A Physics-informed Deep-learning Intensity Prediction Scheme for Tropical Cyclones over the Western North Pacific

Accurate prediction of tropical cyclone(TC)intensity is challenging due to the complex physical processes involved.Here,we introduce a new TC intensity prediction scheme for the western North Pacific(WNP)based on a time-dependent theory of TC intensification,termed the energetically based dynamical system(EBDS)model,together with the use of a long short-term memory(LSTM)neural network.In time-dependent theory,TC intensity change is controlled by both the internal dynamics of the TC system and various environmental factors,expressed as environmental dynamical efficiency.The LSTM neural network is used to predict the environmental dynamical efficiency in the EBDS model trained using besttrack TC data and global reanalysis data during 1982–2017.The transfer learning and ensemble methods are used to retrain the scheme using the environmental factors predicted by the Global Forecast System(GFS)of the National Centers for Environmental Prediction during 2017–21.The predicted environmental dynamical efficiency is finally iterated into the EBDS equations to predict TC intensity.The new scheme is evaluated for TC intensity prediction using both reanalysis data and the GFS prediction data.The intensity prediction by the new scheme shows better skill than the official prediction from the China Meteorological Administration(CMA)and those by other state-of-art statistical and dynamical forecast systems,except for the 72-h forecast.Particularly at the longer lead times of 96 h and 120 h,the new scheme has smaller forecast errors,with a more than 30%improvement over the official forecasts.

Westerlies Affecting the Seasonal Variation of Water Vapor Transport over the Tibetan Plateau Induced by Tropical Cyclones in the Bay of Bengal

This study investigates the activity of tropical cyclones(TCs)in the Bay of Bengal(BOB)from 1979 to 2018 to discover the mechanism affecting the contribution rate to the meridional moisture budget anomaly(MMBA)over the southern boundary of the Tibetan Plateau(SBTP).May and October–December are the bimodal phases of BOB TC frequency,which decreases month by month from October to December and is relatively low in May.However,the contribution rate to the MMBA is the highest in May.The seasonal variation in the meridional position of the westerlies is the key factor affecting the contribution rate.The relatively southern(northern)position of the westerlies in November and December(May)results in a lower(higher)contribution rate to the MMBA.This mechanism is confirmed by the momentum equation.When water vapor enters the westerlies near the trough line,the resultant meridional acceleration is directed north.It follows that the farther north the trough is,and the farther north the water vapor can be transported.When water vapor enters the westerlies from the area near the ridge line,for Type-T(Type-R)TCs,water vapor enters the westerlies downstream of the trough(ridge).Consequently,the direction of the resultant meridional acceleration is directed south and the resultant zonal acceleration is directed east(west),which is not conducive to the northward transport of water vapor.This is especially the case if the trough or ridge is relatively south,as the water vapor may not cross the SBTP.

Roles of Upper-Level Descending Inflow in Moat Development in Simulated Tropical Cyclones with Secondary Eyewall Formation

This study investigated the effects of upper-level descending inflow(ULDI)associated with inner-eyewall convection on the formation of the moat in tropical cyclones(TCs)with secondary eyewall formation(SEF).In our numerical experiments,a clear moat with SEF occurred in TCs with a significant ULDI,while no SEF occurred in TCs without a significant ULDI.The eyewall convection developed more vigorously in the control run.A ULDI occurred outside the inner-eyewall convection,where it was symmetrically unstable.The ULDI was initially triggered by the diabatic warming released by the inner eyewall and later enhanced by the cooling below the anvil cloud.The ULDI penetrated the outer edge of the inner eyewall with relatively dry air and prevented excessive solid-phase hydrometeors from being advected further outward.It produced extensive sublimation cooling of falling hydrometeors between the eyewall and the outer convection.The sublimation cooling resulted in negative buoyancy and further induced strong subsidence between the eyewall and the outer convection.As a result,a clear moat was generated.Development of the moat in the ongoing SEF prevented the outer rainband from moving farther inward,helping the outer rainband to symmetrize into an outer eyewall.In the sensitivity experiment,no significant ULDI formed since the eyewall convection was weaker,and the eyewall anvil developed relatively lower,meaning the formation of a moat and thus an outer eyewall was less likely.This study suggests that a better-represented simulation of inner-eyewall convective structures and distribution of the solid-phase hydrometeors is important to the prediction of SEF.

