化不同类型的ATOVS卫星亮温资料对于热带气旋的移动路径有着不同程度的改善,其中以HIRS3和HIRS4资料同化对热带气旋移动路径改善效果最好。 相似文献
6.
The super cyclone in October 1999 was the most intense tropical cyclone in the last century in Orissa, a coastal state in India. This state was battered for more than two days by strong winds and intense rain killing thousands of people. The main objective of this study is to examine the impact of total precipitable water content (TPWC) and surface wind speed data from sensors on board the Tropical Rainfall Measuring Mission (TRMM), Defense Meteorological Satellite Project (DMSP), and Indian Remote Sensing Satellite (OceanSat-I) satellites on the data assimilation system at NCMRWF, New Delhi during the Orissa cyclone period. Comparison of various assimilation experiments suggests that the utilization of TRMM Microwave Imager (TMI) data in the assimilation produced the best analyses. However, in all the forecasts, the storm was predicted to weaken and did not have a reasonably good track. Assimilation experiments with the other two satellite data showed the cyclone track much to the south of the observed track and also it was a weak storm. Biases in the data, when compared with each other, are evident in the analyses also. Better analyses are obtained when the satellite data are used in the originally obtained resolution than when reduced by averaging. A forecast experiment with assimilated data, utilizing the Cloud Motion Vectors (CMVs) from METEOSAT along with TMI data, produced the best forecast among all the experiments. However, the forecast quality was poor. A high-resolution data assimilation experiment was carried out to see the impact of model resolution on the analyses of the cyclone. The strength of the cyclone further increased when higher resolution TMI data were included. The study highlights the need for more satellite data over the Indian Ocean, where conventional data coverage is too poor to define the vertical structure of the atmosphere. 相似文献
7.
目前中国气象局全球集合预报系统（China Meteorological Administration Global Ensemble Prediction System,CMA-GEPS）利用CMA全球数值预报系统分析场计算奇异向量（ANSV）,欧洲中期天气预报中心采用同化背景场计算奇异向量（FCSV）,在业务流程上先于计算ANSV,可优化集合预报系统运行时间。为此,在CMA-GEPS中探索采用FCSV进行集合预报的可行性,分析ANSV和FCSV的空间分布及相似指数,进而针对夏秋季节10个个例开展采用ANSV和FCSV的全球集合预报试验,从等压面要素集合预报技巧、中国地区24 h累积降水概率预报技巧、台风路径集合预报技巧、台风中心最低海平面气压预报技巧等方面对比二者结果。结果表明:ANSV和FCSV的主要结构特征相似,两组集合预报结果相当,表明在CMA-GEPS中使用FCSV可行,可作为未来高分辨率CMA-GEPS业务系统建设的选项。 相似文献
8.
Application of Nonlinear Balance Scheme in Three-Dimensional Variational Data Assimilation 总被引：1，自引：1，他引：1 
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下载免费PDF全文 The dynamical constrains in three-dimensional variational data assimilation are discussed when consid- ering the impact of stream divergence and convergence on the pressure and wind fields.For the analysis of severe tropical cyclone,frontal structures,and other rapidly changing structures,the geostrophic balance and linear balance cannot properly represent the relationship between wind and pressure fields.However,the nonlinear balance incremental equation takes into account the information of flow-dependent background, and makes response to the flow-dependent background covariance in the 3D-Var system.Results indicate that the application of the nonlinear balance equation to 3D-Var system improves the quality of severe trop- ical cyclone assimilation system,which has some positive effects on intensity prediction of tropical cyclones. 相似文献
9.
J. Le Marshall 《Meteorology and Atmospheric Physics》1998,65(3-4):141-151
Summary Tropical cyclone track prediction remains a vexing problem in meteorology, particularly for numerical weather prediction. While there has been significant improvement in forecast skill in recent years, errors in prognosis, particularly for recurving cyclones still remain unacceptably high. Consistent with track prediction being to a significant extent an initial value problem, there has been, in recent years, cogent evidence that, a combination of high resolution numerical modelling, the use of appropriate assimilation techniques and the exploitation of high spatial and temporal resolution observations can improve the accuracy of tropical cyclone forecasts.Before landfall, tropical cyclones have their genesis and move over the data-sparse tropical oceans. Here the prediction of their movement is an application for which remotely sensed data are quintessential. In this context, this paper examines the increasingly important contribution of cloud and water vapour motion vectors to tropical cyclone prediction and evaluates their import to accurate prediction in terms of both the numerical modelling characteristics and the data assimilation techniques employed.Overall, it is shown that cloud and water vapour drift winds have made a significant contribution to the tropical cyclone track forecasting problem when used with conventional intermittent assimilation techniques, such as 6-hourly cycling, and, more recently, with continuous assimilation techniques such as 3- and 4-dimensional variational assimilation. These continuous assimilation schemes appear to have the potential to use near continuous asynoptic wind data in the most effective way.With 3 Figures 相似文献
10.
