Ensemble Forecasting of Tropical Cyclone Motion Using a Baroclinic Model

The purpose of this study is to investigate the effectiveness of two different ensemble forecasting （EF） techniques-the lagged-averaged forecast （LAF） and the breeding of growing modes （BGM）. In the BGM experiments, the vortex and the environment are perturbed separately （named BGMV and BGME）. Tropical cyclone （TC） motions in two difficult situations are studied： a large vortex interacting with its environment, and an apparent binary interaction. The former is Typhoon Yancy and the latter involves Typhoon Ed and super Typhoon Flo, all occurring during the Tropical Cyclone Motion Experiment TCM- 90. The model used is the baroclinic model of the University of New South Wales. The lateral boundary tendencies are computed from atmospheric analysis data. Only the relative skill of the ensemble forecast mean over the control run is used to evaluate the effectiveness of the EF methods, although the EF technique is also usecl to quantify forecast uncertainty in some studies. In the case of Yancy, the ensemble mean forecasts of each of the three methodologies are better than that of the control, with LAF being the best. The mean track of the LAF is close to the best track, and it predicts landfall over Taiwan. The improvements in LAF and the full BGM where both the environment and vortex are perturbed suggest the importance of combining the perturbation of the vortex and environment when the interaction between the two is appreciable. In the binary interaction case of Ed and Flo, the forecasts of Ed appear to be insensitive to perturbations of the environment and/or the vortex, which apparently results from erroneous forecasts by the model of the interaction between the subtropical ridge and Ed, as well as from the interaction between the two typhoons, thus reducing the effectiveness of the EF technique. This conclusion is reached through sensitivity experiments on the domain of the model and by adding or eliminating certain features in the model atmosphere. Nevertheless, the forecast tracks in some of the cases are improved over that of the control. On the other hand, the EF technique has little impact on the forecasts of Flo because the control forecast is already very close to the best track. The study provides a basis for the. future development of the EF technique. The limitations of this study are also addressed. For example, the above results are based on a small sample, and the study is actually a simulation, which is different than operational forecasting. Further tests of these EF techniques are proposed.

A Method Fusing Conventional Wind Field with Cloud Motion Wind and Its Application in Location Forecast of the Severe Convection

Based on the fast algorithm of meteorological satellite guide wind vector tracing, cloud motion wind vector is calculated. According to the different characteristics of cloud motion wind field and sounding wind field, a method which fuses conventional data with unconventional data based on variation principle is presented. The fundamental is constructing a cost function that makes the value approach conventional data and the gradient approach unconventional data. Using this method, the conventional wind and the cloud motion wind are fused. The fused wind field has high resolu- tion. Its wind direction approaches cloud motion wind which indicates move direction of the synoptic system, and its velocity approaches conventional wind which indicates move velocity of the synoptic system. The wind field data are used for short-time forecast of severe convective weather location, which gets a good result.

APPLICATION OF STATISTICAL INTERPRETATION TECHNIQUES WITH NWP PRODUCTS FOR OBJECTIVE FORECASTING OF TROPICAL CYCLONE MOTION

Statistical study is first performed of the efficiency of the technique of statistical interpretation using the products of NWP. The result shows that the application of the technique has improved the predictabilily of predictors in objective forecasting of tropical cyclone motion, increased the forecasting skill of models and extended the valid period of forecast. Then a discussion is made of some technical problems in the application in the motion forecasting, suggesting: a large sample of data and perfect forecast method be employed in constructing objective forecast models for tropical cyclone motion, predictors be included that are so finely built that they reflect all synoptic features and physical quantity fields and NWP products be used and corrected that are available at multiple times. It is one of the effective ways to improve the skill and stability of the forecast by composite use of outcomes from various forecasting models.

SOME ASPECTS OF OBJECTIVE FORECASTING OF TROPICAL CYCLONE MOTION

As shown in a statistical analysis of the relationship between environmental fields at varied timeand tropical cyclone motion, the forecasting ability of the initisl environmental field predictors for tropical cyclone motion decreases with the increase of valid time period of forecast;it is higher with these predictors at a fUture time than at an initial time. The work also indicates that for the tropical cyclone motion over a given period of valid forecast, better predictors appear at times mostly differing from thevalid periods; for periods at 48-120 h the environmental predictors at 48-72 h are m0re capable of forecasting. With statistical interpretation of NWP products, a predictive model for tropical cyclone motionis superior in performance over a statistical forecasting model that employes predictors of the initial field in the basic framework. The concluding remarks can be used as reference in the construction of an objective prediction model for tropical cyclone motion.