Track-Pattern-Based Characteristics of Extratropical Transitioning Tropical Cyclones in the Western North Pacific

Based on the Regional Specialized Meteorological Center(RSMC)Tokyo-Typhoon Center best-track data and the NCEP-NCAR reanalysis dataset,extratropical transitioning(ET)tropical cyclones(ETCs)over the western North Pacific(WNP)during 1951–2021 are classified into six clusters using the fuzzy c-means clustering method(FCM)according to their track patterns.The characteristics of the six hard-clustered ETCs with the highest membership coefficient are shown.Most tropical cyclones(TCs)that were assigned to clusters C2,C5,and C6 made landfall over eastern Asian countries,which severely threatened these regions.Among landfalling TCs,93.2%completed their ET after landfall,whereas 39.8%of ETCs completed their transition within one day.The frequency of ETCs over the WNP has decreased in the past four decades,wherein cluster C5 demonstrated a significant decrease on both interannual and interdecadal timescales with the expansion and intensification of the western Pacific subtropical high(WPSH).This large-scale circulation pattern is favorable for C2 and causes it to become the dominant track pattern,owning to it containing the largest number of intensifying ETCs among the six clusters,a number that has increased insignificantly over the past four decades.The surface roughness variation and three-dimensional background circulation led to C5 containing the maximum number of landfalling TCs and a minimum number of intensifying ETCs.Our results will facilitate a better understanding of the spatiotemporal distributions of ET events and associated environment background fields,which will benefit the effective monitoring of these events over the WNP.

Environmental Conditions Conducive to the Formation of Multiple Tropical Cyclones over the Western North Pacific

There is limited understanding regarding the formation of multiple tropical cyclones(MTCs).This study explores the environmental conditions conducive to MTC formation by objectively determining the atmospheric circulation patterns favorable for MTC formation over the western North Pacific.Based on 199 MTC events occurring from June to October 1980–2020,four distinct circulation patterns are identified:the monsoon trough(MT)pattern,accounting for 40.3%of occurrences,the confluence zone(CON)pattern at 26.2%,the easterly wave(EW)pattern at 17.8%,and the monsoon gyre(MG)pattern at 15.7%.The MT pattern mainly arises from the interaction between the subtropical high and the monsoon trough,with MTCs forming along the monsoon trough and its flanks.The CON pattern is affected by the subtropical high,the South Asian high,and the monsoon trough,with MTCs emerging at the confluence zone where the prevailing southwesterly and southeasterly flows converge.The EW pattern is dominated by easterly flows,with MTCs developing along the easterly wave train.MTCs in the MG pattern arise within a monsoon vortex characterized by strong southwesterly flows.A quantitative analysis further indicates that MTC formation in the MT pattern is primarily governed by mid-level vertical velocity and low-level vorticity,while mid-level humidity and vertical velocity are significantly important in the other patterns.The meridional shear and convergence of zonal winds are essential in converting barotropic energy from the basic flows to disturbance kinetic energy,acting as the primary source for eddy kinetic energy growth.

