Current status and challenges of typhoon forecasting and warning systems in China

China is one of the countries most severely suffering from tropical cyclones. The exact and timely forecasting and warning is of significant importance in fighting against tropical cyclones and mitigating their impacts on China. The numerical weather prediction(NWP)system for tropical cyclone rainfall and strong wind is going to play a more and more important role. There is also a need for timely and user friendly modern warning services in order to provide the governments and relevant authorities at all levels and general public with typhoon forecasts and information about the associated disasters and response strategy services.

Assimilation of atmospheric infrared sounder radiances with WRF-GSI for improving typhoon forecast

The Atmospheric Infrared Sounder （AIRS） can provide the profile information on atmospheric temperature and humidity in high vertical resolution. The assimilation of its radiances has been proven to improve the Numerical Weather Prediction （NWP） in global models. In this study, regional assimilation of AIRS radiances was carried out in a community assimilation system, using Gridpoint Statistical Interpolation （GSI） coupled with the Weather Research and Forecasting （WRY） model. The AIRS channel selection, quality control, and radiances bias correction were examined and illustrated for optimized assimilation. The bias correction scheme in the regional model showed that corrections on most of the channels produce satisfactory results except for several land surface channels. The assimilation and forecast experiments were carried out for three typhoon cases （Saola, Damrey, and Haikui in 2012） with and without including AIRS radiances. Results show that the assimilation of AIRS radiances into the WRF/GSI model improves both the typhoon track and intensity in a 72-hour forecast.

A baroclinic typhoon model with a moving multi-nested grid andvariational adjustment initializationII. Forecast experiments

A 3-dimensional baroclinic typhoon model with a moving multi-nested grid and its initialization are described first. Prediction results are improved by using a simple but effective data assimilation method in which the initial field is adjusted by the sixth hour's typhoon report and the weak-constraint variational principle. Finally someforecast examples made by this typhoon model are given.

AN ENSEMBLE FORECAST EXPERIMENT OF A LANDING TYPHOON

Based on the Global Regional Assimilation and Prediction System-Tropical Cyclone Model(GRAPES-TCM),an ensemble forecast experiment was performed,in which Typhoon Wipha during the period immediately prior to landfall was selected for the study and the breeding of growing mode(BGM) method was used to perturb the initial conditions of the vortex field and the environment field.The results of the experiment indicate that each member had a different initial status in BGM processing and they show a reasonable spread among members along with the forecast phase.Changes in the large-scale field,thermodynamic structure,and spread among members took place when Wipha made landfall.The steering effect of the large-scale field and the interaction between the thermodynamics and the dynamics resulted in different tracks of the members.Meanwhile,the forecast uncertainty increased.In summary,the ensemble mean did not perform as well as the control forecast,but the cluster mean provided some useful information,and performed better than the control in some instances.The position error was 34 km for 24 h forecast,153 km for 48 h forecast,and 191 km for 66 h forecast.The strike probability chart qualitatively described the forecast uncertainty.

Optimization of multi-model ensemble forecasting of typhoon waves

Accurately forecasting ocean waves during typhoon events is extremely important in aiding the mitigation and minimization of their potential damage to the coastal infrastructure, and the protection of coastal communities. However, due to the complex hydrological and meteorological interaction and uncertainties arising from different modeling systems, quantifying the uncertainties and improving the forecasting accuracy of modeled typhoon-induced waves remain challenging. This paper presents a practical approach to optimizing model-ensemble wave heights in an attempt to improve the accuracy of real-time typhoon wave forecasting. A locally weighted learning algorithm is used to obtain the weights for the wave heights computed by the WAVEWATCH III wave model driven by winds from four different weather models （model-ensembles）. The optimized weights are subsequently used to calculate the resulting wave heights from the model-ensembles. The results show that the opti- mization is capable of capturing the different behavioral effects of the different weather models on wave generation. Comparison with the measurements at the selected wave buoy locations shows that the optimized weights, obtained through a training process, can significantly improve the accuracy of the forecasted wave heights over the standard mean values, particularly for typhoon-induced peak waves. The results also indicate that the algorithm is easy to imnlement and practieal for real-time wave forecasting.

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.

