热带气旋预报的人工神经网络方法

根据１９４９－１９８８年登陆珠江口的热带气旋资料，运用了人工神经网络的一个典型模型－“反向传播”模型，建立了该地区３５－４９小时热带气旋登陆地点的预报模型，并应用于热带气旋登陆地点的预报，即珠江口的热带气旋登陆地点预报，其拟合最大相对误差不超过０．７％。结果表明，神经网络预报模型具有容错能力强、预报速度快的特点，可望成为望带气旋预报的有效辅助手段。     

模糊神经网络方法在热带气旋强度预报中的应用研究

以1960-2007年共48年6月份西行进入南海海域的热带气旋样本为基础, 将热带气旋中心附近最大风速作为台风强度, 以气候持续预报因子作为模型输入, 采用模糊神经网络方法, 进行了热带气旋强度预报模型的预报建模研究。结果表明, 对175个独立预报样本模糊神经网络方法的南海热带气旋强度24 h的预报平均绝对误差为3 m·s-1。另外, 根据相同的热带气旋样本及预报因子, 还进一步将该预报方法与国内外普遍采用的气候持续法热带气旋强度预报方法进行对比分析, 结果表明, 气候持续预报方法的预报误差明显偏大, 独立样本强度预报平均绝对误差为4.54 m·s-1。     

南海热带气旋强度预报的线性模型与非线性模型研究

以1980—2012年共33 a的6—10月在南海生成或西行进入南海海域的热带气旋样本为基础,采用线性回归方法和非线性人工神经网络方法,分别进行12～72 h各个预报时效的南海热带气旋强度预报模型建模研究。根据相同的热带气旋个例,相同的预报因子,将逐步回归预报模型、BP神经网络预报模型和遗传-神经网络预报模型进行比较。试验预报结果表明,非线性的神经网络预报模型比线性的回归模型有更好的预报能力;而同为非线性模型,遗传-神经网络模型比BP神经网络预报模型预报能力更强。      

西北太平洋热带气旋强度统计释用预报方法研究

为了提高西北太平洋地区热带气旋（TC）强度预报准确率,在气候持续预报方法基础上,考虑气候持续性因子、天气因子、卫星资料因子,以TC强度变化为预报对象,运用逐步回归统计方法,建立西北太平洋地区24、48、72小时TC强度预报方程。通过不同的分海区试验（远海区域、华东近海、华南近海）,证明回归结果较好。逐一分析选入因子发现：气候持续性因子在方程中相当重要;同时对远海区域和华东近海而言,海温影响也不容忽视,对华南近海而言,反映动力强迫作用的因素也较为重要。卫星资料的加入,对回归结果略有改进。用“刀切法”作独立样本检验,与气候持续法比较,预报误差明显减小。     

热带气旋路径强度预报——SAPC法

SAPC——逐段相似气候持续性热带气旋路径、强度预报方法，既考虑了热带气旋的气候持续性规律，又考虑了与现时热带气旋状态特别相似的历史热带气旋路径、强度变化规律，用不同的相似条件和权重，把气候路径、相似路径和持续性路径作了有机的统一。该方法克服了预报路径的大曲率变化，考虑了随时间、地点变化的热带气旋的气候规律，根据热带气旋的现时状态，即可随时制作路径、强度预报。历史资料和实际应用表明该方法有实用价值。     

集成方法在热带气旋路径和强度预报中的应用

利用多元线性回归、递归正权决策和算术平均方法,分别建立热带气旋路径和强度多模式集成预报方程,并用2004年西北太平洋和南海生成的热带气旋资料进行预报试验,同时对各家预报和集成预报进行了检验分析。结果表明,用集成预报方法作热带气旋路径和强度预报是可行的,预报年总平均误差有一定程度的减小,最大预报误差也有所减小,出现较大预报误差的概率明显减小。集成方法的预报能力一般好于集成方法中采用的任意单一预报,体现了集成方法的优越性。     

用统计动力方法作盛夏南海中北部热带气旋强度预报

对1960～2002年盛夏（7～9月）在南海中北部海域活动的热带气旋，引入欧洲中心（ECMWF）数值预报格点资料，采用移动坐标，选用有关热带气旋自身特征变量及环境场等物理量动力因子，用多元回归方法，建立热带气旋强度的动力统计预报模式，结果表明该模式较单纯靠天气学经验的预报能力有明显提高。     

