Assimilation of the multisatellite data into the WRF model for track and intensity simulation of the Indian Ocean tropical cyclones

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.     

Assimilating AMSU-a radiance data with the WRF hybrid En3DVAR system for track predictions of Typhoon Megi (2010)

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.     

Changes in the frequency of tropical cyclones over the North Indian Ocean

Summary  Changes in the frequency of tropical cyclones developing over the Arabian Sea and the Bay of Bengal have been studied utilizing 122 year (1877–1998) data of tropical cyclone frequency. There have been significant increasing trends in the cyclone frequency over the Bay of Bengal during November and May which are main cyclone months. During transitional monsoon months; June and September however, the frequency has decreased. The results have been presented for five months, i.e., May-November which are relevant as far as tropical cyclone frequency over the Arabian Sea and the Bay of Bengal are concerned. The tropical cyclone frequency in the Arabian Sea has not shown any significant trend, probably due to small normal frequency. The frequency time series has been subjected to the spectral analysis to obtain the significant periods. The cyclone frequency over the Bay of Bengal during May has shown a 29 year cycle. A significant 44 year cycle has been found during November. Over the Arabian Sea significant cycles of 13 and 10 years have been observed during May-June and November, respectively. The tropical cyclone frequency in the North Indian Ocean has a prominent El Ni?o-Southern Oscillation (ENSO) scale cycle (2–5 years) during all above five months. The annual cyclone frequency exhibits 29 year and ENSO scale (2–4 years) oscillations. There is a reduction in tropical cyclone activity over the Bay of Bengal in severe cyclone months May and November during warm phases of ENSO. Examination of the frequencies of severe cyclones with maximum sustained winds ≥ 48 knots has revealed that these cyclones have become more frequent in the North Indian Ocean during intense cyclone period of the year. The rate of intensification of tropical disturbances to severe cyclone stage has registered an upward trend. Received June 7, 1999/Revised March 20, 2000     

Cloud and water vapour motion vectors in tropical cyclone track forecasting — A review

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     

Sensitivity of physical parameterizations on prediction of tropical cyclone Nargis over the Bay of Bengal using WRF model

Comprehensive sensitivity analyses on physical parameterization schemes of Weather Research Forecast (WRF-ARW core) model have been carried out for the prediction of track and intensity of tropical cyclones by taking the example of cyclone Nargis, which formed over the Bay of Bengal and hit Myanmar on 02 May 2008, causing widespread damages in terms of human and economic losses. The model performances are also evaluated with different initial conditions of 12?h intervals starting from the cyclogenesis to the near landfall time. The initial and boundary conditions for all the model simulations are drawn from the global operational analysis and forecast products of National Center for Environmental Prediction (NCEP-GFS) available for the public at 1° lon/lat resolution. The results of the sensitivity analyses indicate that a combination of non-local parabolic type exchange coefficient PBL scheme of Yonsei University (YSU), deep and shallow convection scheme with mass flux approach for cumulus parameterization (Kain-Fritsch), and NCEP operational cloud microphysics scheme with diagnostic mixed phase processes (Ferrier), predicts better track and intensity as compared against the Joint Typhoon Warning Center (JTWC) estimates. Further, the final choice of the physical parameterization schemes selected from the above sensitivity experiments is used for model integration with different initial conditions. The results reveal that the cyclone track, intensity and time of landfall are well simulated by the model with an average intensity error of about 8?hPa, maximum wind error of 12?m?s^?1and track error of 77?km. The simulations also show that the landfall time error and intensity error are decreasing with delayed initial condition, suggesting that the model forecast is more dependable when the cyclone approaches the coast. The distribution and intensity of rainfall are also well simulated by the model and comparable with the TRMM estimates.     