AN EXPERIMENT WITH THE CONSENSUS FORECAST OF TYPHOON TRACK

Obvious results have been achieved in the forecast of typhoon track that is improved with a consensus procedure Forecast experiments were conducted with the analogue model (TSF) and the Markov type model (MTSF)that are widely used and the results show that there has been significant increase in the capability of forecasting with the improvement by the consensus procedure.

EXPERIMENTS OF ENSEMBLE FORECAST OF TYPHOON TRACK USING BDA PERTURBING METHOD

A new method, BDA perturbing, is used in ensemble forecasting of typhoon track. This method isbased on the Bogus Data Assimilation scheme. It perturbs the initial position and intensity of typhoons and gets aseries of bogus vortex. Then each bogus vortex is used in data assimilation to obtain initial conditions. Ensembleforecast members are constructed by conducting simulation with these initial conditions. Some cases of typhoonare chosen to test the validity of this new method and the results show that: using the BDA perturbing method toperturb initial position and intensity of typhoon for track forecast can improve accuracy, compared with the directuse of the BDA assimilation scheme. And it is concluded that a perturbing amplitude of intensity of 5 hPa isprobably more appropriate than 10 hPa if the BDA perturbing method is used in combination with initialposition perturbation.

UPGRADING OF TROPICAL LIMITED－AREA NUMERICAL MODEL AND APPLICATION IN TYPHOON FORECAST

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CHGS method for numerical forecasting of typhoon waves-Ⅰ. Spectrum of waves in growing phase

Owing to the fact that the wind speed and direction of typhoon vary rapidly with time and space in typhoon fetch; the nearer to the typhoon eye the greater the wind velocity, and the shorter the wind fetch the smaller the wind time,as a result,the more difficult for the wind wave to fully grow. Hence.in typhoon wave numerical calculation it is impossible to use the model for a fully grown wave spectrum. Lately, the author et at. presented a CHGS method for numerical forecasting of typhoon waves, where a model for the growing wave spectrum was set up (see Eq. (2) in the text). The model involves a parameter indicating the growing degree of wind wave, i. e. ,the mean wave age β. When βvalue is small, the wave energy is chiefly concentrated near the peak frequency, so that the spectral peak gets high and steep; with the increase of β the spectral shape gradually gets lower and gentler; when β=Ⅰ, the wave fully grows, the growing spectrum becomes a fully grown P-M spectrum. The model also shows a spectral “overshooting” phenomenon within the “balance zone”.

A SIMILARITY SCHEME FOR QUANTITATIVE FORECAST OF PRECIPITATION OF TYPHOONS

A quantitative scheme is put forward in our work of forecasting the storm rainfall of typhoons for specific sites.Using the initial parameters,weather situations and physical quantities as well as numerical weather prediction products,the scheme constructs multivariate,objective and similarity criteria for environmental factors for the time between the current and forthcoming moment within the domain of forecast.Through defining a non-linear similarity index,this work presents a comprehensive assessment of the similarity between historical samples of typhoons and those being forecast in terms of continuous dynamic states under the multivariate criteria in order to identify similar samples.The historical rainfall records of the similar samples are used to run weighted summarization of the similarity index to determine site-specific and quantitative forecasts of future typhoon rainfall.Samples resembling the typhoon being forecast are selected by defining a non-linear similarity index composed of multiple criteria.Trial tests have demonstrated that this scheme has positive prediction skill.

河南2023年麦收期连阴雨极端特征及预报偏差分析

基于多尺度观测资料、多种数值模式和主观预报产品,分析了2023年河南麦收关键期出现的连续降水天气过程的极端性特征,并对主客观预报进行检验评估。结果表明:5月20日至6月4日累计降水量距平百分率全省平均为170.3%,累计雨量有17个站达到历史同期排名第一;5月25日至6月4日出现长达11天的全省范围的连阴雨过程,历史排名第二。2023年5月2530日500 hPa平均场副高西伸脊点较气候态偏西33个经度以上,河南上空高度场较气候态高出160~200 gpm。中层气流变化导致降水系统移动方向发生变化,是豫西强降水漏报的主要原因;模式对台风和副高位置预报的偏差,是导致雨带向南偏差的直接原因,进而导致各数值模式暴雨以上量级降水评分偏低。豫西地形对风场影响的机理较为复杂,需对更多个例诊断分析,得到客观结论。

