Observation system experiments for Typhoon Jangmi (200815) observed during T-PARC

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.     

下投探空资料在台风莫拉克路径预报的应用试验

2009年8月7日中国大陆举行了首次利用机载下投式探空仪观测台风的试验,飞机在台风莫拉克与天鹅之间的云带相对稀薄区释放11个下投式探空仪。基于下投探空观测资料、常规探空资料和1°×1°分辨率的NCEP再分析资料,分析下投探空资料的可用性,并以下投探空资料初步分析了两台风间南海上空的风场、湿度场等大气特性;分别进行了有无以同化下投探空为初始场的GRAPES模式的模拟试验,以了解下投探空资料对台风莫拉克预报的影响作用。初步结论表明,台风天鹅与莫拉克之间的南海上空对流层中低层为深厚的西南气流,对流层低层及高层湿度小,中间层大;同化下投探空资料后,观测地区(下投探空点及其附近)800 hPa以下西南风减弱,以上加强,湿度中低层减小;有无同化下投探空资料的初值场差异随模式积分向下游传播,影响台风的环境场,改变了台风的引导气流:同化后500 hPa台风引导气流偏东、偏北分量加强,使台风的路径更接近实况路径,48 h台风路径预报误差比原来减少18%。     

Observation System Experiments for Typhoon Nida (2004) Using the CNOP Method and DOTSTAR Data

This study investigated the influence of dropwindsonde observations on typhoon forecasts. The study also evaluated the feasibility of the conditional nonlinear optimal perturbation (CNOP) method as a basis for sensitivity analysis of such forecasts. This sensitivity analysis could furnish guidance in the selection of targeted observations. The study was performed by conducting observation system experiments (OSEs). This research used the fifth-generation Mesoscale Model (MM5), the Weather Research and Forecasting (WRF) model, and dropsonde observations of Typhoon Nida at 1200 UTC 17 May 2004. The dropsondes were collected under the operational Dropsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR) program. In this research, five kinds of experiments were designed and conducted:(1) no observations were assimilated; (2) all observations were assimilated;(3) observations in the sensitive area revealed by the CNOP method were assimilated;(4) the same as in (3), but for the region revealed by the first singular vector (FSV) method;and (5) observations within a randomly selected area were assimilated. The OSEs showed that (1) the DOTSTAR data had a positive impact on the forecast of Nida’s track;(2) dropsondes in the sensitive areas identified by the MM5 CNOP and FSV remained effective for improving the track forecast for Nida on the WRF platform;and (3) the greatest improvement in the track forecast resulted from the CNOP-based (third) simulation, which indicated that the CNOP method would be useful in decision making about dropsonde deployments.     

Assimilation of GPM Microwave Imager Radiance for Track Prediction of Typhoon Cases with the WRF Hybrid En3DVAR System

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.     

Typhoon Track Forecast with a Hybrid GSI-ETKF Data Assimilation System

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.     

Uncertainty analysis using the WRF maximum likelihood ensemble filter system and comparison with dropwindsonde observations in Typhoon Sinlaku (2008)

In this study, the maximum likelihood ensemble filter (MLEF) is applied to a tropical cyclone case to identify the uncertainty areas in the context of targeting observations, using the WRF model. Typhoon Sinlaku (2008), from which dropwindsonde data are collected through THORPEX Pacific Asian Regional Campaign (TPARC), is selected for the case study. For the uncertainty analysis, a measurement called the deep layer mean (DLM) wind variance is employed. With assimilation of conventional rawinsonde data, the MLEF-WRF system demonstrated stable data assimilation performance over multiple data assimilation cycles and produced high uncertainties mostly in data-void areas, for the given tropical cyclone case. Dropwindsonde deployment through T-PARC turned out to occur inside or near the weak uncertainty areas that are identified through the MLEF-WRF system. The uncertainty analysis using the MLEF method can provide a guide for identifying more effective targeting observation areas.     

不同 AMDAR资料同化时间窗对台风“摩羯”预报影响研究

2018年第14号台风“摩羯”对山东造成了大范围暴雨和大风天气,基于WRF（Weather Research and Forecasting）模式及其Hybrid-3DVAR混合同化预报系统,对Hybrid-3DVAR不同集合协方差比例和不同航空气象数据转发（aircraft meteorological data relay,以下简称AMDAR）资料同化时间窗对台风“摩羯”预报的影响进行了数值研究。结果表明：加大集合协方差比例对台风“摩羯”路径预报有较大影响和改进;当全部取来自集合体的流依赖误差协方差时,预报的台风路径最好,降水预报也最接近实况;AMDAR资料同化对于台风路径和降水预报也有正的改进作用,但加大集合协方差比例到100%时对台风路径预报影响更大;不同资料同化时间窗会影响同化的AMDAR资料数量,从而影响台风降水精细化预报;45 min同化时间窗的要素预报误差最小,对台风造成的强降水精细特征预报最接近实况;不同资料同化时间窗主要影响台风降水预报落区分布,对台风路径预报影响相对较小。     

