APPLICATION OF BDA SCHEME IN TYPHOON TRACK PREDICTION

The MM5, which is the PSU/NCAR mesoscale nonhydrostatic limited-area ,nodel, and its adjoining modeling system are used in this paper. Taking T106 analysis data as background field the authors generate an optimal initial condition of a typhoon by using two bogus data assimilation schemes, and conduct some numerical simulating experiments. The results ofno.9608 typhoon （Gloria） show that the optimal initial tield have some dramatic improvements, such as inaccurate position of typhoon center, weaker typhoon circulation and incomplete inner structure of the typhoon, which are caused by shortage of data over the sea. Some improvements have been made in the track forecast. Through several comparing experiments, the initialization optimized by BDA scheme is found to be more reasonable than GFDL scheme and its typhoon track forrecast is better.

Prediction of Typhoon Tracks Using Dynamic Linear Models

This paper presents a study on the statistical forecasts of typhoon tracks. Numerical models have their own systematic errors, like a bias. In order to improve the accuracy of track forecasting, a statistical model called DLM (dynamic linear model) is applied to remove the systematic error. In the analysis of typhoons occurring over the western North Pacific in 1997 and 2000, DLM is useful as an adaptive model for the prediction of typhoon tracks.

ANALYSIS OF RAINSTORMS ASSOCIATED WITH SIMILAR TRACK TROPICAL CYCLONES HAITANG (0505) AND BILIS (0604)

It is generally thought that the influence of comparable track typhoons is approximately similar, but in fact their wind and especially their rainstorm distribution are often very different. Therefore, a contrastive analysis of rainstorms by tropical cyclones (TCs) Haitang (0505) and Bilis (0604), which are of a similar track, is designed to help understand the mechanism of the TC rainstorm and to improve forecasting skills. The daily rainfall of TC Haitang (0505) and Bilis (0604) is diagnosed and compared. The result indicates that these two TCs have similar precipitation distribution before landfall but different precipitation characteristics after landfall. Using NCEP/GFS analysis data, the synoptic situation is analyzed; water vapor transportation is discussed regarding the calculated water vapor flux and divergence. The results show that the heavy rainfall in the Zhejiang and Fujian Provinces associated with Haitang (0505) and Bilis (0604) before landfall results from a peripheral easterly wind, a combination of the tropical cyclone and the terrain. After landfall and moving far inland of the storm, the precipitation of Haitang is caused by water vapor convergence carried by its own circulation; it is much weaker than that in the coastal area. One of the important contributing factors to heavy rainstorms in southeast Zhejiang is a southeast jet stream, which is maintained over the southeast coast. In contrast, the South China Sea monsoon circulation transports large amounts of water vapor into Bilis – when a water-vapor transport belt south of the tropical cyclone significantly strengthens – which strengthens the transport. Then, it causes water vapor flux to converge on the south side of Bilis and diverge on the north side. Precipitation is much stronger on the south side than that on the north side. After Bilis travels far inland, the cold air guided by a north trough travels into the TC and remarkably enhances precipitation. In summary, combining vertical wind shear with water vapor transportation is a good way to predict rainstorms associated with landing tropical cyclones.

Possible Sources of Forecast Errors Generated by the Global/Regional Assimilation and Prediction System for Landfalling Tropical Cyclones.PartⅠ:Initial Uncertainties

This paper investigates the possible sources of errors associated with tropical cyclone （TC） tracks forecasted using the Global/Regional Assimilation and Prediction System （GRAPES）. The GRAPES forecasts were made for 16 landfaIling TCs in the western North Pacific basin during the 2008 and 2009 seasons, with a forecast length of 72 hours, and using the default initial conditions （＂initials＂, hereafter）, which are from the NCEP-FNL dataset, as well as ECMWF initials. The forecasts are compared with ECMWF forecasts. The results show that in most TCs, the GRAPES forecasts are improved when using the ECMWF initials compared with the default initials. Compared with the ECMWF initials, the default initials produce lower intensity TCs and a lower intensity subtropical high, but a higher intensity South Asia high and monsoon trough, as well as a higher temperature but lower specific humidity at the TC center. Replacement of the geopotential height and wind fields with the ECMWF initials in and around the TC center at the initial time was found to be the most efficient way to improve the forecasts. In addition, TCs that showed the greatest improvement in forecast accuracy usually had the largest initial uncertainties in TC intensity and were usually in the intensifying phase. The results demonstrate the importance of the initial intensity for TC track forecasts made using GRAPES, and indicate the model is better in describing the intensifying phase than the decaying phase of TCs. Finally, the limit of the improvement indicates that the model error associated with GRAPES forecasts may be the main cause of poor forecasts of landfalling TCs. Thus, further examinations of the model errors are required.