用统计动力方法作盛夏南海中北部热带气旋强度预报

对1960~2002年盛夏(7~9月)在南海中北部海域活动的热带气旋,引入欧洲中心(ECMW F)数值预报格点资料,采用移动坐标,选用有关热带气旋自身特征变量及环境场等物理量动力因子,用多元回归方法,建立热带气旋强度的动力统计预报模式,结果表明该模式较单纯靠天气学经验的预报能力有明显提高。     

A Western North Pacific Tropical Cyclone Intensity Prediction Scheme

A western North Pacific tropical cyclone (TC) intensity prediction scheme (WIPS) is developed based on TC samples from 1996 to 2002 using the stepwise regression technique, with the western North Pacific divided into three sub-regions: the region near the coast of East China (ECR), the South China Sea region (SCR), and the far oceanic region (FOR). Only the TCs with maximum sustained surface wind speed greater than 17.2 m s-1 are used in the scheme. Potential predictors include the climatology and persistence factors, synoptic environmental conditions, potential intensity of a TC and proximity of a TC to land. Variances explained by the selected predictors suggest that the potential intensity of a TC and the proximity of a TC to land are significant in almost all the forecast equations. Other important predictors include vertical wind shear in ECR, 500-hPa geopotential height anomaly at the TC center, zonal component of TC translation speed in SCR, intensity change of TC 12 or 24 h prior to initial time, and the longitude of TC center in FOR. Independent tests are carried out for TCs in 4 yr (2004-2007), with mean absolute errors of the maximum surface wind being 3.0, 5.0, 6.5, 7.3, 7.6, and 7.9 m s-1 for 12- to 72-h predictions at 12-h intervals, respectively. Positive skills are obtained at all leading time levels as compared to the climatology and persistence prediction scheme, and the large skill scores (near or over 20%) after 36 h imply that WIPS performs especially better at longer leading times. Furthermore, it is found that the amendment in TC track prediction and real-time model analysis can significantly improve the performance of WIPS in the SCR and ECR. Future improvements will focus on applying the scheme for weakening TCs and those near the coastal regions.     

用数字云图确定热带气旋强度的原理和方法

本文采用数字云图资料，分析热带气旋强度与热带气旋中云系结构的关系，提出了云系结构紧密度因子的概念并用云带旋转的圈数表示热带气旋强度的方法。本文对原有关于热带气旋中云系结构的某些因子的取值作了适当调整， 改进了用增强红外云图确定热带气旋强度的方法。 经过对2446组样本的拟合，热带气旋强度最大风速估计值的平均绝对误差为2.48 m/s。本方法可以实现人机交互，能更客观地作出定量估计。对1993年12个热带气旋检验，最大风速平均绝对误差为2.31 m/s。     

Comparison of Three Tropical Cyclone Intensity Datasets

Analyzed in this paper are the 16-yr (1988-2003) tropical cyclone (TC) intensity data from three major forecast centers of the western North Pacific, i.e., China Meteorological Administration (CMA), Regional Specialized Meteorological Center Tokyo (RSMC Tokyo), and Joint Typhoon Warning Center (JTWC) of the United States. Results show that there are significant discrepancies (at 1% significance level) in the intensity of TCs among the three centers, with a maximum difference for the same TC over 30 m s-1. The flight reconnaissance over TC can minish the discrepancy to some extent. A climatic and persistent prediction model is set up to study the impact of initial data from different forecast centers on the prediction of TC intensity. It is obtained that the root mean square error (RMSE) of a 4-yr independent test is the largest using data from JTWC, while the smallest using data from RSMC Tokyo. Average absolute deviation in 24-h intensity prediction is 2.5 m s-1 between CMA and RSMC Tokyo data, and 4.0 m s-1 between CMA and JTWC data, with a maximum deviation reaching 21 m s-1. Such a problem in the initial value increases the difficulty in intensity prediction of TCs over the western North Pacific.     

Evaluation of Tropical Cyclone Intensity Forecasts from Five Global EnsemblePrediction Systems During 2015-2019

This study presented an evaluation of tropical cyclone (TC) intensity forecasts from five global ensemble prediction systems (EPSs) during 2015-2019 in the western North Pacific region. Notable error features include the underestimation of the TC intensity by ensemble mean forecast and the under-dispersion of the probability forecasts.The root mean square errors (brier scores) of the ensemble mean (probability forecasts) generally decrease consecutively at long lead times during the five years, but fluctuate between certain values at short lead times.Positive forecast skill appeared in the most recent two years (2018-2019) at 120 h or later as compared with the climatology forecasts. However, there is no obvious improvement for the intensity change forecasts during the 5-yearperiod, with abrupt intensity change remaining a big challenge. The probability forecasts show no skill for strongTCs at all the lead times. Among the five EPSs, ECMWF-EPS ranks the best for the intensity forecast, while NCEP-GEFS ranks the best for the intensity change forecast, according to the evaluation for ensemble mean and dispersion. As for the other probability forecast evaluation, ECMWF-EPS ranks the best at lead times shorter than 72 h, while NCEP-GEFS ranks the best later on.     