考虑台风事件影响的日降水预报检验与订正

【目的】台风带来的强降水常给当地带来洪涝等灾害,在台风事件下提供准确可靠的降水预报是科学研究和业务预报的重要工作。【方法】通过台风路径缓冲区筛选台风场次,检验台风事件和非台风事件分布情况;对美国国家环境预报中心提供的GEFSv12逐日原始降水预报检验数据精度情况,评价原始预报技巧;应用伯努利-伽马-高斯模型对GEFSv12降水预报,在我国粤港澳大湾区格点,设计不同订正方案,在不同降水场景下,评估不同情况下模型订正前后预报性能。【结果】影响我国东南沿海台风登陆时间主要集中于7—9月,台风等级集中在14级以前;台风事件下,利用台风事件样本训练模型订正后预报BIAS接近0,排序概率技巧得分CRPSS平均提高了近15%,α-index相对原始预报提升了约0.16。【结论】伯努利-伽马-高斯模型能有效订正原始预报存在的系统偏差,提高预报的准确性;不同降水场景订正效果有所区别,对出现极值降水较少的非台风事件,订正后效果有更好的表现;台风事件下,利用台风样本训练模型订正效果相对较好,提高了原始预报精度技巧、可靠性,减少预报偏差;订正的效果和相关系数大小有关,相关系数表现好的区域有更好的预报精度技巧得分,经订正后有利于后续水文集合预报应用、模型发展和备灾应灾工作。

基于CNN-LSTM的珠江河口台风过程实时滚动修正预报

为改善台风预报精度,基于实时滚动修正预报思路,利用卷积神经网络嵌套长短期记忆神经网络(CNN-LSTM)和误差校正(EC)技术,搭建了珠江河口台风实时预报模型。研究结果表明:“滚动预报”比单次预报有更好的路径和强度预报效果,随着模型滚动时间的延长,预报整体精度有逐渐改善的趋势。路径预报结果的均方根误差比单次预报减小了25.67%,强度预报结果的平均绝对误差比单次预报减小了65.04%;考虑误差校正的CNN-LSTM-EC的路径、强度“滚动预报”效果均优于CNN-LSTM,前者的路径预报误差较后者减小了22.57%,强度预报误差减小2.5%。

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(Vr)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 Vr alone and Z alone each improved predictions of typhoon intensity,track,and precipitation;however,the impacts of Vr 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.

2203号台风“暹芭”的路径预报偏差及思考

针对2022年第3号台风“暹芭”的主要特点和预报难点问题进行分析和研究,得出如下主要结论:“暹芭”是2022年首个登陆我国的台风,在华南登陆减弱后,其残余环流继续北上,与西风带系统共同影响我国华中、华东、华北及东北等地的部分地区;累计雨量大、风雨强度强;台风外围出现多个龙卷。主要的预报难点问题有:弱台风准确定位问题表现突出,引进新的卫星产品有助于提高定位精度;72 h路径预报的偏差问题主要是由于模式对东台风、大陆高压和南压高压、西风急流等关键系统的预报偏差引起;台风登陆后北上长时间维持(含减弱后的残涡)的预报问题需关注持续的水汽通道和高层出流条件变化。

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.

2020年北上台风不同模式的预报误差分析

2020年台风“巴威”、“美莎克”和“海神”直接北上引发了辽宁地区大范围的强降水天气过程。针对业务数值预报模式在路径、强度和降水等方面预报存在一定偏差,利用多家数值模式台风预报资料,采用评分检验和空间检验方法对北上台风的模式预报结果进行检验评估,为以后的台风气象预报工作提供参考。结果表明:各模式对台风路径的可预报时效为72 h,随着台风逐渐北上,台风的路径预报误差偏大,台风的强度预报较稳定。在降水的MODE检验结果中,ECMWF全球模式的相似度更高,CMA_MESO_3KM区域模式对降水量级预报偏大,空报较多,但两者对台风降水都有着较好的可参考性,同时台风降水预报效果与台风路径和强度预报密切相关。

浙江省台风影响预测及沿海风险识别系统研究

浙江省台风灾情频发,为科学应对台风威胁,通过优化相似台风匹配算法、对历史台风资料进行整理并作降雨网格化处理、海岸增水数据网格处理和海岸风险分析,切实解决了目前系统存在相似台风匹配不精确、无台风降雨过程和沿海增水展示不直观、缺少海岸线风险识别等问题,为新形势下的台风预报预警提供有力的技术支撑。