The relationship between wet component of atmospheric refractivity and movement and landfall of tropical cyclone in the Bay of Bengal region

In this paper, a simple relationship is employed to investigate the relative impacts on the movement and landfall of tropical cyclone in the Bay of Bengal region when wet component of atmospheric refractivity of different tropospheric levels is used as an input. Four tropical cyclones during pre-monsoon and post-monsoon season over the Bay of Bengal region were selected for the study. The radiosonde/radiowind data of coastal stations, namely Kolkata (Dumdum), Agartala, Bhubaneswar, Visakhapatnam, Machlipatnam, Chennai and Karaikal, were collected for the period of the cyclones under study. The wet component of atmospheric refractivity of different standard levels was plotted against time for the stations for every cyclone. The study suggests that the cyclone moves towards and crosses near the station having a relatively steeper increase in the wet component of atmospheric refractivity up to mid-tropical level. A possible explanation is also presented.     

1977-2008年北印度洋热带气旋统计特征分析

采用美国联合台风警报中心（JTWC）提供的北印度洋1977-2008年热带气旋资料、NOAA提供的1982-2008年高分辨率合成资料和NCEP提供的1982-2008年全球再分析资料,对北印度洋上167个热带气旋个例进行了统计分析,结果表明：1）北印度洋热带气旋通常发生在阿拉伯海东部和孟加拉湾中部,阿拉伯海上活动的热...     

登陆热带气旋长久维持与迅速消亡的大尺度环流特征

采用动态合成分析方法 ,对登陆后长久维持热带气旋 (LTC)和迅速消亡热带气旋 (STC)的大尺度环流特征进行合成分析和动力诊断。研究表明 :(1)LTC登陆后 ,在一个长波槽前有向偏北移动靠近中纬度斜压锋区的趋势 ,而STC登陆后 ,无长波槽靠近 ,并远离中纬度斜压锋区 ;(2 )LTC登陆后 ,仍与一支低空急流水汽输送通道连结 ,而STC登陆后很快与这支水汽通道分离 ;(3)LTC登陆后逐渐变性 ,获取斜压能量 ,其环境风垂直切变增强 ,Δζ2 0 0 -850负值增大 ,而STC登陆后没有这样的特征 ;(4 )LTC登陆后 ,其高层与中纬度急流靠近 ,增强了其向东北方向的高空流出气流 ,而STC不存在这样一支流出气流 ;(5 )LTC登陆后 ,摩擦使其能量耗损 ,但从中高层环境中获得了能量 ,而STC登陆后 ,有同样的能耗却无明显的环境能量补给。因此 ,当一个热带气旋登陆后 ,从其移动趋势、与水汽通道的连结、与斜压锋区的关系和高空流出气流等特征 ,可以初步判断其是长久维持还是迅速衰减。     

Skill of synthetic superensemble hurricane forecasts for the Canadian maritime provinces

Summary From 1994 to 2003, fifty-five tropical cyclones entered the Canadian Hurricane Centre (CHC) Response Zone, or about 42% of all named Atlantic tropical cyclones in this ten-year period, and 2003 was the fourth consecutive year for a tropical cyclone to make landfall in Canada. The CHC forecasts all tropical cyclones that enter the CHC Response Zone and assumes the lead in forecasting once the cyclone enters its area of forecast responsibility. This study acknowledges the challenges of forecasting such tropical cyclones at extratropical latitudes. If a tropical cyclone has been declared extratropical, global models may no longer use vortex bogussing to carry the cyclone, and even if it is modeled, large model errors often result. The purpose of this study is to develop a new version of the Florida State University (FSU) hurricane superensemble with greater skill in tracking tropical cyclones, especially at extratropical latitudes. This has been achieved from the development of the synthetic superensemble, which is similar to the operational version of the multi-model superensemble that is used at FSU. The synthetic superensemble differs in that is has a larger set of member models consisting of regular member models, synthetic versions of these models, and the operational superensemble and its synthetic version. This synthetic superensemble is being used here to forecast hurricane tracks from the 2001, 2002, and 2003 hurricane seasons. The track forecasts from this method have generally less error than those of the member models, the operational superensemble, and the ensemble mean. This study shows that the synthetic superensemble performs consistently well and would be an asset to operational hurricane track forecasting.     

Analyses of Orissa Super Cyclone using TRMM (TMI), DMSP (SSM/I) and OceanSat-I (MSMR) Derived Data

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.     