Comprehensive Risk Assessment of Sea Level Rise and Tropical Cyclones in Dongzhaigang Mangroves,China

Mangroves play a pivotal role in tropical and subtropical coastal ecosystem,yet they are highly vulnerable to the effects of climate change,particularly the accelerated global sea level rise(SLR)and stronger tropical cyclones(TCs).However,there is a lack of research addressing future simultaneous combined impacts of the slow-onset of SLR and rapid-onset of TCs on China's mangroves.In order to develop a comprehensive risk assessment method considering the superimposed effects of these two factors and analyze risk for mangroves in Dongzhaigang,Hainan Island,China,we used observational and climate model data to assess the risks to mangroves under low,intermediate,and very high greenhouse gas(GHG)emission scenarios(such as SSP1-2.6,SSP2-4.5,and SSP5-8.5)in 2030,2050,and 2100,and compiled a risk assessment scheme for mangroves in Dongzhaigang,China.The results showed that the combined risks from SLR and TCs will continue to rise;however,SLRs will increase in intensity,and TCs will decrease.The comprehensive risk of the Dongzhaigang mangroves posed by climate change will remain low under SSP1-2.6 and SSP2-4.5 scenarios by 2030,but it will increase substantially by 2100.While under SSP5-8.5 scenario,the risks to mangroves in Dongzhaigang are projected to increase considerably by 2050,and approximately 68.8%of mangroves will be at very high risk by 2100.The risk to the Dongzhaigang mangroves is not only influenced by the hazards but also closely linked to their exposure and vulnerability.We therefore propose climate resilience developmental responses for mangroves to address the effects of climate change.This study for the combined impact of TCs and SLR on mangroves in Dongzhaigang,China can enrich the method system of mangrove risk assessment and provide references for scientific management.

Effect of the Initial Vortex Structure on Intensity Change During Eyewall Replacement Cycle of Tropical Cyclones:A Numerical Study

This study investigates the effect of the initial tropical cyclone(TC)vortex structure on the intensity change during the eyewall replacement cycle(ERC)of TCs based on two idealized simulations using the Weather Research and Forecasting(WRF)model.Results show that an initially smaller TC with weaker outer winds experienced a much more drastic intensity change during the ERC than an initially larger TC with stronger outer winds.It is found that an initially larger TC vortex with stronger outer winds favored the development of more active spiral rainbands outside the outer eyewall,which slowed down the contraction and intensification of the outer eyewall and thus prolonged the duration of the concentric eyewall and slow intensity evolution.In contrast,the initially smaller TC with weaker outer winds corresponded to higher inertial stability in the inner core and weaker inertial stability but stronger filamentation outside the outer eyewall.These led to stronger boundary layer inflow,stronger updraft and convection in the outer eyewall,and suppressed convective activity outside the outer eyewall.These resulted in the rapid weakening during the formation of the outer eyewall,followed by a rapid re-intensification of the TC during the ERC.Our study demonstrates that accurate initialization of the TC structure in numerical models is crucial for predicting changes in TC intensity during the ERC.Additionally,monitoring the activity of spiral rainbands outside the outer eyewall can help to improve short-term intensity forecasts for TCs experiencing ERCs.

Simulation of the Effects of SST Changes Induced by Tropical Cyclones on the Intensity of Tropical Cyclone Bilis(0604)

The effects of sea surface temperature(SST)changes induced by tropical cyclone(TC)Bilis(0604)and its preceding TC,TC Ewiniar(0603),on the intensity of TC Bilis were investigated by using numerical experiments.The observed SST changes induced by TCs Ewiniar(0603)and Bilis(0604)were first separated by using the smooth filtering and cylindrical filtering methods.The maximum SST cooling induced by TC Ewiniar(0603)exceeded 3℃,and that induced by the two TCs,Ewiniar(0603)and Bilis(0604),exceeded 6℃.The simulation results show that the SST cooling induced by TC Ewiniar(0603)and by two TCs reduced the intensity of TC Bilis(0604)by 6.2 m s^(-1)and 7.6 m s^(-1)within 60 h,respectively.Without the SST cooling induced by TC Ewiniar(0603),TC Bilis(0604)could have developed into a typhoon.The cold wake induced by TC Ewiniar(0603)was an important factor in inhibiting the intensity of TC Bilis(0604).Based on the analysis of the physical processes of the simulation results,a schematic diagram of the effects of SST changes induced by TCs on the intensity of TC Bilis(0604)was presented.The SST cooling reduced the upward heat flux and moisture flux at the surface of TC mainly within a radius of two latitudes,which in turn decreased the conditional instability and atmospheric moisture in the lower layer of TC,followed by weakening in TC precipitation,TC warm core,the upward vertical velocity of TC,and the inward radial wind in the lower layer of TC.The intensity of TC Bilis(0604)decreased accordingly.