THE ENSEMBLE FORECASTING OF TROPICAL CYCLONE MOTION I:USING A PRIMITIVE EQUATION BAROTROPIC MODEL

Ensemble forecasting of tropical cyclone (TC) motion was studied using a primitive equation barotropic model by perturbing initial position and structure for 1979 1993 TC. The results show that TC initial position perturbation affects its track, but the ensemble mean is close to control forecast. Experiments was also performed by perturbing TC initial parameters which were used to generate TC initial field, and more improvement can be obtained by taking ensemble mean of selective member than selecting members randomly. The skill of 60 % 70 % of all cases is improved in selective ensemble mean. When the ambient steering current is weak, more improvement can be obtained over the control forecast.

A multiple template approach for robust tracking of fast motion target

Target tracking is very important in computer vision and related areas. It is usually difficult to accurately track fast motion target with appearance variations. Sometimes the tracking algorithms fail for heavy appearance variations. A multiple template method to track fast motion target with appearance changes is presented under the framework of appearance model with Kalman filter. Firstly, we construct a multiple template appearance model, which includes both the original template and templates affinely transformed from original one. Generally speaking, appearance variations of fast motion target can be covered by affine transformation. Therefore, the affine tr templates match the target of appearance variations better than conventional models. Secondly, we present an improved Kalman filter for approx- imate estimating the motion trail of the target and a modified similarity evaluation function for exact matching. The estimation approach can reduce time complexity of the algorithm and keep accuracy in the meantime. Thirdly, we propose an adaptive scheme for updating template set to alleviate the drift problem. The scheme considers the following differences： the weight differences in two successive frames; different types of affine transformation applied to templates. Finally, experiments demonstrate that the proposed algorithm is robust to appearance varia- tion of fast motion target and achieves real-time performance on middle/low-range computing platform.

Minor Component Analysis-based Landing Forecast System for Ship-borne Helicopter

The general structure of ship-borne helicopter landing forecast system is presented, and a novel ship motion prediction model based on minor component analysis (MCA) is built up to improve the forecast effectiveness. To validate the feasibility of this landing forecast system, time series for the roll, pitch and heave are generated by simulation and then forecasted based on MCA. Simulation results show that ship-borne helicopters can land safely in higher sea condition while carrying on rescue or replenishment tasks at sea in terms of the landing forecast system.

Multipoint Heave Motion Prediction Method for Ships Based on the PSO-TGCN Model

During ship operations,frequent heave movements can pose significant challenges to the overall safety of the ship and completion of cargo loading.The existing heave compensation systems suffer from issues such as dead zones and control system time lags,which necessitate the development of reasonable prediction models for ship heave movements.In this paper,a novel model based on a time graph convolutional neural network algorithm and particle swarm optimization algorithm(PSO-TGCN)is proposed for the first time to predict the multipoint heave movements of ships under different sea conditions.To enhance the dataset's suitability for training and reduce interference,various filter algorithms are employed to optimize the dataset.The training process utilizes simulated heave data under different sea conditions and measured heave data from multiple points.The results show that the PSO-TGCN model predicts the ship swaying motion in different sea states after 2 s with 84.7%accuracy,while predicting the swaying motion in three different positions.By performing a comparative study,it was also found that the present method achieves better performance that other popular methods.This model can provide technical support for intelligent ship control,improve the control accuracy of intelligent ships,and promote the development of intelligent ships.

Study on High Accuracy Hybrid Controller for Periodic Motion Control

In order to realize high accuracy control for periodic motion,a hybrid controller with grey prediction was presented in this paper.Incorporating the grey prediction,repetitive control,and the traditional Proportional-Integral-Differential(PID)control,a design method of the grey prediction repetitive PID(GRPID)control algorithm was investigated,according to the characteristics of the periodic motion control.The hybrid control algorithm can estimate unsure parameters and disturbance of system using grey prediction,and compensate control in terms of the prediction results,and this may improve control quality and robustness of repetitive control for controlling periodic motion.An example was carried out to verify the feasibility of the controller.The simulation results show that this algorithm has better performances than that of the conventional repetitive control system.It indicates the presented control method is more suitable for control system of periodic motion.

Study of Volatility Stochastic Processes in the Context of Solvency Forecasting for Sri Lankan Life Insurers

The main business of Life Insurers is Long Term contractual obligations with a typical lifetime of 20 - 40 years. Therefore, the Solvency metric is defined by the adequacy of capital to service the cash flow requirements arising from the said obligations. The main component inducing volatility in Capital is market sensitive Assets, such as Bonds and Equity. Bond and Equity prices in Sri Lanka are highly sensitive to macro-economic elements such as investor sentiment, political stability, policy environment, economic growth, fiscal stimulus, utility environment and in the case of Equity, societal sentiment on certain companies and industries. Therefore, if an entity is to accurately forecast the impact on solvency through asset valuation, the impact of macro-economic variables on asset pricing must be modelled mathematically. This paper explores mathematical, actuarial and statistical concepts such as Brownian motion, Markov Processes, Derivation and Integration as well as Probability theorems such as the Probability Density Function in determining the optimum mathematical model which depicts the accurate relationship between macro-economic variables and asset pricing.