The Impact of Dropsonde Data on Forecasts of Hurricane Debby by the Meteorological Office Unified Model

The numerical product of hurricane tracks vastly depends on initial observation fields. However, the forecast error is very large because of lack of observational data, especially when hurricanes are over the sea. This paper shows that extra non-real-time data (dropsonde data) can improve hurricane track forecasts compared with real-time observational data, and that the wind and relative humidity components of the dropsonde data have the greatest impact on the track forecasts.

Impacts of a Large-scale Adaptive Blending Scheme for CMA-MESO on Regional Forecasts-A Case Study of Typhoon Haima

Large-scale atmospheric information plays an important role in the regional model for the forecasts of weather such as tropical cyclone(TC).However,it is difficult to be fully represented in regional models due to domain size and a lack of observation data,particularly at sea used in regional data assimilation.Blending analysis has been developed and implemented in regional models to reintroduce large-scale information from global model to regional analysis.Research of the impact of this large-scale blending scheme for the Global/Regional Assimilation and PrEdiction System(CMA-MESO)regional model on TC forecasting is limited and this study attempts to further progress by examining the adaptivity of the blending scheme using the two-dimensional Discrete Cosine Transform(2D-DCT)filter on the model forecast of Typhoon Haima over Shenzhen,China in 2016 and considering various cut-off wavelengths.Results showed that the error of the 24-hour typhoon track forecast can be reduced to less than 25 km by applying the scale-dependent blending scheme,indicating that the blending analysis is effectively able to minimise the large-scale bias for the initial fields.The improvement of the wind forecast is more evident for u-wind component according to the reduced root mean square errors(RMSEs)by comparing the experiments with and without blending analysis.Furthermore,the higher equitable threat score(ETS)provided implications that the precipitation prediction skills were increased in the 24h forecast by improving the representation of the large-scale feature in the CMA-MESO analysis.Furthermore,significant differences of the track error forecast were found by applying the blending analysis with different cut-off wavelengths from 400 km to 1200 km and the track error can be reduced less than by 10 km with 400 km cut-off wavelength in the first 6h forecast.It highlighted that the blending scheme with dynamic cut-off wavelengths adapted to the development of different TC systems is necessary in order to optimally introduce and ingest the large-scale information from global model to the regional model for improving the TC forecast.In this paper,the methods and data applied in this study will be firstly introduced,before discussion of the results regarding the performance of the blending analysis and its impacts on the wind and precipitation forecast correspondingly,followed by the discussion of the effects of different blending scheme on TC forecasts and the conclusion section.

Effects of a Dry-Mass Conserving Dynamical Core on the Simulation of Tropical Cyclones

The accurate forecasting of tropical cyclones(TCs)is a challenging task.The purpose of this study was to investigate the effects of a dry-mass conserving(DMC)hydrostatic global spectral dynamical core on TC simulation.Experiments were conducted with DMC and total(moist)mass conserving(TMC)dynamical cores.The TC forecast performance was first evaluated considering 20 TCs in the West Pacific region observed during the 2020 typhoon season.The impacts of the DMC dynamical core on forecasts of individual TCs were then estimated.The DMC dynamical core improved both the track and intensity forecasts,and the TC intensity forecast improvement was much greater than the TC track forecast improvement.Sensitivity simulations indicated that the DMC dynamical core-simulated TC intensity was stronger regardless of the forecast lead time.In the DMC dynamical core experiments,three-dimensional winds and warm and moist cores were consistently enhanced with the TC intensity.Drier air in the boundary inflow layer was found in the DMC dynamical core experiments at the early simulation times.Water vapor mixing ratio budget analysis indicated that this mainly depended on the simulated vertical velocity.Higher updraft above the boundary layer yielded a drier boundary layer,resulting in surface latent heat flux(SLHF)enhancement,the major energy source of TC intensification.The higher DMC dynamical core-simulated updraft in the inner core caused a higher net surface rain rate,producing higher net internal atmospheric diabatic heating and increasing the TC intensity.These results indicate that the stronger DMC dynamical coresimulated TCs are mainly related to the higher DMC vertical velocity.

