An Analysis of the Low Moving Speed of Landfalling Typhoon In-Fa in 2021

The movement speed of Typhoon In-Fa(2021)was notably slow,at 10 km h-1or less,for over 20 hours following its landfall in Zhejiang,China,in contrast to other typhoons that have made landfall.This study examines the factors contributing to the slow movement of Typhoon In-Fa,including the steering flow,diabatic heating,vertical wind shear(VWS),and surface synoptic situation,by comparing it with Typhoons Yagi(2018)and Rumbia(2018)which followed similar tracks.The findings reveal that the movement speed of Typhoons Yagi and Rumbia is most closely associated with their respective 500 h Pa environmental winds,with a steering flow of 10^(-12)m s^(-1).In contrast,Typhoon InFa’s movement speed is most strongly correlated with the 850 h Pa environmental wind field,with a steering flow speed of only 2 m s^(-1).Furthermore,as Typhoon In-Fa moves northwest after landfall,its intensity is slightly greater than that of Typhoons Yagi and Rumbia,and the pressure gradient in front of Typhoon In-Fa is notably smaller,leading to its slow movement.Additionally,the precipitation distribution of Typhoon In-Fa differs from that of the other two typhoons,resulting in a weak asymmetry of wavenumber-1 diabatic heating,which indirectly affects its movement speed.Further analysis indicates that VWS can alter the typhoon’s structure,weaken its intensity,and ultimately impact its movement.

A Time Neighborhood Method for the Verification of Landfalling Typhoon Track Forecast

Landfalling typhoons can cause disasters over large regions.The government and emergency responders need to take measures to mitigate disasters according to the forecast of landfall position,while slight timing error can be ignored.The reliability of operational model forecasts of typhoon landfall position needs to be evaluated beforehand,according to the forecasts and observation of historical cases.In the evaluation of landfalling typhoon track,the traditional method based on point-to-point matching methods could be influenced by the predicted typhoon translation speed.Consequently,the traditional track evaluation method may result in a large track error even if the predicted landfall position is close to observation.The purpose of this paper is to address the above issue using a simple evaluation method of landfalling typhoon track forecast based on the time neighborhood approach.In this new method,the timing error was lessened to highlight the importance of the position error during the landfall of typhoon.The properties of the time neighborhood method are compared with the traditional method based on numerical forecast results of 12 landfalling typhoon cases.Results demonstrated that the new method is not sensitive to the sampling frequency,and that the difference between the time neighborhood and traditional method will be more obvious when the moving speed of typhoon is moderate(between 15−30 km h^(−1)).The time neighborhood concept can be easily extended to a broader context when one attempts to examine the position error more than the timing error.

Numerical Experiments for Typhoon Dan Incorporating AMSU-A Retrieved Data with 3DVM

Two sets of assimilation experiments on a landfalling typhoon--Typhoon Dan （1999） over the western North Pacific were designed to compare the performances of two kinds of variational data assimilation schemes that are the 3-Dimensional Variational data assimilation of Mapped observation （3DVM） and the 4-dimensional variational data assimilation （4DVar）. Results show that： （1） both the 3DVM and 4DVar successfully improved the simulations of typhoon intensity and track incorporating the satellite AMSU-A retrieved temperature and wind data into the initial conditions, and the 3DVM more significantly due to the flow-dependent of background error covariance matrix and observation error covariance matrix like 3- dimensional variational data assimilation （3DVar） circle; （2） inclusions of extra model integration iterations at each observation time in the 3DVM make it more consistent with prediction model; （3） the 3DVM is much more time-saving due to the exclusion of the adjoint technique in it.