Short-Term Rolling Prediction of Tropical Cyclone Intensity Based on Multi-Task Learning with Fusion of Deviation-Angle Variance and Satellite Imagery

Tropical cyclones(TCs)are one of the most serious types of natural disasters,and accurate TC activity predictions are key to disaster prevention and mitigation.Recently,TC track predictions have made significant progress,but the ability to predict their intensity is obviously lagging behind.At present,research on TC intensity prediction takes atmospheric reanalysis data as the research object and mines the relationship between TC-related environmental factors and intensity through deep learning.However,reanalysis data are non-real-time in nature,which does not meet the requirements for operational forecasting applications.Therefore,a TC intensity prediction model named TC-Rolling is proposed,which can simultaneously extract the degree of symmetry for strong TC convective cloud and convection intensity,and fuse the deviation-angle variance with satellite images to construct the correlation between TC convection structure and intensity.For TCs'complex dynamic processes,a convolutional neural network(CNN)is used to learn their temporal and spatial features.For real-time intensity estimation,multi-task learning acts as an implicit time-series enhancement.The model is designed with a rolling strategy that aims to moderate the long-term dependent decay problem and improve accuracy for short-term intensity predictions.Since multiple tasks are correlated,the loss function of 12 h and 24 h are corrected.After testing on a sample of TCs in the Northwest Pacific,with a 4.48 kt root-mean-square error(RMSE)of 6 h intensity prediction,5.78 kt for 12 h,and 13.94 kt for 24 h,TC records from official agencies are used to assess the validity of TC-Rolling.

Vision Transformer for Extracting Tropical Cyclone Intensity from Satellite Images

Tropical cyclone(TC)intensity estimation is a fundamental aspect of TC monitoring and forecasting.Deep learning models have recently been employed to estimate TC intensity from satellite images and yield precise results.This work proposes the ViT-TC model based on the Vision Transformer(ViT)architecture.Satellite images of TCs,including infrared(IR),water vapor(WV),and passive microwave(PMW),are used as inputs for intensity estimation.Experiments indicate that combining IR,WV,and PMW as inputs yields more accurate estimations than other channel combinations.The ensemble mean technique is applied to enhance the model's estimations,reducing the root-mean-square error to 9.32 kt(knots,1 kt≈0.51 m s^(-1))and the mean absolute error to 6.49 kt,which outperforms traditional methods and is comparable to existing deep learning models.The model assigns high attention weights to areas with high PMW,indicating that PMW magnitude is essential information for the model's estimation.The model also allocates significance to the cloud-cover region,suggesting that the model utilizes the whole TC cloud structure and TC eye to determine TC intensity.

A Generative Adversarial Network with an Attention Spatiotemporal Mechanism for Tropical Cyclone Forecasts