基于副热带奇异向量的初值扰动方法已应用于GRAPES （Global and Regional Assimilation PrEdiction System）全球集合预报系统,但存在热带气旋预报路径离散度不足的问题。通过分析发现,热带气旋附近区域初值扰动结构不合理导致预报集合不能较好地估计热带气旋预报的不确定性,是路径集合离散度不足的可能原因之一。通过建立热带气旋奇异向量求解方案,将热带气旋奇异向量和副热带奇异向量共同线性组合生成初值扰动,以弥补热带气旋区域初值扰动结构不合理这一缺陷,进而改进热带气旋集合预报效果。利用GRAPES全球奇异向量计算方案,以台风中心10个经纬度区域为目标区构建热带气旋奇异向量求解方案,针对台风“榕树”个例进行集合预报试验,并开展批量试验,利用中国中央气象台最优台风路径和中国国家气象信息中心的降水观测资料进行检验,对比分析热带气旋奇异向量结构特征和初值扰动特征,评估热带气旋奇异向量对热带气旋路径集合预报和中国区域24 h累计降水概率预报技巧的影响。结果表明,热带气旋奇异向量具有局地化特征,使用热带气旋奇异向量之后,热带气旋路径离散度增加,路径集合平均预报误差和离散度的关系得到改善,路径集合平均预报误差有所减小,集合成员更好地描述了热带气旋路径的预报不确定性;中国台风降水的小雨、中雨、大雨、暴雨各量级24 h累计降水概率预报技巧均有一定提高。总之,当在初值扰动的生成中考虑热带气旋奇异向量后,可改进热带气旋初值扰动结果,并有助于改善热带气旋路径集合预报效果。 相似文献
11.
S. K. Roy Bhowmik Soma Sen Roy Kuldeep Srivastava B. Mukhopadhay S. B. Thampi Y. K. Reddy Hari Singh S. Venkateswarlu Sourav Adhikary 《Meteorology and Atmospheric Physics》2011,111(3-4):133-147
This paper demonstrates the usefulness of Indian Doppler Weather Radar (DWR) data for nowcasting applications, and assimilation into a mesoscale Numerical Weather Prediction (NWP) model. Warning Decision Support System Integrated Information (WDSS-II) developed by National Severe Storm Laboratory (NSSL) and Advanced Regional Prediction System (ARPS) developed at the Centre for Analysis and Prediction, University of Oklahoma are used for this purpose. The study reveals that the WDSS-II software is capable of detecting and removing anomalous propagation echoes from the Indian DWR data. The software can be used to track storm cells and mesocyclones through successive scans. Radar reflectivity mosaics are created for a land-falling tropical cyclone??Khaimuk of 14 November 2008 over the Bay of Bengal using observations from three DWR stations, namely, Visakhapatnam, Machilipatnam and Chennai. Assimilation of the quality-controlled radar data (DWR, Chennai) of the WDSS-II software in a very high-resolution NWP model (ARPS) has a positive impact for improving mesoscale prediction. This has been demonstrated for a land-falling tropical cyclone Nisha of 27 November 2008 of Tamil Nadu coast. This paper also discusses the optimum scan strategy and networking considerations. This work illustrates an important step of transforming research to operation. 相似文献
12.
A hybrid GSI (Grid-point Statistical Interpolation)-ETKF (Ensemble Transform Kalman Filter) data assimilation system has been recently developed for the WRF (Weather Research and Forecasting) model and tested with simulated observations for tropical cyclone (TC) forecast. This system is based on the existing GSI but with ensemble background information incorporated. As a follow-up, this work extends the new system to assimilate real observations to further understand the hybrid scheme. As a first effort to explore the system with real observations, relatively coarse grid resolution (27 km) is used. A case study of typhoon Muifa (2011) is performed to assimilate real observations including conventional in-situ and satellite data. The hybrid system with flow-dependent ensemble covariance shows significant improvements with respect to track forecast compared to the standard GSI system which in theory is three dimensional variational analysis (3DVAR). By comparing the analyses, analysis increments and forecasts, the hybrid system is found to be potentially able to recognize the existence of TC vortex, adjust its position systematically, better describe the asymmetric structure of typhoon Muifa and maintain the dynamic and thermodynamic balance in typhoon initial field. In addition, a cold-start hybrid approach by using the global ensembles to provide flow-dependent error is tested and similar results are revealed with those from cycled GSI-ETKF approach. 相似文献
13.
