一种新型的适应性观测资料应用对台风预报的影响试验研究

近年来，气象界提出了一个“适应性（或目标）观测（adaptive or targeting observation）”的新概念，它是根据数值预报的敏感区在现有的、固定的气象观测网基础上增加的、有目标的特别观测。下投式探空仪（Dropsonde）是适应性观测的重要观测仪器。利用我国新一代数值预报系统GRAPES，初步研究了应用热带气旋适应性观测的下投式探空仪探测资料对台风（2003年杜鹃台风）预报的影响，并进行了敏感性试验。结果表明，数值天气预报中增加下投式探空仪观测资料之后，对台风的移动路径、台风中心位置和强度，以及其它要素的预报都有所改善；敏感性试验还指出，下投式探空仪观测资料的误差结构设置对台风的预报也有明显的影响，该类观测资料在修正背景场的过程中权重并不是越高越好     

Effects of Dropsonde Data in Field Campaigns on Forecasts of Tropical Cyclones over the Western North Pacific in 2020 and the Role of CNOP Sensitivity

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...     

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%。     

The impact of T-PARC 2008 dropsonde observations on typhoon track forecasting

The THORPEX-Pacific Asian Regional Campaign 2008 (T-PARC 2008) was performed during the period of August 1 through October 4, 2008, and mainly focused on the genesis, intensification, recurvature, and extra-tropical transition over the western North Pacific in collaboration with TCS-08 and DOTSTAR. This study investigates the impact of dropsonde observations on the improvement of predictive skills for Typhoon Sinlaku (0813) and Jangmi (0815) during T-PARC 2008. Twelve and six cases were selected for Sinlaku and Jangmi, respectively. The dropsonde data were assimilated by the Weather Research and Forecasting (WRF)-Three-Dimensional Variational system (3DVAR), and then the typhoon track was obtained by running a WRF model for up to 72 hours. Consequently, the assimilation of the dropsonde data had positive impacts on the typhoon track forecast and lead to mean track error reductions of 22.5% and 17.0% for Typhoon Sinlaku and Jangmi, respectively. Subsequent experiments were also conducted to determine the sensitivities of storm activity in the horizontal and vertical distributions and the dynamic and thermodynamic variables using the dropsonde data. The results show that sondes released south of storms around the middle troposphere (500～850 hPa) are more effective in improving the track forecast. The dynamic variables mainly affect the storm tracks, while the thermodynamic variables mainly affect the central pressure of the storm.     

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.     

The Sensitive Regions Identified by CNOPs of Three Typhoon Events

In this paper, several sets of observing system simulation experiments (OSSEs) were designed for three typhoon cases to determine whether or not the additional observation data in the sensitive regions identified by conditional nonlinear optimal perturbations (CNOPs) could improve the short-range forecast of typhoons. The results show that the CNOPs capture the sensitive regions for typhoon forecasts, which implies that conducting additional observation in these specific regions and eliminating initial errors could reduce forecast errors. It is inferred from the results that dropping sondes in the CNOP sensitive regions could lead to improvements in typhoon forecasts.     

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。     

A SENSITIVITY SIMULATION ABOUT CLOUD MICROPHYSICAL PROCESSES OF TYPHOON CHANCHU

With the Reisner-2 bulk microphysical parameterization of the fifth-generation Pennsylvania State University–U.S. National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5), this paper investigates the microphysical sensitivities of Typhoon Chanchu. Four different microphysical sensitivity experiments were designed with an objective to evaluate their respective impacts in modulating intensity forecasts and microphysics budgets of the typhoon. The set of sensitivity experiments were conducted ...     

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.     

APPLICATION OF BDA SCHEME IN TYPHOON TRACK PREDICTION

The MM5, which is the PSU/NCAR mesoscale nonhydrostatic limited-area model, and its adjoining modeling system are used in this paper. Taking T106 analysis data as background field the authors generate an optimal initial condition of a typhoon by using two bogus data assimilation schemes, and conduct some numerical simulating experiments. The results of No.9608 typhoon (Gloria) show that the optimal initial field have some dramatic improvements, such as inaccurate position of typhoon center, weaker typhoon circulation and incomplete inner structure of the typhoon, which are caused by shortage of data over the sea. Some improvements have been made in the track forecast. Through several comparing experiments, the initialization optimized by BDA scheme is found to be more reasonable than GFDL scheme and its typhoon track forecast is better.     