Tropical cyclones(TCs)are complex and powerful weather systems,and accurately forecasting their path,structure,and intensity remains a critical focus and challenge in meteorological research.In this paper,we propose an Attention Spatio-Temporal predictive Generative Adversarial Network(AST-GAN)model for predicting the temporal and spatial distribution of TCs.The model forecasts the spatial distribution of TC wind speeds for the next 15 hours at 3-hour intervals,emphasizing the cyclone's center,high wind-speed areas,and its asymmetric structure.To effectively capture spatiotemporal feature transfer at different time steps,we employ a channel attention mechanism for feature selection,enhancing model performance and reducing parameter redundancy.We utilized High-Resolution Weather Research and Forecasting(HWRF)data to train our model,allowing it to assimilate a wide range of TC motion patterns.The model is versatile and can be applied to various complex scenarios,such as multiple TCs moving simultaneously or TCs approaching landfall.Our proposed model demonstrates superior forecasting performance,achieving a root-mean-square error(RMSE)of 0.71 m s^(-1)for overall wind speed and 2.74 m s^(-1)for maximum wind speed when benchmarked against ground truth data from HWRF.Furthermore,the model underwent optimization and independent testing using ERA5reanalysis data,showcasing its stability and scalability.After fine-tuning on the ERA5 dataset,the model achieved an RMSE of 1.33 m s^(-1)for wind speed and 1.75 m s^(-1)for maximum wind speed.The AST-GAN model outperforms other state-of-the-art models in RMSE on both the HWRF and ERA5 datasets,maintaining its superior performance and demonstrating its effectiveness for spatiotemporal prediction of TCs.

Analysis on causes of tropical cyclones and their disasters affecting on Guangxi coast based on historical data

The tropical cyclone that lands or passes through Guangxi coast is a serious natural disaster, which brings about strong winds, heavy rains, storm surges and other disasters causing severe damage of property or casualties in the coastal region every year. By counting and analyzing the tropical cyclones affecting Guangxi coast from 1950 to 2012, we find that the annual number of tropical cyclones changes significantly, and the maximum value can be up to 9, whereas the minimum value is 0 in some year. The regularity of seasonal distribution of tropical cyclones is obvious, and the peak period is in July, August and September every year, followed by June and October. Most of tropical cyclones come from the east of Philippines. After entering the South China Sea and passing through Hainan province and Leizhou Peninsula, they landed on Guangxi coast once again and caused the mean of peak surge reaching 111.2 cm, which is 2.6 times of non-landing typhoon. The formation of storm surge disaster is directly related to the severe typhoon weather systems, diurnal spring tide and discharge of river flood. Severe typhoons generate huge waves and rainfall, which lead to the rise of water level at the estuary, and would result in significant increasing water when stacking up with the storm surge, and cause huge tidal disaster.

An Overview of Research and Forecasting on Rainfall Associated with Landfalling Tropical Cyclones

The ability to forecast heavy rainfall associated with landfalling tropical cyclones （LTCs） can be improved with a better understanding of the mechanism of rainfall rates and distributions of LTCs. Research in the area of LTCs has shown that associated heavy rainfall is related closely to mechanisms such as moisture transport, extratropical transition （ET）, interaction with monsoon surge, land surface processes or topographic effects, mesoscale convective system activities within the LTC, and boundary layer energy transfer etc.. LTCs interacting with environmental weather systems, especially the westerly trough and mei-yu front, could change the rainfall rate and distribution associated with these mid-latitude weather systems. Recently improved technologies have contributed to advancements within the areas of quantitative precipitation estimation （QPE） and quantitative precipitation forecasting （QPF）. More specifically, progress has been due primarily to remote sensing observations and mesoscale numerical models which incorporate advanced assimilation techniques. Such progress may provide the tools necessary to improve rainfall forecasting techniques associated with LTCs in the future.

A GCM-Based Forecasting Model for the Landfall of Tropical Cyclones in China

A statistical dynamic model for forecasting Chinese landfall of tropical cyclones （CLTCs） was developed based on the empirical relationship between the observed CLTC variability and the hindcast atmospheric circulations from the Pusan National University coupled general circulation model （PNU-CGCM）.In the last 31 years,CLTCs have shown strong year-to-year variability,with a maximum frequency in 1994 and a minimum frequency in 1987.Such features were well forecasted by the model.A cross-validation test showed that the correlation between the observed index and the forecasted CLTC index was high,with a coefficient of 0.71.The relative error percentage （16.3%） and root-mean-square error （1.07） were low.Therefore the coupled model performs well in terms of forecasting CLTCs;the model has potential for dynamic forecasting of landfall of tropical cyclones.