Previous studies showed that 4 D-Var technique used for data assimilation could be modified for weather control. This study demonstrates the ability of 4 D-Var to influence the future path of a tropical cyclone by calculating perturbations in WRF simulation. Given the background error covariance matrix, the initial field is improved by the vortex dynamic initialization technique. Our results show that 4 D-Var can be applied to control the trajectory of simulated tropical cyclones by producing "optimal" perturbations. In the numerical simulation experiment of Typhoon Mitag in 2019, after this kind of weather control similar to data assimilation, the tropical cyclone moved obviously,and the damaging wind over the coastline weakened. The prediction results after the initial field modified by 4 D-Var have a great change, and the position of the tropical cyclone moved about 0.5° southeastward after assimilation,which misses the southeast coast of China. Moreover, the damaging wind is also weakened. Since the 4 D-Var is premised on the assumption that the model is perfect and does not consider the model error, then the research plan to consider model error and introduce new methods is discussed in the paper. 相似文献
14.
近30年影响我国东南沿海的热带气旋降水强度变化特征分析 总被引：3，自引：0，他引：3
利用中国地面台站逐日降水资料和中国气象局上海台风研究所整编的热带气旋最佳路径资料研究了1978～2007年影响我国热带气旋降水强度的变化及其对我国东南沿海盛夏降水变化的影响.近30年影响我国东南沿海盛夏的热带气旋降水增加是导致我国东南沿海盛夏降水显著增加的主要原因.仅从热带气旋降水来看,东南沿海和内陆(包括江西、湖南东部和湖北南部)热带气旋降水强度显著增加,而影响热带气旋降水频次略有增加.通过对雨量站与引起降水热带气旋的中心距离的变化分析发现:内陆地区影响热带气旋距离显著下降,近距离热带气旋引起降水的增加,是该区域热带气旋降水强度增加的主要来源;而东南沿海地区近距离热带气旋降水增加不明显,热带气旋降水强度的增加主要由于同距离热带气旋降水强度的增加.热带气旋经过频次的空间的变化结果证实,近30年经过中国沿海的TC个数变化不大,仅福建沿海一带略有增加,而内陆地区则增加明显,且经过该区域时热带气旋移动速度变慢,这均与该区域近距离热带气旋降水的增加一致. 相似文献
15.
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：3，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
16.
A hybrid grid-point statistical interpolation-ensemble transform Kalman filter (GSI-ETKF) data assimilation system for the Weather Research and Forecasting (WRF) model was developed and applied to typhoon track forecast with simulated dropsonde observations. This hybrid system showed significantly improved results with respect to tropical cyclone track forecast compared to the standard GSI system in the case of Muifa in 2011. Further analyses revealed that the flow-dependent ensemble covariance was the major contributor to the better performance of the GSI-ETKF system than the standard GSI system; the GSI-ETKF system was found to be potentially able to adjust the position of the typhoon vortex systematically and better update the environmental field. 相似文献
17.
18.
该文提出一种西北太平洋热带气旋年生成活动的客观预测模型。研究大尺度环境因子对西北太平洋热带气旋年生成频次的作用,使用最小角回归算法对初始14个预测因子进行选择和降维,将资料集分为训练集(1979—2015年)和验证集(2016—2020年),建立随机森林回归模型预测热带气旋年生成频次。分析环境因子对西北太平洋热带气旋生成位置的作用,使用逐步回归算法筛选影响显著的预测因子,建立局部泊松回归模型预测热带气旋生成空间位置的概率。结果表明:随机森林回归模型可以预测西北热带气旋频次的主要变化和趋势,揭示环境因子对西北太平洋热带气旋年生成频次的影响。局部泊松回归模型对于气旋生成位置概率有一定预测能力。利用随机森林回归模型和局部泊松回归模型模拟1979—2020年西北太平洋热带气旋生成,结果与观测基本一致,可见模型可为热带气旋危险性分析提供参考。 相似文献
19.
20.
利用中国气象局提供的1951—2018年台风最佳路径数据集,筛选经过江苏的热带气旋个例,发现历史上所有经过江苏的热带气旋都发生在夏秋季节。基于春季130种气候信号指数,利用C4.5决策树算法建立“台风是否经过江苏”的预测模型。结果表明:基于C4.5算法的决策树能够较为直观且准确地对每年“台风是否经过江苏”进行预测。利用1951—2000年(51 a)的数据样本进行训练,学习准确率达到82%,利用2001—2018年(18 a)的数据样本对模型进行泛化能力测试,测试准确率达到83.3%,最后利用2019年第9号热带气旋“利奇马”经过江苏的事实进行个例检验,符合决策树规则C。可以证明C4.5算法对“台风是否经过江苏”的预测具有较高的准确率和通用性。 相似文献