登陆热带气旋与夏季风相互作用对暴雨的影响

利用《热带气旋年鉴》资料、NCEP/NCAR再分析资料采用动态合成分析方法,研究了登陆热带气旋降水与夏季风急流之间的关系,同时对登陆热带气旋与夏季风急流发生相互作用的典型个例强热带风暴Bilis (0604) 利用数值模拟方法研究了二者之间的相互作用对暴雨的影响。结果表明:登陆后造成大范围强降水的热带气旋往往与低层急流长时间相连,其水汽通量和潜热能显著大于弱降水热带气旋。数值试验结果表明:夏季风低空急流向热带气旋输送水汽对热带气旋结构维持有利,当水汽输送被截断后,热带气旋气旋性结构被破坏,强降水减弱、范围明显缩小;季风急流风速增强时可增加水汽通量输送,使得强降水范围增加、强度增强;在夏季风影响背景下,热带气旋在陆上的移动改变水汽和不稳定能量的分布,而热带气旋本身独特的动力结构使得强降水强度增加。     

登陆热带气旋研究的进展

随着大气探测技术的发展 ,登陆热带气旋研究已经成为热带气旋研究中一个新的领域。新的探测技术能初步揭示出热带气旋登陆过程中发生的多种改变。近年来 ,国内外科学家实施了一系列外场科学试验 (Fieldscientificexperi ments) ,对登陆热带气旋进行探测和研究 ,旨在提高预报的准确率。登陆热带气旋研究内容包括 :海岸和内陆山脉地形影响 ,结构和强度变化 ,登陆热带气旋的暴雨强度和分布 ,大风强度和分布 ,风暴潮强度和范围 ,登陆热带气旋在陆上的维持机制 ,陆地涡旋的路径和入海加强 ,边界层结构 ,陆面过程和能量交换 ,变性过程等。研究采用外场科学试验与数值模拟相结合的方法。模拟或预报模式中使用同化资料尤其是卫星同化资料来构造初值场 ,取得较好结果。登陆热带气旋的研究目前正在展开 ,并取得了一些重要结果。研究表明 ,潜热释放和斜压位能释放是近海或登陆热带气旋加强或维持的两种主要能源。这两种能量可分别从水汽输送和热带气旋与中纬度环流的相互作用中获得。另外 ,陆面饱和湿地或水面的潜热输送、热带气旋与中尺度涡旋或热带云团的合并以及高空流出气流强辐散也对其加强和维持有利。世界气象组织的热带气象研究计划 (TMRP)正在组织对这一领域的总结和下一步的研究计划。这项研究将对预报和     

2013年欧洲中心台风集合预报的检验

广州中心气象台利用中国气象局下发的欧洲中心台风集合预报数据,制作了台风集合预报产品,供业务参考应用。利用欧洲中心台风集合预报数据,对2013年1307—1331号热带气旋的集合预报路径和强度进行检验,通过对比集合平均、模式高分辨率确定性预报和预报员主观预报,发现路径集合平均在24~120 h预报误差最小;在有限的预报样本数中,从热带风暴到台风级别的热带气旋,各预报时效路径集合平均的误差随强度增强而减小;强引导气流背景下的热带气旋预报误差小于弱引导气流的误差。对比强度集合平均和模式高分辨率确定性预报,发现各时效集合平均的误差比确定性预报大,随着预报时效的延长误差没有明显增大或减小的趋势,而且强度集合平均预报,在中心最低气压、中心最大风速、热带气旋等级都表现出明显的系统性偏弱特征;对不同级别的热带气旋强度预报,集合平均的误差随强度增强而增大,即强度集合预报对强度较弱的热带气旋有更高的准确率;对比受强、弱引导气流影响的两类热带气旋,集合平均对受弱引导气流影响的一类预报误差更小。     

Improved tropical cyclone intensity and intensity spread prediction in bifurcation situations