顾及有效角动量与IGS超快解数据的极移预报方法

极移高精度预报对卫星实时定轨、深空探测器导航等应用至关重要.本文提出了一种联合有效角动量(Effective Angular Momentum,EAM)与国际全球卫星导航系统服务组织(International GNSS Service,IGS)提供的超快解数据进行极移预报的方法.该方法基于IGS超快解数据得到的极移第1天预报值,对引入EAM得到的极移预报结果进行校正,获得联合预报值.首先,基于LS(Least Squares)+AR(Auto-Regressive)模型实现了引入EAM的极移预报,相对国际地球自转与参考系统服务组织(International Earth Rotation and Reference Systems Service,IERS)提供的公报A数据,在超短期(第1~10天)预报跨度可以得到更高精度的极移预报结果,其中大气和海洋角动量发挥了主要作用.其次,鉴于IGS超快解数据精度高、更新快的特点,以IGS超快解为基础数据,基于LS+AR模型可以得到极移第1天预报值,其精度显著优于IERS公报A的极移第1天预报值.最后,利用第1天预报值对顾及有效角动量的预报结果进行校正获得了联合预报值,进一步提高了超短期极移预报精度(尤其是第1~5天).2020年7月24日—2022年1月30日间的联合预报结果表明:第1~20天的预报值总体优于IERS公报A的预报值.其中,第1~10天的预报精度显著提升,在预报第1天,X、Y方向预报值相对公报A预报值的精度提升分别可达39.5%~62.3%和24.5%~51.9%;在预报第10天,相对公报A预报值的精度提升分别可达28.0%~28.9%和21.9%~23.4%.

基于LSTM的船舶纵摇极短期预报

为船舶航行决策相关设备的精度校准提供数据支持,保障船舶安全航行及船用设备的稳定运行具有重要意义。传统水动力学分析方法难以精确、高效地预报船舶的非线性运动。为了提高船舶极短期预报的精度,分别构建单特征和多特征输入的长短期记忆人工神经网络(LSTM)模型,对船舶在波浪中的纵摇运动进行研究和预测,分析了运动参数和波浪参数对模型预报精度的影响,并对输入参数的时间间隔和模型训练数量等参数展开分析。结果表明,该方法在单特征输入情况下有效预测时间可达6 s,在多特征输入的情况下有效预测时间可达12 s,验证了LSTM算法对船舶在波浪中的纵摇运动进行极短期预报的可行性。

热带气旋路径集合预报方法研究I——正压模式结果的初步分析

选择1979～1993年间的热带气旋为试验个例,通过扰动热带气旋初始位置和初始结构,构造集合成员, 用正压原始方程模式,进行路径集合预报试验, 并初步探讨预报成员的集合方法。试验结果表明:热带气旋定位误差影响路径预报,但扰动初始位置的集合平均预报与控制试验的预报水平相接近。扰动热带气旋初始结构的集合预报试验表明,约有60 %～70 %个例的集合路径预报得到改进。此外,试验结果还表明,当环境引导气流较弱时,进行扰动热带气旋初始结构的集合预报,预报结果的改善较明显。

云迹风资料同化对暴雨预报影响的数值模拟

文中运用MM5对 1998年 6月 13～ 14日长江中下游一次暴雨强降水进行了数值模拟及云迹风资料同化试验研究。结果表明 ,云迹风资料同化能有效地改善高空风场质量 ,修正控制试验中模式高空风场对中纬度高空西风急流前沿西风强度的描述 ,使得模拟的暴雨强度与实际降水分布更加接近。分析认为在暴雨预报业务和科研中 ,云迹风资料的使用可有效地改善高空风场分布 ,对提高降水预报质量是一个有效途径 。

滞后平均法(LAF)在热带气旋路径集合预报中的应用

本文用一正压模式 ,采用滞后平均法 (LAF)对 2 0 0 0年热带气旋进行路径集合预报试验 ,并与基于热带气旋初始结构扰动的集合预报方法进行了比较分析 ,结果表明LAF方法对热带气旋路径预报具有较好的改进作用。但LAF的集合预报效果受模式本身误差的影响 ,在完美模式的假设下 ,LAF集合预报相对于控制试验的技巧水平 2 0～ 4 0 %。