The evolution of hollow symmetric-PV tower during the landfall of Typhoon Mujigae(2015)

The evolution of Typhoon Mujigae(2015)during the landfall period is determined using potential vorticity(PV)based on a high-resolution numerical simulation.Diabatic heating from deep moist convections in the eyewall produces a hollow PV tower extending from the lower troposphere to the middle levels.Since the potential temperature and wind fields could be highly asymmetric during landfall,the fields are divided into symmetric and asymmetric components.Thus,PV is split into three parts:symmetric PV,first-order asymmetric PV,and quadratic-order asymmetric PV.By calculating the azimuth mean,the first-order term disappears.The symmetric PV is at least one order of magnitude larger than the azimuthal mean quadratic-order term,nearly accounting for the mean cyclone.Furthermore,the symmetric PV tendency equation is derived in cylindrical coordinates.The budget terms include the symmetric heating term,flux divergence of symmetric PV advection due to symmetric flow,flux divergence of partial first-order PV advection due to asymmetric flow,and the conversion term between the symmetric PV and quadratic-order asymmetric term.The diagnostic results indicate that the symmetric heating term is responsible for the hollow PV tower generation and maintenance.The symmetric flux divergence largely offsets the symmetric heating contribution,resulting in a horizontal narrow ring and vertical extension structure.The conversion term contribution is comparable to the mean term contributions,while the contribution of the partial first-order PV asymmetric flux divergence is apparently smaller.The conversion term implicitly contains the combined effects of processes that result in asymmetric structures.This term tends to counteract the contribution of symmetric terms before landfall and favor horizontal PV mixing after landfall.

The T-TREC Technique for Retrieving the Winds of Landfalling Typhoons in China

In this study, an extension of the TREC （Tracking Radar Echo by Correlations） technique, named Tropical Cyclone （TC） circulation TREC （T-TREC）, is developed to retrieve the winds of landfalling typhoons in China. The T-TREC analysis is performed on a polar grid centered at the TC center, using arc-shaped correlation cells and an arc-shaped search area. The search for the best correlation match is confined along the cyclonic direction with a limited search distance in the radial direction based on the cyclonic circulation characteristics of TCs in the Northern Hemisphere. The TC center is determined objectively using reflectivity data while the Doppler radar radial velocities are incorporated to estimate the search range and create a velocity correlation matrix as auxiliary constraints. The T-TREC was applied to the landfalling Typhoon Saomai （0608） observed by Chinese next generation Weather Surveillance Radar 1998 Doppler （CINRAD WSR-98D） on the southeast coast of China. The results show that the T-TREC has the ability to estimate the typhoon circulation with an average bias of 4 m s -1 . The incorporation of radial velocity data could distinctively improve wind retrievals for intense typhoons, especially by reducing the underestimation caused by fairly uniform reflectivity patterns in the vicinity of the eyewall and the outer rainband. A quantitative evaluation of the influence of typhoon center and cell size on the wind estimation demonstrates that the quality of the T-TREC retrieved wind circulation depends on the estimation of the typhoon center. A 4-km deviation of the TC center may result in a 10% increase in the retrieved wind error. The effect of cell size depends on the typhoon scale： better wind retrieval results can be obtained for a smaller typhoon.

Cloud type identification for a landfalling typhoon based on millimeter-wave radar range-height-indicator data

As a basic property of cloud,accurate identification of cloud type is useful in forecasting the evolution of landfalling typhoons.Millimeter-wave cloud radar is an important means of identifying cloud type.Here,we develop a fuzzy logic algorithm that depends on radar range-height-indicator(RHI)data and takes into account the fundamental physical features of different cloud types.The algorithm is applied to a ground-based Ka-band millimeter-wave cloud radar.The input parameters of the algorithm include average reflectivity factor intensity,ellipse long axis orientation,cloud base height,cloud thickness,presence/absence of precipitation,ratio of horizontal extent to vertical extent,maximum echo intensity,and standard variance of intensities.The identified cloud types are stratus(St),stratocumulus(Sc),cumulus(Cu),cumulonimbus(Cb),nimbostratus(Ns),altostratus(As),altocumulus(Ac)and high cloud.The cloud types identified using the algorithm are in good agreement with those identified by a human observer.As a case study,the algorithm was applied to typhoon Khanun(1720),which made landfall in south-eastern China in October 2017.Sequential identification results from the algorithm clearly reflected changes in cloud type and provided indicative information for forecasting of the typhoon.

