Analysis of a Group of Weak Small-Scale Vortexes in the Planetary Boundary Layer in the Mei-yu Front

A mei-yu front process in the lower reaches of the Yangtze River on 23 June 1999 was simulated by using the fifth-generation Pennsylvania State University-NCAR （PSU/NCAR） Mesoscale Model （MM5） with FDDA （Four Dimension Data Assimilation）. The analysis shows that seven weak small mesoscale vortexes of tens of kilometers, correspondent to surface low trough or mesoscale centers, in the planetary boundary layer （PBL） in the mei-yu front were heavily responsible for the heavy rainfall. Sometimes, several weak small-scale vortexes in the PBL could form a vortex group, some of which would weaken locally, and some would develop to be a meso-α-scale low vortex through combination. The initial dynamical triggering mechanism was related to two strong currents： one was the northeast flow in the PBL at the rear of the mei-yu front, the vortexes occurred exactly at the side of the northeast flow; and the other was the strong southwest low-level jet （LLJ） in front of the Mei-yu front, which moved to the upper of the vortexes. Consequently, there were notable horizontal and vertical wind shears to form positive vorticity in the center of the southwest LLJ. The development of mesoscale convergence in the PBL and divergence above, as well as the vertical positive vorticity column, were related to the small wind column above the nose-shaped velocity contours of the northeast flow embedding southwestward in the PBL, which intensified the horizontal wind shear and the positive vorticity column above the vortexes, baroclinicity and instability.

Adjoint Sensitivity Experiments of a Meso-β-scale Vortex in the Middle Reaches of the Yangtze River

A relatively independent and small-scale heavy rainfall event occurred to the south of a slow eastwardmoving meso-α-scale vortex. The analysis shows that a meso-β-scale system is heavily responsible for the intense precipitation. An attempt to simulate it met with some failures. In view of its small scale, short lifetime and relatively sparse observations at the initial time, an adjoint model was used to examine the sensitivity of the meso-β-scale vortex simulation with respect to initial conditions. The adjoint sensitivity indicates how small perturbations of initial model variables anywhere in the model domain can influence the central vorticity of the vortex. The largest sensitivity for both the wind and temperature perturbation is located below 700 hPa, especially at the low level. The largest sensitivity for the water vapor perturbation is located below 500 hPa, especially at the middle and low levels. The horizontal adjoint sensitivity for all variables is mainly located toward the upper reaches of the Yangtze River with respect to the simulated meso-β-scale system in Hunan and Jiangxi provinces with strong locality. The sensitivity shows that warm cyclonic perturbations in the upper reaches can have a great effect on the development of the meso-β-scale vortex. Based on adjoint sensitivity, forward sensitivity experiments were conducted to identify factors influencing the development of the meso-β-scale vortex and to explore ways of improving the prediction. A realistic prediction was achieved by using adjoint sensitivity to modify the initial conditions and implanting a warm cyclone at the initial time in the upper reaches of the river with respect to the meso-β-scale vortex, as is commonly done in tropical cyclone prediction.

FY-3A SATELLITE MICROWAVE DATA ASSIMILATION EXPERIMENTS IN TROPICAL CYCLONE FORECAST

China's new generation of polar-orbiting meteorological satellite FY-3A was successfully launched on May 26,2008,carrying microwave sounding devices which had similar performance to ATOVS of NOAA series.In order to study the application of microwave sounding data in numerical prediction of typhoons and to improve typhoon forecasting,we assimilated data directly for numerical forecasting of the track and intensity of the 2009 typhoon Morakot(0908)based on the WRF-3DVar system.Results showed that the initial fields of the numerical model due to direct assimilation of FY-3A microwave sounding data was improved much more than that due to assimilation of conventional observations alone,and the improvement was especially significant over the ocean,which is always without conventional observations.The model initial fields were more reasonable in reflecting the initial situation of typhoon circulation as well as temperature and humidity conditions,and typhoon central position at sea was also adjusted.Through direct 3DVar assimilation of FY-3A microwave data,the regional mesoscale model improves the forecasting of typhoon track.Therefore,the FY-3A microwave data could efficiently improve the numerical prediction of typhoons.