Dvorak技术估测热带气旋强度研究进展

在常规观测资料稀少的热带洋面上,卫星云图是监测热带气旋的主要工具。Dvorak技术通过一系列经验规则,将热带气旋在卫星云图中表现出来的云系结构特征及特定的参数同其发展强度联系起来。介绍了利用Dvorak技术估测热带气旋强度的研究背景和原理方法,总结了国内外在该领域的研究进展及其存在的优势和不足,指出Dvorak技术是目前业务化估测热带气旋强度的主要工具,同时展望了该技术未来的发展方向。     

Importance of Air-Sea Coupling in Simulating Tropical Cyclone Intensity at Landfall

An atmosphere-only model system for making seasonal prediction and projecting future intensities of landfalling tropical cyclones (TCs) along the South China coast is upgraded by including ocean and wave models. A total of 642 TCs have been re-simulated using the new system to produce a climatology of TC intensity in the South China Sea. Detailed comparisons of the simulations from the atmosphere-only and the fully coupled systems reveal that the inclusion of the additional ocean and wave models enable differential sea surface temperature responses to various TC characteristics such as translational speed and size. In particular, interaction with the ocean does not necessarily imply a weakening of the TC, with the coastal bathymetry possibly playing a role in causing a near-shore intensification of the TC. These results suggest that to simulate the evolution of TC structure more accurately, it is essential to use an air-sea coupled model instead of an atmosphere-only model.     

Uncertainty in Tropical Cyclone Intensity Predictions due to Uncertainty in Initial Conditions

Focusing on the role of initial condition uncertainty, we use WRF initial perturbation ensemble forecasts to investigate the uncertainty in intensity forecasts of Tropical Cyclone(TC) Rammasun(1409), which is the strongest TC to have made landfall in China during the past 50 years. Forecast results indicate that initial condition uncertainty leads to TC forecast uncertainty, particularly for TC intensity. This uncertainty increases with forecast time, with a more rapid and significant increase a...     

热带气旋强度与结构研究新进展

主要回顾热带气旋(TC)强度与结构变化的研究发展近况。以往热带气旋的理论研究认为在给定的大气和海洋热状况下,存在着一个TC所能达到的最大可能强度(MPI)。但实际上,海洋生成的热带气旋达到的最大强度普遍要比由MPI理论计算得到最大强度要低。近几年的研究表明,存在着内部和外部的不利因子通过对TC结构的改变来阻碍其加强,从而限制TC的强度。以往认为在诸多因子中,垂直风切变产生的内核区非对称结构与眼墙区下方海水上涌造成的海面冷却是制约TC达到MPI的主要因子。最新的研究进一步指出,产生TC非对称性的中尺度过程对其强度与结构的变化至关重要。中尺度过程包含有对流耦合的涡旋Rossby波、内外圈螺旋雨带、嵌于TC环流内的中尺度涡旋。外部的环境气流也是通过这些眼墙的中尺度过程影响到TC的强度与结构变化。     

Understanding of the Effect of Climate Change on Tropical Cyclone Intensity: A Review

The effect of climate change on tropical cyclone intensity has been an important scientific issue for a few decades.Although theory and modeling suggest the intensification of tropical cyclones in a warming climate,there are uncertainties in the assessed and projected responses of tropical cyclone intensity to climate change.While a few comprehensive reviews have already provided an assessment of the effect of climate change on tropical cyclone activity including tropical cyclone intensity,this review focuses mainly on the understanding of the effect of climate change on basin-wide tropical cyclone intensity,including indices for basin-wide tropical cyclone intensity,historical datasets used for intensity trend detection,environmental control of tropical cyclone intensity,detection and simulation of tropical cyclone intensity change,and some issues on the assessment of the effect of climate change on tropical cyclone intensity.In addition to the uncertainty in the historical datasets,intertwined natural variabilities,the considerable model bias in the projected large-scale environment,and poorly simulated inner-core structures of tropical cyclones,it is suggested that factors controlling the basin-wide intensity can be different from individual tropical cyclones since the assessment of the effect of climate change treats tropical cyclones in a basin as a whole.