SEA SURFACE TEMPERATURE RESPONSE TO TYPHOON MORAKOT(2009) AND ITS INFLUENCE

While previous studies indicate that typhoons can decrease sea surface temperature(SST) along their tracks, a few studies suggest that the cooling patterns in coastal areas are different from those in the open sea. However, little is known about how the induced cooling coupled with the complex ocean circulation in the coastal areas can affect tropical cyclone track and intensity. The sea surface responses to the land falling process of Typhoon Morakot(2009) are examined observationally and its influences on the activity of the typhoon are numerically simulated with the WRF model. The present study shows that the maximum SST cooling associated with Morakot occurred on the left-hand side of the typhoon track during its landfall. Numerical simulations show that, together with the SST gradients associated with the coastal upwelling and mesoscale oceanic vortices, the resulting SST cooling can cause significant difference in the typhoon track, comparable to the current 24-hour track forecasting error. It is strongly suggested that it is essential to include the non-uniform SST distribution in the coastal areas for further improvement in typhoon track forecast.

A Bogus Typhoon Scheme and Its Application to a Movable Nested Mesh Model

A bogus typhoon scheme,designed for the initialization of a typhoon track prediction model,is developed in thispaper.This scheme includes both effects of axisymmetric wind and asymmetric wind.Experimental forecasts using atwo-way interactive movable nested mesh model show that the forecast skill of typhoon tracks has clearly improvedafter introducing the bogus typhoon into the initial fields.

Forecasting of tropical cyclones ASANI(2022)and MOCHA(2023)over the Bay of Bengal-real time challenges to forecasters

This study examines the track and intensity forecasts of two typical Bay of Bengal tropical cyclones(TC)ASANI and MOCHA.The analysis of various Numerical Weather Prediction(NWP)model forecasts[ECMWF(European Centre for Medium range Weather Forecast),NCEP(National Centers for Environmental Prediction),NCUM(National Centre for Medium Range Weather Forecast-Unified Model),IMD(India Meteorological Department),HWRF(Hurricane Weather Research and Forecasting)],MME(Multi-model Ensemble),SCIP(Statistical Cyclone Intensity Prediction)model,and OFCL(Official)forecasts shows that intensity forecasts of ASANI and track forecasts of MOCHA were reasonably good,but there were large errors and wide variation in track forecasts of ASANI and in intensity forecasts of MOCHA.Among all model forecasts,the track forecast errors of IMD model and MME were least in general for ASANI and MOCHA respectively.Also,the landfall point forecast errors of IMD were least for ASANI,and the MME and OFCL forecast errors were least for MOCHA.No model is found to be consistently better for landfall time forecast for ASANI,and the errors of ECMWF,IMD and HWRF were least and of same order for MOCHA.The intensity forecast errors of OFCL and SCIP were least for ASANI,and the forecast errors of HWRF,IMD,NCEP,SCIP and OFCL were comparable and least for MOCHA up to 48 h forecast and HWRF errors were least thereafter in general.The ECMWF model forecast errors for intensity were found to be highest for both the TCs.The results also show that although there is significant improvement of track forecasts and limited or no improvement of intensity forecast in previous decades but challenges still persists in real time forecasting of both track and intensity due to wide variation and inconsistency of model forecasts for different TC cases.

Track forecast:Operational capability and new techniques-Summary from the Tenth International Workshop on Tropical Cyclones(IWTC-10)