台风“灿鸿”(1509)的适应性观测敏感区特征及其模拟观测同化研究

适应性观测可以改善资料同化和预报质量。本文利用集合卡尔曼变换适应性观测系统对2015年09号台风“灿鸿”进行了观测敏感区识别,并以第一目标时刻的观测敏感区为基础,运用观测系统模拟试验方法获取模拟的适应性观测资料。基于WRF中尺度同化和预报系统,开展了适应性观测敏感区模拟资料的同化和预报试验。研究发现,台风“灿鸿”(1509)的观测敏感区主要位于台风中心的东北侧及东南侧。同化敏感区内模拟观测资料比同化常规观测资料能更好地改善分析质量和高度、台风路径的预报质量,但对降水的预报改善较弱。     

雷达资料同化对2015年台风彩虹数值模拟改进

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。     

集合预报对台风天鹅(2015)远距离暴雨的不确定性研究

2015年8月23—24日期间台风天鹅引发华东中部沿海地区出现暴雨或大暴雨天气。基于欧洲中期天气预报中心的集合预报分析导致此次远距离暴雨预报不确定的关键原因,并利用集合敏感性分析方法研究影响此次暴雨过程的主要天气系统的敏感区域,此外对暴雨发生发展的热动力机制展开探讨,主要结论包括:集合预报对此次台风天鹅引起的远距离暴雨的可预报性明显偏低,仅在暴雨发生前24 h才做出较大调整。在不同起报时次下,当台风路径的系统性偏差最小时,台风降水集合预报也最接近实况,但是进一步的分析表明,台风路径误差与降水量级之间的对应关系并不确定。不同雨量成员组间中低层环流场的对比分析表明:高空槽的预报差异是集合预报不确定的主要原因,高空槽东移加深有利于增加暴雨区的斜压不稳定,也有利于增强对流层低层的水汽输送急流带。500 hPa高度场的敏感性分析表明无论是初始场还是预报场,暴雨区平均降雨量均与高空槽的东移和加深显著相关,且随着预报时次的临近,显著相关区域向低槽下游明显扩大。此外还发现高空槽的东移有利于增强(减弱)暴雨区左(右)侧低层冷空气的强度,使得台风右侧更多暖湿气流向暴雨区输送。     

台风预报误差的流依赖特征及混合资料同化中最优耦合系数

基于集合卡尔曼变换与三维变分(ETKF-3DVAR)混合资料同化系统和欧洲中期天气预报中心(ECWMF)的全球集合预报,以"梅花"台风为例,分析了台风系统预报误差的流依赖特征,讨论了耦合系数在混合同化和预报中的敏感性及其对预报质量的影响。结果显示,台风系统的预报误差协方差具有显著的中小尺度结构特征,集合估计的预报误差协方差结构能够再现其流依赖属性。相对于3DVAR方案,混合资料同化方案的最优耦合系数对台风系统的分析和预报质量具有更好的改善;但不同的耦合系数对台风路径预报有明显的影响,不合适的耦合系数甚至可能导致更坏的结果,只有耦合了相对合适的预报误差协方差的流依赖信息,混合资料同化方案才可能对分析和预报质量有正效果。这表明在混合资料同化系统中,构造一种具有自适应能力的耦合权重函数,实现相对最优权重的自动选择,对充分发挥混合资料同化方案的潜在优势具有重要意义。     

条件非线性最优扰动方法在适应性观测研究中的初步应用

针对适应性观测中敏感性区域的确定问题,考虑初始误差对预报结果的影响, 比较了条件非线性最优扰动(CNOP)与第一线性奇异向量(FSV)在两个降水个例中的空间结构的差异,考察了它们总能量范数随时间发展演变的异同。结合敏感性试验的分析,揭示了预报结果对CNOP类型的初始误差的敏感性要大于对FSV类型的初始误差的敏感性,因而减少初值中CNOP类型误差的振幅比减少FSV类型的收益要大。这一结果表明可以把CNOP方法应用于适应性观测来识别大气的敏感区。关于将CNOP方法有效地应用于适应性观测所面临的挑战及需要采取的对策等也进行了讨论。     