Moisture Analysis of a Squall Line Case Based on Precipitable Water Vapor Data from a Ground-Based GPS Network in the Yangtze River Delta

A squall line swept eastward across the area of the Yangtze River Delta and produced gusty winds and heavy rain from the afternoon to the evening of 24 August 2002. In this papers the roles of moisture in the genesis and development of the squall line were studied. Based on the precipitable water vapor （PWV） data from a ground-based GPS network over the Yangtze River Delta in China, plus data from a Pennsylvania State University/National Atmospheric Center （PSU/NCAR） mesoscale model （MM5） simulation, initialized by three-dimensional variational （3D-VAR） assimilation of the PWV data, some interesting features are revealed. During the 12 hours prior to the squall line arriving in the Shanghai area, a significant increase in PWV indicates a favorable moist environment for a squall line to develop. The vertical profile of the moisture illustrates that it mainly increased in the middle levels of the troposphere, and not at the surface. Temporal variation in PWV is a better precursor for squall line development than other surface meteorological parameters. The characteristics of the horizontal distribution of PWV not only indicated a favorable moist environment, but also evolved a cyclonic wind field for a squall line genesis and development. The ＂＋2 mm＂ contours of the three-hourly PWV variation can be used successfully to predict the location of the squall line two hours later.

Radar Data Assimilation of the GRAPES Model and Experimental Results in a Typhoon Case

Constructing βmesoscale weather systems in initial fields remains a challenging problem in a mesoscale numerical weather prediction （NWP） model. Without vertical velocity matching the βmesoscale weather system, convection activities would be suppressed by downdraft and cooling caused by precipitating hydrom eteors. In this study, a method, basing on the threedimensional variational （3DVAR） assimilation technique, was developed to obtain reasonable structures of βmesoscale weather systems by assimilating radar data in a nextgeneration NWP system named GRAPES （the Global and Regional Assimilation and Prediction System） of China. Singlepoint testing indicated that assimilating radial wind significantly improved the horizontal wind but had little effect on the vertical velocity, while assimilating the retrieved vertical velocity （taking Richardson’s equation as the observational operator） can greatly improve the vertical motion. Ex periments on a typhoon show that assimilation of the radial wind data can greatly improve the prediction of the typhoon track, and can ameliorate precipitation to some extent. Assimilating the retrieved vertical velocity and rainwater mixing ratio, and adjusting water vapor and cloud water mixing ratio in the initial fields simultaneously, can significantly improve the tropical cyclone rainfall forecast but has little effect on typhoon path. Joint assimilating these three kinds of radar data gets the best results. Taking into account the scale of different weather systems and representation of observational data, data quality control, error setting of background field and observation data are still requiring further indepth study.

THE EFFECTS OF STATION NETWORK DENSITY ON STATISTICAL ANALYSES OF TROPICAL CYCLONE PRECIPITATION

In this paper, 1416 conventional ground-based meteorological observation stations on the mainland of China were subdivided into groups of differing spatial density. Data from each subgroup were then used to analyze variations in the tropical cyclone(TC) precipitation statistics derived from each subgroup across the mainland of China(excluding Taiwan, Hong Kong, and Macao), as well as in two regions(east China and south China) and three provinces(Guangdong, Hainan, and Jiangxi) between 1981 and 2010. The results showed that for the mainland of China, total precipitation, mean annual precipitation, mean daily precipitation, and its spatial distribution were the same regardless of the spatial density of the stations. However, some minor differences were evident with respect to precipitation extremes and their spatial distribution. Overall, there were no significant variations in the TC precipitation statistics calculated from different station density schemes for the mainland of China. The regional and provincial results showed no significant differences in mean daily precipitation, but this was not the case for the maximum daily precipitation and torrential rain frequency. The maximum daily precipitation calculated from the lower-density station data was slightly less than that based on the higher-density station schemes, and this effect should be taken into consideration when interpreting regional climate statistics. The impact of station density on TC precipitation characteristics was more obvious for Hainan than for Guangdong or Jiangxi provinces. In addition, the effects were greater for south China(including Guangxi Zhuang Autonomous region, Guangdong, and Hainan provinces) than east China(including Shandong, Jiangsu, Zhejiang, Shanghai, Fujian, Anhui, and Jiangxi provinces). Furthermore, the analysis proved that the statistical climatic characteristics began to change significantly when the station spacing was between 40 and 50 km,which are close to the mean spacing for all stations across the mainland of China. Moreover, TC areal precipitation parameters, including mean total areal precipitation and mean daily areal precipitation, also began to change significantly when the spacing was between 40 and 50 km, and were completely different when it was between 100 and200 km.