Application of the frequency-matching method in the probability forecast of landfalling typhoon rainfall

In this paper,a revised method for typhoon precipitation probability forecast,based on the frequencymatching method,is developed by combining the screening and the neighborhood methods.The frequency of the high-resolution precipitation forecasts is used as the reference frequency,and the frequency of the lowresolution ensemble forecasts is used as the forecast frequency.Based on frequency–matching method,the frequency of rainfall above the rainstorm magnitude increases.The forecast members are then selected by using the typhoon tracks of the short-term predictions,and the precipitation probability is calculated for each member using a combination of the neighbor and the traditional probability statistical methods.Moreover,four landfalling typhoons(i.e.,STY Lekima and STS Bailu in 2019,and TY Hagupit and Higos in 2020)were chose to test the rainfall probability forecast.The results show that the method performs well with respect to the forecast rainfall area and magnitude for the four typhoons.The Brier and Brier skill scores are almost entirely positive for the probability forecast of 0.1–250 mm rainfall during Bailu,Hagupit and Higos(except for 0.1mm of Hagupit),and for<100 mm rainfall(except for 25 mm)during Lekima.

Identification of synoptic patterns for extreme rainfall events associated with landfalling typhoons in China during 1960–2020

Extreme rainfall associated with landfalling typhoon(ERLTC)can cause severe disasters and economic impacts throughout China.Improving the accuracy of ERLTC forecasts is therefore crucial in disaster prevention and mitigation.The top 26 ERLTC events in China during 1960–2020 are investigated based on multi-source datasets.These ERLTC events are categorized into five main types according to the geographical location of the extreme precipitation and its position relative to the tropical cyclone(TC)center,namely:the typhoon inner-core rainfall in Taiwan(TWIC),typhoon inverted trough rainfall in Taiwan(TWIT),weak typhoon rainfall in Hainan(HNWK),strong typhoon rainfall in Zhejiang(ZJST)and inland typhoon remnant rainfall(ILRM).All the ERLTC events occurred in the weakening stage of TC after reaching its lifetime maximum intensity in convective cloud(TBB≤−32℃)regions over complex local terrain.The translational speeds of 20 TCs(76.9%of the total)were smaller than the climatological average(20.6 km h^(−1))during the extreme precipitation events.The differences are as follows:the TWIC and TWIT types are featured with different season,track and water vapor channel although both occurred in Taiwan.The other three types are distinguished by spinning track and strong convective cloud for HNWK type,strong TC intensity and binary TC interactions for ZJST type;and stagnation and strong westerly trough activity for ILRM type,respectively.These results are expected to provide useful clues for an in-depth understanding of ERLTC events over China.

Numerical Study on Impact of the Boundary Layer Fluxes over Wetland on Sustention and Rainfall of Landfalling Tropical Cyclones

Numerical studies have been carried out to investigate the sustention and intensification of Typhoon Nina （7503）, and the impacts of saturated wetland on the sustention and rainfall of tropical cyclone （TC） over land through sensitivity experiments, using the PSU/NCAR non-hydrostatic mesoscale model MM5v3 and its TC bogus scheme. The results show that the vertical transfer of fluxes in the boundary layer over saturated wetland has significant influence on the intensity, structure, and rainfall of a landfalling TC. The latent heating flux and the sensible heating flux are both favourable for TC sustaining and intensification on which the latent heating transfer is more favourable than the sensible heating transfer. They are also favourable for the maintenance of the spiral structure, and have an evident effect on the distribution of TC rainfall. The momentum flux weakens the TC vortex wind fields significantly, and is the dominant factor to dissipate and fill in a low pressure system, while it increases the local precipitation induced by a typhoon.