0920号超强台风“卢碧”引起的强海上大气波导成因分析与数值模拟研究

基于中国台湾地区主持的侵台台风之飞机侦察及下投式探空仪观测实验（Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region,DOTSTAR）获得的高分辨率下投式探空仪探测资料,分析了2003年9月—2012年8月所有发生在中国台湾地区附近海域的台风型大气波导事件,遴选出一次由0920号超强台风“卢碧”引起的强台风型海上大气波导过程作为研究对象。利用欧洲中期数值预报中心（ECMWF）再分析资料（水平分辨率0.125°×0.125°）,对此次波导的生成原因进行了分析;基于WRF模式比较了不同初始化方法对台风强度、尺度和周围台风型大气波导的模拟能力。结果表明,此次强台风型大气波导发生在台风环流西北侧外围的弱下沉运动区,其形成与850 hPa高度附近北方强干空气平流导致湿度随高度锐减密切相关。在数值模拟中运用台风动力初始化方法,可以有效改进台风强度、路径和尺度的模拟效果,进而有利于改善台风型大气波导尤其是波导层所在高度的模拟效果。台风外围出现的大气波导通常以悬空波导为主,模拟效果与台风螺旋雨带和内核尺度的模拟关系密切,而与台风强度和眼墙结构关系不大。中尺度数值模式WRF具有模拟台风型大气波导的能力,是研究台风型大气波导的有力手段。      

散射计和下投式探空仪资料对台风模拟的影响

为了评估同化QuikSCAT海平面气压场资料和Dropsonde资料对台风"Bilis"和"Kat-rina"模拟的影响,通过WRF-3DVAR变分同化系统将QuikSCAT海平面气压场资料和Dropsonde资料同化到WRF模式中,并以未同化任何资料和同化了QuikSCAT海平面气压场以及同化了Drop-sonde资料的数据为初始场,应用WRF模式进行模拟预报,并对得到的初始分析场和模拟预报得到的结果与台风实况报文进行了对比,得到的结论是:对台风初始时刻海平面气压场分布、初始台风中心定位、台风初始暖心结构的改善、台风路径、海平面最低气压场、海面最大风速和雷达回波的模拟方面,同化QuikSCAT海平面气压场的效果比同化Dropsonde资料明显,其中二者对海平面最低气压场的改进效果比海面最大风速的要好。但是两种资料的同化对初始相对湿度和台风强度细节变化方面都没有产生明显改善作用。同化QuikSCAT海平面气压场试验虽然仅仅同化了单层海平面气压场,但是在三维变分同化系统的动力约束作用下,也可以影响到中高层的各个要素场。     

SEA SURFACE TEMPERATURE RESPONSE TO TYPHOON MORAKOT(2009) AND ITS INFLUENCE

While previous studies indicate that typhoons can decrease sea surface temperature(SST) along their tracks, a few studies suggest that the cooling patterns in coastal areas are different from those in the open sea. However, little is known about how the induced cooling coupled with the complex ocean circulation in the coastal areas can affect tropical cyclone track and intensity. The sea surface responses to the land falling process of Typhoon Morakot(2009) are examined observationally and its influences on the activity of the typhoon are numerically simulated with the WRF model. The present study shows that the maximum SST cooling associated with Morakot occurred on the left-hand side of the typhoon track during its landfall. Numerical simulations show that, together with the SST gradients associated with the coastal upwelling and mesoscale oceanic vortices, the resulting SST cooling can cause significant difference in the typhoon track, comparable to the current 24-hour track forecasting error. It is strongly suggested that it is essential to include the non-uniform SST distribution in the coastal areas for further improvement in typhoon track forecast.     

SEA SURFACE TEMPERATURE RESPONSE TEMPERATURE TO TYPHOON MORAKOT (2009) AND ITS INFLUENCE

While previous studies indicate that typhoons can decrease sea surface temperature(SST) along their tracks, a few studies suggest that the cooling patterns in coastal areas are different from those in the open sea. However, little is known about how the induced cooling coupled with the complex ocean circulation in the coastal areas can affect tropical cyclone track and intensity. The sea surface responses to the land falling process of Typhoon Morakot(2009) are examined observationally and its influences on the activity of the typhoon are numerically simulated with the WRF model. The present study shows that the maximum SST cooling associated with Morakot occurred on the left-hand side of the typhoon track during its landfall. Numerical simulations show that, together with the SST gradients associated with the coastal upwelling and mesoscale oceanic vortices, the resulting SST cooling can cause significant difference in the typhoon track, comparable to the current 24-hour track forecasting error. It is strongly suggested that it is essential to include the non-uniform SST distribution in the coastal areas for further improvement in typhoon track forecast.     