Experiments in Forecasting Mesoscale Convective Weather over Changjiang Delta

The real time operational severe convective weather forecast experiment carried out during May to July in 1990 over the Changjiang Delta is briefly described. The heavy rainfall and severe conveetive weather forecast worksheets for the Changjiang Delta have been proposed and used in the daily forecasting. Results show that the ability of 0-12h convective weather prediction has been improved significantly after the development of the forecast methods and the establishment of a mesoscale forecast base at Shanghai Meteorological Center during 1986 to 1990.Three cases of convective weather systems (meso-alpha, meso-beta, meso-gamma) during the experiment period are described and discussed.

An Application of the Adjoint Method to a Statistical-Dynamical Tropical-Cyclone Prediction Model （SD-90）Ⅱ：Real Tropical Cyclone Cases

In the first paper in this series, a variational data assimilation of ideal tropical cyclone （TC） tracks was performed for the statistical-dynamical prediction model SD-90 by the adjoint method, and a prediction of TC tracks was made with good accuracy for tracks containing no sharp turns. In the present paper, the cases of real TC tracks are studied. Due to the complexity of TC motion, attention is paid to the diagnostic research of TC motion. First, five TC tracks are studied. Using the data of each entire TC track, by the adjoint method, five TC tracks are fitted well, and the forces acting on the TCs are retrieved. For a given TC, the distribution of the resultant of the retrieved force and Coriolis force well matches the corresponding TC track, i.e., when a TC turns, the resultant of the retrieved force and Coriolis force acts as a centripetal force, which means that the TC indeed moves like a particle; in particular, for TC 9911, the clockwise looping motion is also fitted well. And the distribution of the resultant appears to be periodic in some cases. Then, the present method is carried out for a portion of the track data for TC 9804, which indicates that when the amount of data for a TC track is sufficient, the algorithm is stable. And finally, the same algorithm is implemented for TCs with a double-eyewall structure, namely Bilis （2000） and Winnie （1997）, and the results prove the applicability of the algorithm to TCs with complicated mesoscale structures if the TC track data are obtained every three hours.

Structure and Propagation Characteristics of Climatological Mean Kinetic Energy of Disturbance of Intraseasonal Oscillation in Asian Summer Monsoon Zone

[Objective] The research aimed to study the structure and propagation characteristics of climatological mean kinetic energy of disturbance of intraseasonal oscillation in Asian summer monsoon zone. [Method] When South China Sea monsoon started to break out, the kinetic energy of intraseasonal oscillation disturbance in the monsoon zone was analyzed, especially the researches about the variation of South China Sea monsoon, the development of Indian monsoon and the advancement of East Asian monsoon. [Result] The developed process of Asian summer monsoon had the close relationship with the kinetic energy activity of 30-60 d low-frequency oscillation disturbance. The kinetic energy of disturbance explained the eruption, occurrence, development and termination of monsoon from the energy angle. It was found that the kinetic energy of disturbance in Arabian Sea zone, Bay of Bengal and South China Sea area was the strongest, especially in Arabian Sea zone. It illustrated that Arabian Sea zone (Somali jet) was the biggest energy source of Asian monsoon. The starting mark of monsoon eruption in the whole Asia was the abrupt eruption of South China Sea monsoon. The eruption of South China Sea monsoon in the middle dekad of May was the westward transmission result of kinetic energy of disturbance on the east sea surface of Philippines. The kinetic energy of disturbance in East Asian monsoon zone had the seasonal northward advancement in summer. The high kinetic energy center of disturbance in Indian monsoon zone changed from one to two. They were respectively in Arabian Sea and Bay of Bengal. [Conclusion] The research provided the theory basis for analyzing the atmospheric intraseasonal oscillation.

ESTIMATION OF OBSERVATION IMPACT WITH AN ENSEMBLE SENSITIVITY METHOD

The ensemble based forecast sensitivity to observation method by Liu and Kalnay is applied to the SPEEDY-LETKF system to estimate the observation impact of three types of simulated observations.The estimation results show that all types of observations have positive impact on short-range forecast.The largest impact in Northern Hemisphere is produced by rawinsondes,followed by satellite retrieved profiles and cloud drift wind data,which in Southern Hemisphere is produced by satellite retrieved profiles,rawinsondes and cloud drift wind data.Satellite retrieved profiles influence more on the Southern Hemisphere than on the Northern Hemisphere due to few observations from rawinsondes in the Southern Hemisphere.At the level of 200 to 300 h Pa,the largest impact is attributed to wind observations from rawinsondes and cloud drift wind.