Improvement of wind field hindcasts for tropical cyclones

This paper presents a study on the improvement of wind field hindcasts for two typical tropical cyclones, i.e., Fanapi and Meranti, which occurred in 2010. The performance of the three existing models for the hindcasting of cyclone wind fields is first examined, and then two modification methods are proposed to improve the hindcasted results. The first one is the superposition method, which superposes the wind field calculated from the parametric cyclone model on that obtained from the cross-calibrated multi-platform （CCMP） reanalysis data. The radius used for the superposition is based on an analysis of the minimum difference between the two wind fields. The other one is the direct modification method, which directly modifies the CCMP reanalysis data according to the ratio of the measured maximum wind speed to the reanalyzed value as well as the distance from the cyclone center. Using these two methods, the problem of underestimation of strong winds in reanalysis data can be overcome. Both methods show considerable improvements in the hindcasting of tropical cyclone wind fields, compared with the cyclone wind model and the reanalysis data.

A Comparison of Precipitation Distribution of Two Landfalling Tropical Cyclones during the Extratropical Transition

The precipitation distributions associated with two landfalling tropical cyclones（TCs） during extratropical transition（ET） were examined in this study.Their distinction is that the bulk of precipitation fell to the left of the TC track in one TC and to the right in the other.The analyses indicate that,for the TC Haima（2004） case,accompanied by the approach of a deep midlatitude trough throughout the depth of the troposphere,the warm and moist air advection by the southeasterly flow north of TC was favorable for warm advection and frontogenesis to the northwest of the TC.Due to the steepening of equivalent potential temperature（θ e）,the air-parcel uplift along the θ e surface,in collaboration with thermally direct circulation related to frontogenesis,led to enhanced precipitation northwest of the TC.In contrast,for TC Matsa（2005） embedded within a moister environment,a weak midlatitude trough was situated at the mid-upper level.The convection was triggered by the conditional instability at the lower level and then sustained by dynamic forcing at the mid-upper level so that the heavy precipitation occurred to the northeast of TC.For the two TC cases,the precipitation enhancement was also linked to the upper-level anomalous divergence associated with the jet-related forcing on the right side of the jet entrance.From the quasigeostrophic perspective,the advection of geostrophic absolute vorticity by the thermal wind most likely served as an indication reflecting the displacement of the vertical motion relative to the center of the TC.

CLIMATOLOGICAL FEATURES OF RAPIDLY INTENSIFYING (RI) TROPICAL CYCLONES IN NW PACIFIC WEST OF 135°E^1

Tropical cyclones which rapidly intensify (ΔV≥ 20 m/s in 24 h)in the Northwest Pacific Ocean west of 135°E could have adverse influence on oceanic and coastal economic activities in China, 71% of which land in China. Rapid intensification is mostly seen east and northeast of the Luzon Island. It is much correlated with sea surface temperature(≥28℃)and upper air conditions, such as enhanced subtropical high, onset of Southwest monsoon surge, invasion of modest cold air, and Tropical Upper Tropospheric Trough(TUTT) etc. Abovementioned processes enhance inflows in the low level and deep convection in the area of inner core. Statistics of satellite pixels have confirmed that rapidly intensifying tropical cyclones are marked by a sharp increase in the inner core convection and stable or slowly-increasing deep convection in outer region. Non-rapidly intensifying tropical cyclones have only constant or decreased deep convection in inner core and outer region. The sharp increasing of deep convection in the inner core and the rapid warming in its upper level is a forewarning of rapid intensification of tropical cyclones.