Bifurcation or bi-modal tropical cyclone intensity forecasts may arise due to uncertainty in the timing of formation, timing and magnitude of rapid intensification periods, or track forecast uncertainty leading to landfall or non-landfall or leading to interaction with warm- or cold-ocean eddies. An objective technique is developed and tested to detect these intensity bifurcation situations in our weighted-analog intensity (WANI) forecasts that are based on the 10 best historical analogs to the Joint Typhoon Warning Center (JTWC) official track forecasts. About 19% of the overall sample of 1136 WANI forecasts in the western North Pacific during the 2010–2012 seasons met the criteria for a substantial intensity bifurcation situation. Using a hierarchical clustering technique, two clusters of the 10 best analogs are defined and separate WANI forecasts and intensity spreads are calculated for the two clusters. If an always perfect selection of the correct cluster WANI forecast of each bifurcation situation is made, a substantial improvement in the intensity mean absolute errors is achieved relative to the original WANI forecasts based on all 10 of the best analogs. These perfect-cluster selection WANI forecasts have smaller bias errors and are more highly correlated with the verifying intensities at all forecast intervals through 120 h. Without further bias correction and calibration, the cluster WANI intensity spreads are under-determined as the Probability of Detections are smaller than the desired 68%. Four examples of WANI cluster predictions of intensity bifurcation situations are provided to illustrate how a correct choice of the intensity forecast and the intensity spread can be the basis for improved warnings of the threat from western North Pacific tropical cyclones.     

A PRELIMINARY STUDY ON THE 3DVAR ASSIMILATION OF THE AMSU-A DATA IN SPACE-TIME MULTISCALE ANALYSIS SYSTEM

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.     

Further experiments on cyclone track prediction with a quasi-Lagrangian limited area model

Summary Results of an earlier study of cyclone track prediction using a quasi-Lagrangian model (QLM) to generate track forecasts of up to 36 hours were reported by Prasad and Rama Rao (2003). Further experiments to produce track forecasts of up to 72 hours with an updated version of the same model have been carried out in the present study. In this case, the ability of the model to predict recent historical cyclones in the Bay of Bengal and Arabian Sea has been assessed. Analysis of some of the structural features of analyzed and predicted fields has been carried out. Such fields include wind distribution and vertical motion around the cyclone centre. In addition, the merging of an idealized vortex with the large scale initial fields provided by a global model, has been carried out for a particular case study of a May 1997 storm, which hit the Bangladesh coast. This current study has demonstrated that the model generates a realistic structure of a tropical cyclone with an idealized vortex. Performance evaluation has been carried out by computing the direct position errors (DPE). The results of which show that the mean error for a 24 h forecast is about 122 km, which increases to about 256 km for a 48 h forecast and 286 km for a 72 h forecast. These figures are comparable to similar errors in respect of tropical cyclone forecasts produced by an advanced NWP centre, viz., the UKMO global model during the corresponding period, 1997–2000 (obtained from UKMO web site). The average forecast errors of the UKMO model are 160 km for 24 h, 265 km for 48 h, 415 km for 72 h forecast ranges.     

Tropical cyclone track and intensity prediction: The generation and assimilation of high-density, satellite-derived data

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     

Satellite Data Assimilation of Upper-Level Sounding Channels in HWRF with Two Different Model Tops

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.     

孟加拉湾热带风暴的初步分析

本文利用14年孟咖拉湾热带风暴资料,给出了其概况,分析了引起孟加拉湾热带风暴的活动双峰型特征的原因及多热带风暴月和无热带风暴月的环境流场。     

热带气旋路径集合预报试验

以MM5模式为试验模式，分别用增长模繁殖法（BGM）和模式物理过程扰（MPP）形成12个集合成员，对2005年登陆我国的8个热带气旋进行了52次路径集合预报试验，以寻找适合西北太平洋热带气旋路径的集合预报方法。结果表明:BGM方法的集合预报结果总体上好于控制试验结果，其中对强度较弱的热带气旋的集合预报效果更好。MPP方法的集合预报结果总体上不如控制试验结果，但对初始时刻强度达到台风的热带气旋的集合预报效果较好，集合预报相对于控制试验的改进效果明显。基于BGM方法和MPP方法集合预报的不同特点，将两种方法相结合形成扰动成员，这一综合方法的集合预报效果好于单一方法的集合预报效果。BGM方法和MPP方法的系统发散度总体上都偏小。