Helicity as a Method for Forecasting Severe Weather Events

This paper introduces a method for forecasting severe weather which is yieded by integrating helicity as a dynamical parameter with K and TOT indexes as thermal parameters.The results of operational tests for two years ure detailed.And the seasonal suitability of the method applications is discussed as well.

Predictability of Chinese Summer Extreme Rainfall Based on Arctic Sea Ice and Tropical Sea Surface Temperature

Chinese summer extreme rainfall often brings huge economic losses, so the prediction of summer extreme rainfall is necessary. This study focuses on the predictability of the leading mode of Chinese summer extreme rainfall from empirical orthogonal function(EOF) analysis. The predictors used in this study are Arctic sea ice concentration(ASIC) and regional sea surface temperature(SST) in selected optimal time periods. The most important role that Arctic sea ice(ASI) plays in the appearance of EOF1 may be strengthening the high pressure over North China, thereby preventing water vapor from going north. The contribution of SST is mainly at low latitudes and characterized by a significant cyclone anomaly over South China. The forecast models using predictor ASIC(PA), SST(PS), and the two together(PAS) are established by using data from 1980 to 2004. An independent forecast is made for the last 11 years(2005-2015). The correlation coefficient(COR) skills between the observed and cross-validation reforecast principal components(PC) of the PA, PS, and PAS models are 0.47, 0.66, and 0.76, respectively. These values indicate that SST is a major cause of Chinese summer extreme rainfall during 1980-2004. The COR skill of the PA model during the independent forecast period of 2004-2015 is 0.7, which is significantly higher than those of the PS and PAS models. Thus, the main factor influencing Chinese summer extreme rainfall in recent years has changed from low latitudes to high latitudes. The impact of ASI on Chinese summer extreme rainfall is becoming increasingly significant.

Effect of Using Land Use Data with Building Characteristics on Urban Weather Simulations:A High Temperature Event in Shanghai

Land use data with building characteristics are important for modeling the impacts of urban morphology on local climate.In this study,an extreme heat event in Shanghai,China,was simulated by using a WRF/BEP+BEM(Weather Research and Forecasting/Building Effect Parameterization+Building Energy Model)model.We incorporated local climate zone(LCZ)land use data that resolved urban morphology using 10 classes of building parameters.The simulation was compared to a control case based on MODIS(Moderate-resolution Imaging Spectroradiometer)land use data.The findings are as follows:(1)the LCZ data performed better than the MODIS data for simulating 10-m wind speed.An increase in building height led to the wind speed to decrease by 0.6-1.4 m s^(-1)in the daytime and by 0.2-0.7 m s^(-1)at nighttime.(2)High-rise buildings warmed the air by trapping radiation in the urban canyon.This warming effect was partially offset by the cooling effect of building shadows in the day.As a result,the 2-m temperature increased by 0.8℃ at night but only by 0.4℃ during the day.(3)Heterogeneous urban surfaces increased the 50-m turbulent kinetic energy by 0.4 m^(2) s^(-2),decreased the 10-m wind speed by 1.8 m s^(-1)in the daytime,increased the surface net radiation by 45.1 W m^(2)-,and increased the 2-m temperature by 1.5℃ at nighttime.(4)The LCZ data modified the atmospheric circulation between land and ocean.The shadowing effect reduced the air temperature differences between land and ocean and weakened the sea breeze.Moreover,high-rise buildings obstructed sea breezes,restricting their impact to a smaller portion(10 km along the wind direction)of inland areas compared to that with MODIS.

Evaluation on the applicability of ERA5 reanalysis dataset to tropical cyclones affecting Shanghai