A 28-Year Climatological Analysis of Size Parameters for Northwestern Pacific Tropical Cyclones

A 28-year best track dataset containing size parameters that include the radii of the 15.4 m s^-1 winds （R15） and the 25.7 m s^-1 winds （R26） of tropical cyclones （TCs） in the Northwestern Pacific, the NCEP/ NCAR reanalysis dataset and the Extended Reconstructed Sea Surface Temperature （ERSST） dataset are employed in this study. The climatology of size parameters for the tropical cyclones in the Northwestern Pacific from 1977 to 2004 is investigated in terms of the spatial and temporal distributions. The results show that the major activity of TCs in the Northwestern Pacific is from July to October. A majority of TCs lie over the ocean west of 150°E, and a few TCs can intensify to the Saffir-Simpson （S-S） categories 4, 5. Both R15 and R26 tend to increase as the tropical cyclones intensify. The values of R15 and R26 are larger for intense TCs in the Northwestern Pacific than in the North Atlantic generally. Both R15 and R26 peak in October, and before and after October, R15 and R26 decrease, which is different from the case in the North Atlantic. The smaller R15s and R26s occur in a large range over the Northwestern Pacific, while the larger R15s and R26s mainly lie in the eastern ocean from Taiwan Island to the Philippine Islands where many tropical cyclones develop in intense systems. The tropical cyclones with size parameters of R15 or R26 on average take a longer time to intensify than to weaken, and the weak tropical cyclones have faster weakening rates than intensification rates. From 1977 to 2004, the annual mean values of R15 increase basically with year; during the 28-year period, the value of R15 increases by 52.7 kin, but R26 does not change with year obviously.

The characteristic differences of tropical cyclones forming over the western North Pacific and the South China Sea

The best track dataset of tropical cyclones in the western North Pacific （WNP） and the South China Sea （SCS） from 1977 to 2005 during the satellite era, the NCEP/NCAR reanalysis dataset and the extended reconstructed sea surface temperature dataset are employed in this study. The main climatological characteristics of tropical cyclone formation over the WNP and the SCS are compared. It is found that there is obviously different for the locations of tropical cyclone origins, achieving the lowest central pressure and termination points between over the WNP and over the SCS. The annual number of tropical cyclones forming over the SCS is obviously less than over the WNP, and there is a significant negative correlation with the correlation coefficient being - 0.36 at the 5% significance level between over the WNP and over the SCS. The mean speed of tropical cyclone moving is 6.5 m/s over the WNP and 4.6 m/s over the SCS. The mean lowest central pressure of tropical cyclones is obviously weaker over the SCS than over the WNP. The tropical cyclone days per year, mean total distance and total displacement of tropical cyclone traveled over the WNP are all obviously longer than those over the SCS. Tropical cyclone may intensify to Saffir - Simpson hurricane scale 5 over the WNP, but no tropical cyclone can intensify to Saffir - Simpson hurricane scale 3 over the SCS. The changing ranges of the radii （R15,R16） of the 15.4 m/s winds them and the 25.7 m/s winds over the WNP are obviously wider than those over the SCS, and the median values of the radii over the WNP are also larger than those over the SCS. For the same intensity of tropical cyclones, both radii have larger medians over the WNP than over the SCS. The correlations of annual mean tropical cyclone size parameters between over the WNP and over the SCS are not significant. At the same time, the asymmetric radii of tropical cyclones over the WNP are different from those over the SCS.

Seasonal Forecast Model for the Number of Tropical Cyclones to Make Landfall in China

The year-to-year increment prediction approach proposed by was applied to forecast the annual number of tropical cyclones (TCs) making landfall over China.The year-to-year increase or decrease in the number of land-falling TCs (LTCs) was first predicted to yield a net number of LTCs between successive years.The statistical prediction scheme for the year-to-year increment of annual LTCs was developed based on data collected from 1977 to 2007,which includes five predictors associated with high latitude circulations in both Hemispheres and the circulation over the local,tropical western North Pacific Ocean.The model shows reasonably high predictive ability,with an average root mean square error (RMSE) of 1.09,a mean absolute error (MAE) of 0.9,and a correlation coefficient between the predicted and observed annual number of LTCs of 0.86,accounting for 74% of the total variance.The cross-validation test further demonstrated the high predictive ability of the model,with an RMSE value of 1.4,an MAE value of 1.2,and a correlation coefficient of 0.74 during this period.