准地转理论基本问题回顾与讨论

准地转理论是大气动力学的中心问题之一,它提供了从大气动力学基本原理入手分析大尺度天气系统演变的方法。准地转理论有助于预报员理解中高纬度大尺度天气系统的三维结构,分析、预报天气系统的发展和移动,因此被称为短期天气预报的理论基础。准地转理论具有完整的理论体系,它包含了较多的基本假定,故容易导致对其中的一些基本问题的理解有混淆。本文从基础的动力学知识出发,对准地转理论的基本概念、基本近似、核心理论及其在实际天气预报过程中的应用作了回顾和讨论。内容包括:准地转运动与准地转近似定义、准地转运动理论的范畴、天气图上的大尺度运动、准地转运动理论与短期天气预报的关系、由斜压二层模式下的准地转理论对高空槽脊和地面气旋发展与移动的判断等。

逐时云迹风资料同化对暴雨预报的模拟试验

文中基于不同的云迹风同化方案,用GRAPES模式对2005年7月11—12日长江中下游一次暴雨强降水过程进行了云迹风资料同化试验及数值模拟,通过对比分析不同方案所得的分析场及预报场的差异,研究逐时云迹风资料三维变分同化对分析场及暴雨预报的影响。首先,根据连续性原理及双通道各层次云迹风资料的误差分析,分3个步骤对7月11日00:00—12:00UTC共12个时次的双通道云迹风资料进行了初步的质量控制;然后,把经过质量控制的云迹风资料放入基于GRAPES3D-VAR三维变分同化方案开发的逐小时循环同化系统中进行同化,将得出的分析场与单一时次未经质量控制的云迹风资料同化得出的分析场进行对比,探讨了逐时云迹风资料同化对数值预报分析场的影响;最后,把同化后的分析场作为初始场,用GRAPES模式对2005年7月11—12日长江流域暴雨过程做24h降水预报试验,分析两个同化方案所模拟得到的预报场的差异。结果表明,经资料的筛选、同经纬度单点通道的选择及资料的稀疏化3个步骤控制后,各层次云迹风资料的误差有明显减小;加入经质量控制的逐时云迹风资料其三维变分同化可以提高分析场中风压场及水汽场的质量;而且在暴雨预报试验中可以相对更准确地预报暴雨落区及雨强。

近断层地震动场预测——以长春市为例

断层带附近地震动场分布的研究,是当前地震工程领域研究的热点问题之一。近断层地震动场的分布对在断层附近进行抗震结构设计时,不仅是提供地震动输入,也是确定建设场地避让范围的重要依据之一。以区域地震构造背景分析、目标断层活动性鉴定、地震危险性评价为基础,结合断层探测结果,利用统计经验关系等最终确定发震断层,并建立相应的震源模型。采用显式有限元和并行计算技术计算目标区域场地的长周期地震动。利用有限断层随机合成的方法,计算高频地震动。将低频和高频地震动合成为目标区域内的宽频带地震动时程。对局部特殊场地条件地区,基于场地调查和勘探的数据,利用等效线性化等方法进行一维土层的非线性反应计算,给出这些特殊场地的宽频带地震动时程。最后,根据地震动时程获得设定地震发生时,目标区域的峰值加速度分布预测图和相应的反应谱。以长春市为例预测了在设定地震发生时,近断层地震动场的分布情况。当长春尖山子—卡伦断层发生6.0级地震时,潜在破坏性地震动的影响范围集中在附近,沿断层走向分布。加速度峰值沿断层垂直变化,主要为90 Gal～140 Gal。只是在长春市南部加速度峰值达到200 Gal。本研究的预测结果具备断层附近地震动的一些最基本的特征,符合当前对断层附近地震动的基本认识。

一次春季冰雹天气的中尺度系统分析

对2007年5月5日江苏出现的大范围雷雨、大风和区域性冰雹天气的环流背景场进行了分析,结果表明:这次强对流天气是由北方南下的冷空气触发所致,锋前对流层低层的增温和500 hPa冷空气的先行南下使潜在的对流不稳定性加剧;地面冷锋前中尺度低压的发展是对流性天气发展的主要因素;强烈的上升运动和低层水汽通量辐合提供了有利于冰雹产生的过冷水滴的碰撞增长条件;冰雹天气的产生与地面物理量场有很好的配置关系。

基于预测的足球机器人抢点射门动作实现研究

在对足球机器人运动性能分析、球在场地的运动预测分析的基础上 ,提出了足球机器人抢点射门的技术动作实现方案 ,分析说明了动作实现的条件与范围 .在实际系统实验中证实了方案的可行性 .