基于BGM与ETKF的台风"苏拉"(1209)集合预报的对比试验Ⅰ:路径预报

采用FNL再分析资料和美国联合台风警报中心(Joint Typhoon Warning Center,JTWC)资料,运用中尺度WRF(Weather Research and Forecasting)模式,分别使用增长模繁殖法(Breeding of Growing Mode,BGM)和集合卡尔曼变换方法(Ensemble Transform Kalman Filter,ETKF),对1209号台风"苏拉"进行了台风路径的集合预报试验,并对预报效果进行对比分析。结果表明:采用BGM或ETKF初始扰动的集合预报系统,集合平均预报对风场、温度场、位势高度场的预报效果均优于控制预报;ETKF方法的预报改进程度较BGM方法更大,且对风场和温度场预报技巧的优势尤为明显。BGM方法所得到的集合成员离散度小于ETKF方法,对大气真实状态的表征能力不及后者;两种扰动方法的集合平均都明显改善了台风"苏拉"的路径预报结果,尤其是控制预报在福建沿海第二次登陆后移速过快的问题,但对台风登陆位置预报的改进不明显;此外,采用ETKF方法的集合平均对台风"苏拉"路径预报的改进效果远优于采用BGM方法的集合平均预报。     

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.     

Numerical Study on the Impacts of the Bogus Data Assimilation and Sea Spray Parameterization on Typhoon Ducts

The Weather Research and Forecasting model version 3.2 (WRF v3.2) was used with the bogus data assimilation (BDA) scheme and sea spray parameterization (SSP), and experiments were conducted to assess the impacts of the BDA and SSP on prediction of the typhoon ducting process induced by Typhoon Mindule (2004). The global positioning system (GPS) dropsonde observations were used for comparison. The results show that typhoon ducts are likely to form in every direction around the typhoon center, with the main type of ducts being elevated duct. With the BDA scheme included in the model initialization, the model has a better performance in predicting the existence, distribution, and strength of typhoon ducts. This improvement is attributed to the positive effect of the BDA scheme on the typhoon’s ambient boundary layer structure. Sea spray affects typhoon ducts mainly by changing the latent heat (LH) flux at the air-sea interface beyond 270 km from the typhoon center. The strength of the typhoon duct is enhanced when the boundary layer under this duct is cooled and moistened by the sea spray; otherwise, the typhoon duct is weakened. The sea spray induced changes in the air-sea sensible heat (SH) flux and LH flux are concentrated in the maximum wind speed area near the typhoon center, and the changes are significantly weakened with the increase of the radial range.     

GRAPES区域集合预报条件性台风涡旋重定位方法研究

为了在集合预报中更合理描述台风涡旋中心定位的不确定性,采用2009—2018年中国气象局和日本气象厅台风最佳路径数据,分析台风最佳路径涡旋中心定位的不确定性特征,在此基础上设计条件性台风涡旋重定位方法（Conditional Typhoon Vortex Relocation,CTVR）,构建集合成员台风涡旋中心重定位阈值条件、台风涡旋分离数学处理及涡旋重定位等数学处理过程,利用中国气象局数值预报中心区域集合预报系统（Global/Regional Assimilation and Prediciton System-Regional Ensemble System,GRAPES-REPS）对2018年西北太平洋上的3个台风（1808号“玛莉亚”、1824号“谭美”和1825号“康妮”）进行轴对称结构和轴对称+非对称结构条件性台风涡旋重定位两种方案的集合预报试验和检验评估。结果表明:（1）中国气象局和日本气象厅台风最佳路径误差平均值为13.72 km,可视为台风涡旋中心定位不确定性的合理估计值;（2）统计检验结果和典型个例分析表明,采用轴对称结构和轴对称+非对称结构条件性台风涡旋重定位方法的台风集合预报路径误差及集合预报一致性结果比较接近;（3）条件性台风涡旋重定位方法可以有效改进GRAPES-REPS区域集合预报台风路径概率预报效果,如台风路径集合预报平均误差有所减小,集合预报一致性（路径离散度与路径均方根误差比值）增大,特别是预报初期概率预报效果改进更为显著,而预报中后期改进有限;（4）通过对“玛莉亚”台风集合预报诊断分析发现,经过条件性台风涡旋重定位后,各集合成员的台风路径误差在预报初期明显减小且路径收敛,但随着预报时效的延长台风路径逐渐发散。应用条件性台风涡旋重定位方法后,台风涡旋环流与大尺度环境场仍然比较连续协调,且台风涡旋环流外的大尺度环境场具有一致性特点,最低气压误差、最大风速误差和降水预报技巧基本不变。可见,条件性台风涡旋重定位方法的应用可以提供更准确的台风路径预报不确定性信息,帮助预报员做出更准确的预报决策。      