Based on the 16 historical tropical cyclones(TCs)affecting Shanghai from 2007 to 2019,the suitability of ERA5 for studying TCs affecting Shanghai is systematically evaluated from the perspective of TC track,intensity,10-m and upper-level wind,using TC best-track data of China Meteorological Administration and surface observations and sounding data.Corresponding to tropical storm(TS),strong tropical storm(STS),typhoon(TY),strong typhoon(STY)and super typhoon(SuperTY),the median TC track bias is 68.1,52.9,42.5,25.4,and 18.2 km,respectively,the median maximum 10-m wind speed(VMAX10m)bias is-3.7,-6.5,-11.4,-21.7,and-32.2 m·s-1,respectively,and the median minimum mean sea level pressure(MSLPmin)bias is 2.2,5.6,8.1,28.2,and 48.7 hPa,respectively.With the increase of TC intensity,the median TC track bias decreases,while the median VMAX10m and MSLPmin bias increase.In general,VMAX10m in ERA5 is lower than observed,and MSLPmin is larger than observed.Under influence of TS,STS,TY and STY,the median 10-m wind speed(V10m)bias in the city is 3.2,4.2,4.7,and 5.4 m·s-1,respectively,and is 4.4-5.2 m·s-1 near the east coast,respectively.V10m is mostly biased high,showing an"M"type pattern with the distance between TC and Shanghai.The median 10 m wind direction(WD10m)bias is in a range of-7° to+7°.The median upper-level wind speed(Vupper)bias decreases with height,with a maximum of~5 m·s-1 at 975 hPa.Below 900 hPa Vupperin ERA5 is typically larger than the radiosonde observation,and its mean bias error(MBE)increases with TC intensity.The upper-level wind direction(WDupper)matches the sounding data well,with a maximum bias of a few degrees only.The results provide a reference for the application of ERA5 to coastal cities affected by TCs.

Short-Term Dynamic Radar Quantitative Precipitation Estimation Based on Wavelet Transform and Support Vector Machine

Currently,Doppler weather radar in China is generally used for quantitative precipitation estimation(QPE)based on the Z–R relationship.However,the estimation error for mixed precipitation is very large.In order to improve the accuracy of radar QPE,we propose a dynamic radar QPE algorithm with a 6-min interval that uses the reflectivity data of Doppler radar Z9002 in the Shanghai Qingpu District and the precipitation data at automatic weather stations(AWSs)in East China.Considering the time dependence and abrupt changes of precipitation,the data during the previous 30-min period were selected as the training data.To reduce the complexity of radar QPE,we transformed the weather data into the wavelet domain by means of the stationary wavelet transform(SWT)in order to extract high and low-frequency reflectivity and precipitation information.Using the wavelet coefficients,we constructed a support vector machine(SVM)at all scales to estimate the wavelet coefficient of precipitation.Ultimately,via inverse wavelet transformation,we obtained the estimated rainfall.By comparing the results of the proposed method(SWTSVM)with those of Z=300×R1.4,linear regression(LR),and SVM,we determined that the root mean square error(RMSE)of the SWT-SVM method was 0.54 mm per 6 min and the average Threat Score(TS)could exceed 40%with the exception of the downpour category,thus remaining at a high level.Generally speaking,the SWT-SVM method can effectively improve the accuracy of radar QPE and provide an auxiliary reference for actual meteorological operational forecasting.

Radiative forcing and global warming potential of perfluorocarbons and sulfur hexafluoride

We developed two radiation parameterizations with different resolutions(17-band and 998-band) for perfluorocarbons(PFCs) and sulfur hexafluoride(SF6) using the updated High-resolution Transmission Molecular Absorption(HITRAN) 2004 database and the correlated k-distribution method.We analyzed the impacts of the two radiation schemes on heating rates.Then we studied their instantaneous radiative efficiency,stratospheric adjusted radiative efficiency,global warming potential(GWP),and global temperature potential(GTP),for both clear-and all-sky conditions using a high-resolution radiation scheme.We found that the stratosphere-adjusted radiative efficiencies of C2F6,CF4,and SF6 for the whole sky were 0.346,0.098,and 0.680 W m-2 ppbv-1,respectively.Radiative forcing from the industrial revolution to 2005 was 0.001,0.007,and 0.004 W m-2,re-spectively;and was predicted to rise to 0.008,0.036,and 0.037 W m-2,respectively,by 2100,according to emission scenarios provided by the IPCC.The GWPs of C2F6,CF4,and SF6 are 17035,7597,and 31298,respectively,for a time horizon of 100 years relative to CO2.Their GTPs of pulse and sustained emissions,GTPP and GTPS,are 22468,10052,and 40935 and 16498,7355,and 30341,respectively,for a 100-year time horizon.