利用多普勒雷达径向速度提取台风环境风场信息

应用蓝金模式模拟了纯气旋性旋转的多普勒雷达径向速度特征,还模拟了不同环境风向和吹向台风中心的辐合风对台风多普勒速度特征的影响。在此基础上,提出了雷达实测台风速度的特征和不同环境风向的速度数值模拟图进行比较,从而提取出相应环境风信息的方法,并应用这种环境风信息来判断台风的移动路径。通过对台风实例分析,特别是在台风发生转折的关键时刻,该方法都能够较准确地判断环境风转折的多普勒速度特征。应用多普勒雷达径向速度图像与不同环境风向模拟图像进行比较的方法,能够实时(雷达观测时间间隔仅为6 min)监测到环境气流的方向及其变化,比较准确地监测台风的移动路径,这是其他大尺度气象资料难以做到的。分析表明:环境风转向变化的现象在前,台风发生转折的现象在后,对台风路径的短时预报具有一定应用价值。     

下投式探空资料对Debby飓风路径预报影响的数值试验

在飓风路径的数值预报中，对于初始场的要求很高，然而，由于初始资料的缺乏，经常导致路径预报的误差较大，尤其是当飓风处于远离陆地的海上时，这种误差更大，通过利用UM模式在Debby飓风活动期间，对下投式探空仪所获取探空资料，采用不同使用方案的三个时次共计10次数值试验的结论分析，给出一些有意义的 结论，即非实时资料对实时资料的有效补充，能够提高飓风路径预报精度，而在众多气象要素场中，风场和湿度场对飓风路径预报的影响更大。     

适应性观测研究现状和展望

适应性观测是指为了有针对性地提高高影响天气数值预报的质量,在已有观测系统基础上对特定敏感区域/特定时段进行补充性加强观测。十多年来,这种旨在提高数值预报质量的新策略在国际上引起高度重视,成功开展了多个系列外场观测试验,并在适应性观测敏感区识别方法的发展和适应性观测资料同化后对数值预报质量影响的定量评估等方面均取得了重要的研究成果。文中简述了适应性观测问题及其目的,着重分析和总结了目标敏感区识别方法及其特点和适应性观测对数值预报质量的影响等方面的研究进展,并讨论了适应性观测资料改进未来数值预报质量需要解决的关键科学问题。     

The impact of observation systems on medium-range weather forecasting in a global forecast system

To investigate the impact of various types of data on medium-range forecasts, observing system experiments are performed using an assimilation algorithm based on the National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) reanalysis system. Data-denial experiments for radiosonde, satellite, aircraft, and sea surface observations, and selected data experiments for radiosonde and surface data, are conducted for the boreal summer of 1997 and the boreal winter of 1997/1998. The data assimilation system used in this study is remarkably dependent on radiosonde data, which provides information about the three-dimensional structure of the atmosphere. As expected, the impact of radiosonde observations on medium-range forecasts is strongly positive over the Northern Hemisphere and tropics, whereas the satellite system is most beneficial over the Southern Hemisphere. These results are also found in experiments simulating historical changes in observation systems. Over the tropics, assimilation without radiosonde observations generates unbalanced analyses resulting in unrealistic forecasts that must be corrected by the forecast model. Forecasts based on analysis from the observation data before the era of radiosonde observation are found to be less meaningful. In addition, the impacts on forecasts are closely related to the geographical distribution of observation data. The memory of observation data embedded in the analysis tends to persist throughout forecasts. However, cases exist where the effect of forecast error growth is more dominant than that of analysis error, e.g., over East Asia in summer, and where the deficiency in observations is supplemented or the imbalance in analysis is adjusted by the forecast model during the period of forecasts. Forecast error growth may be related to the synoptic correction performed by the data assimilation system. Over data-rich areas, analysis fields are corrected to a greater extent by the data assimilation system than are those over data-poor areas, which can cause the forecast model to produce more forecast errors in medium-range forecasts. It is found that even one month per season is sufficient for forecast skill verification in data impact experiments. Additionally, the use of upper-air observations is found to benefit areas that are downstream of observation data-rich areas.