Comprehensive Marine Observing Experiment Based on High-Altitude Large Unmanned Aerial Vehicle(South China Sea Experiment2020 of the “Petrel Project”)

In collaboration with 12 other institutions, the Meteorological Observation Center of the China Meteorological Administration undertook a comprehensive marine observation experiment in the South China Sea using the Yilong-10 high-altitude large unmanned aerial vehicle(UAV). The Yilong-10 UAV carried a self-developed dropsonde system and a millimeter-wave cloud radar system. In addition, a solar-powered unmanned surface vessel and two drifting buoys were used. The experiment was further supported by an intelligent, reciprocating horizontal drifting radiosonde system that was deployed from the Sansha Meteorological Observing Station, with the intent of producing a stereoscopic observation over the South China Sea. Comprehensive three-dimensional observations were collected using the system from 31 July to2 August, 2020. This information was used to investigate the formation and development processes of Typhoon Sinlaku(2020). The data contain measurements of 21 oceanic and meteorological parameters acquired by the five devices, along with video footage from the UAV. The data proved very helpful in determining the actual location and intensity of Typhoon Sinlaku(2020). The experiment demonstrates the feasibility of using a high-altitude, large UAV to fill in the gaps between operational meteorological observations of marine areas and typhoons near China, and marks a milestone for the use of such data for analyzing the structure and impact of a typhoon in the South China Sea. It also demonstrates the potential for establishing operational UAV meteorological observing systems in the future, and the assimilation of such data into numerical weather prediction models.     

Impact of assimilating IASI radiance observations on forecasts of two tropical cyclones

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.     

Impacts of Multigrid NLS-4DVar-based Doppler Radar Observation Assimilation on Numerical Simulations of Landfalling Typhoon Haikui (2012)

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.     

2011年“洛克”和“桑卡”双台风预报效果的初值试验研究

采用南海台风模式,对2011年业务预报误差较大的台风“洛克”（1115）和“桑卡”（1116）双台风的初值方案进行试验和研究,目的在于寻求改进预报的线索,从而提升台风模式性能。针对“洛克”和“桑卡”台风设计了几组初值方案对比试验,结果表明,仅对弱台风“桑卡”进行重定位和bogus的初值处理,与对双台风都进行初值处理相比较,两台风的路径预报误差减小。分析认为仅对弱台风作初值处理以改善其涡旋环流的影响是该双台风路径预报得以改进的原因。对2011—2012年所有弱台风进行批量预报试验,结果表明对弱台风采用重定位和bogus的初值处理,台风路径预报和强度预报的误差减小。对弱台风进行重定位和bogus初值处理,可改善模式对弱台风的预报效果。此外,目前南海台风模式中现有的bogus方法构造的涡旋相对于弱台风而言云顶偏高,可考虑发展针对弱台风的涡旋模型。      

A STUDY OF THE INFLUENCE OF MICROPHYSICAL PROCESSES ON TYPHOON NIDA (2016) USING A NEW DOUBLE-MOMENT MICROPHYSICS SCHEME IN THE WEATHER RESEARCH AND FORECASTING MODEL

The basic structure and cloud features of Typhoon Nida (2016) are simulated using a new microphysics scheme (Liuma) within the Weather Research and Forecasting (WRF) model. Typhoon characteristics simulated with the Liuma microphysics scheme are compared with observations and those simulated with a commonly- used microphysics scheme (WSM6). Results show that using different microphysics schemes does not significantly alter the track of the typhoon but does significantly affect the intensity and the cloud structure of the typhoon. Results also show that the vertical distribution of cloud hydrometeors and the horizontal distribution of peripheral rainband are affected by the microphysics scheme. The mixing ratios of rain water and graupel correlate highly with the vertical velocity component and equivalent potential temperature at the typhoon eye-wall region. According to the simulation with WSM 6 scheme, it is likely that the very low typhoon central pressure results from the positive feedback between hydrometeors and typhoon intensity. As the ice-phase hydrometeors are mostly graupel in the Liuma microphysics scheme, further improvement in this aspect is required.