THE PERFORMANCE OF GLOBAL MODELS IN TC TRACK FORECASTING OVER THE WESTERN NORTH PACIFIC FROM 2010 TO 2012

Forecasts of tropical cyclone(TC)tracks from six global models during 2010 and 2012 were assessed to study the current capability of track forecast guidance over the western North Pacific.To measure the performance of the global model forecasts,a series of statistical evaluations of track forecasts up to 120 h were carried out,including the mean,median,percentile distribution,regional distribution,relative position,correlation analysis,and binned analysis.Results showed that certain improvements have been made for the six global models in their prediction accuracy and stability in the past three years.Remarkably,stepped decreases in the values of each quantile were found at all lead time levels from 2010 to 2012 for NCEP-GFS.An analysis of the regional distribution of position errors showed that a high-latitude region,low-latitude region(which covers mostly the TC genesis region)and the South China Sea are the three main areas within which large errors tend to concentrate.The majority of the models show their own respective characteristics of systematic bias at each lead time,as established through the relative position analysis results.Only the results of NCEP-GFS and CMA-T639 did not show any obvious systematic bias in the three-year study period.Binned analyses indicated that the prediction accuracy and stability of most of the models were better for strong TCs than for weak TCs at short lead time levels.It was also found that the models tend to perform better for initially large TCs,or for those with weak vertical wind shear at lead times shorter than 48 h.The results demonstrate the heavy reliance of forecast errors upon the initial characteristics of a TC or its environmental conditions.

Correlation Between Total Lightning Activity and Precipitation Particle Characteristics Observed from 34 Thunderstorms

A total of 34 thunderstorms around Shanghai and Wuhan of China are analyzed in order to determine the relationship between total lightning activity and precipitation particle characteristics.Precipitation particle concentration data are obtained from the 2A12 product of TRMM/TMI（Tropical Rainfall Measuring Mission/TRMM Microwave Image） and lightning activity data are from the TRMM/LIS（Lightning Imaging Sensor） and SAFIR3000（Surveillance et Alerte Founder par Interferometric Radioelectirque）.On a spatial scale of 0.1°×0.1°,a weak spatial relationship is found between total lightning and the vertically integrated content（VIC） of precipitation particles（cloud water,precipitation water,cloud ice,and precipitation ice）. A strong power relationship is identified between the lightning density（D_（30）;fl km^（-2） min^（-1））,relative to a rainfall intensity threshold value of 30 mm h^（-1）,and the maximum rainfall intensity（R_（max）;mm h^（-1））;the obtained regression equation is R_（max） = 23.10D_（30）^（0.18） ＋ 11,with a correlation coefficient of 0.841.Lightning frequency shows a significant linear correlation with the contents and covering areas of precipitation particles （in which the VICs exceed threshold values）.Furthermore,ice particles above the -10℃level exhibit a stronger correlation with lightning activity than those above the 0℃level or the integrated ice particles at all levels.The results demonstrate that the particles responsible for the most significant charging process and lightning activity are restricted by the threshold value of VIC among the particles,which reflects the demand of the charging process on dynamic characteristics.The obtained fitting equations can provide useful reference for assimilating lightning information into numerical prediction models so as to improve the reliability of forecast results.The particle products from the prediction models are also helpful in estimating the occurrence of lightning activity within 2-6-h periods.

EVALUATION OF TROPICAL CYCLONE FORECASTS FROM OPERATIONAL GLOBAL MODELS OVER THE WESTERN NORTH PACIFIC IN 2013

Tropical cyclones(TCs)forecasts from seven global models in 2013 were assessed to study the current capability of track and intensity forecast guidance over the western North Pacific.Analysis of along-and cross-track error revealed stepped decreases in the values of each quantile at each lead time level by showing the annual track error distribution from 2010 to 2013,particularly in the ECMWF-IFS,NCEP-GFS and UKMO-Met UM models.The TC propagation direction was much easier to handle for most of the global models;however,the propagation speed seemed to be more closely linked to the inner-core dynamics and thus processes that take place at smaller spatial scales.A new model evaluation tool,‘track error rose’,was used to analyze the models’systematic error in the track forecast using the same concepts as the‘wind rose’.The results showed that as the lead time increased,most of the global models forecast a TC moving speed that was slower than observations and the largest track error often appeared around the rear direction of the observation position.Another new model evaluation tool,the Taylor diagram,was used to evaluate the intensity predictions from the global models.A Taylor diagram provides a way of plotting standard deviation,centered root mean square,and the correlation coefficient on a two-dimensional graph,indicating how closely a predicted TC intensity matches observations.This made it easy to distinguish the intensity forecast performance of the seven global models and determine which models were in relatively good agreement with observations.Furthermore,it also provided a statistical measure of the correlation between modeled and observed TC intensity,offering a practical way of assessing and summarizing model capability.