In this paper,we summarize findings from the Tenth International Workshop on Tropical Cyclones(IWTC-10)subgroup on operational track forecasting techniques and capability.The rate of improvement in the accuracy of official forecast tracks(OFTs)appears to be slowing down,at least for shorter lead times,where we may be approaching theoretical limits.Operational agencies continue to use consensus methods to produce the OFT with most continuing to rely on an unweighted consensus of four to nine NWP models.There continues to be limited use of weighted consensus techniques,which is likely a result of the skills and additional maintenance needed to support this approach.Improvements in the accuracy of ensemble mean tracks is leading to increased use of ensemble means in consensus tracks.Operational agencies are increasingly producing situation-dependent depictions of track uncertainty,rather than relying on a static depiction of track forecast certainty based on accuracy statistics from the preceding 5 years.This trend has been facilitated by the greater availability of ensemble NWP guidance,particularly vortex parameter files,and improved spread in ensembles.Despite improving spread-skill relationships,most ensemble NWP systems remain under spread.Hence many operational centers are looking to leverage“super-ensembles”(ensembles of ensembles)to ensure the full spread of location probability is captured.This is an important area of service development for multi-hazard impact-based warnings as it supports better decision making by emergency managers and the community in the face of uncertainty.©2023 The Shanghai Typhoon Institute of China Meteorological Administration.Publishing services by Elsevier B.V.on behalf of KeAi Communication Co.Ltd.This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

Impact of assimilating Taiwan＇s coastal radar radial velocity on forecasting Typhoon Morakot (2009) in southeastern China using a WRF-based EnKF

This study explores for the first time the impact of assimilating radial velocity(Vr)observations from a single or multiple Taiwan's coastal radars on tropical cyclone(TC)forecasting after landfall in the Chinese mainland by using a Weather Research and Forecasting model(WRF)-based ensemble Kalman filter(EnKF)data assimilation system.Typhoon Morakot(2009),which caused widespread damage in the southeastern coastal regions of the mainland after devastating Taiwan,was chosen as a case study.The results showed that assimilating Taiwan's radar Vr data improved environmental field and steering flow and produced a more realistic TC position and structure in the final EnKF cycling analysis.Thus,the subsequent TC track and rainfall forecasts in southeastern China were improved.In addition,better observations of the TC inner core by Taiwan's radar was a primary factor in improving TC rainfall forecast in the Chinese mainland.

Analysis of characteristics and evaluation of forecast accuracy for Super Typhoon Doksuri(2023)

Super Typhoon Doksuri is a significant meteorological challenge for China this year due to its strong intensity and wide influence range,as well as significant and prolonged hazards.In this work,we studied Doksuri's main characteristics and assessed its forecast accuracy meticulously based on official forecasts,global models and regional models with lead times varying from 1 to 5 days.The results indicate that Typhoon Doksuri underwent rapid intensification and made landfall at 09:55 BJT on July 28 with a powerful intensity of 50 m s−1 confirmed by the real-time operational warnings issued by China Meteorological Administration(CMA).The typhoon also caused significant wind and rainfall impacts,with precipitation at several stations reaching historical extremes,ranking eighth in terms of total rainfall impact during the event.The evaluation of forecast accuracy for Doksuri suggests that Shanghai Multi-model Ensemble Method(SSTC)and Fengwu Model are the most effective for short-term track forecasts.Meanwhile,the forecasts from the European Centre for Medium-Range Weather Forecasts(ECMWF)and United Kingdom Meteorological Office(UKMO)are optimal for long-term predictions.It is worth noting that objective forecasts systematically underestimate the typhoon maximum intensity.The objective forecast is terribly poor when there is a sudden change in intensity.CMA-National Digital Forecast System(CMA-NDFS)provides a better reference value for typhoon accumulated rainfall forecasts,and regional models perform well in forecasting extreme rainfall.The analyses above assist forecasters in pinpointing challenges within typhoon predictions and gaining a comprehensive insight into the performance of each model.This improves the effective application of model products.

Unusual tracks:Statistical,controlling factors and model prediction

The progress of research and forecast techniques for tropical cyclone(TC)unusual tracks(UTs)in recent years is reviewed.A major research focus has been understanding which processes contribute to the evolution of the TC and steering flow over time,especially the reasons for the sharp changes in TC motion over a short period of time.When TCs are located in the vicinity of monsoon gyres,TC track forecast become more difficult to forecast due to the complex interaction between the TCs and the gyres.Moreover,the convection and latent heat can also feed back into the synoptic-scale features and in turn modify the steering flow.In this report,two cases with UTs are examined,along with an assessment of numerical model forecasts.Advances in numerical modelling and in particular the development of ensemble forecasting systems have proved beneficial in the prediction of such TCs.There are still great challenges in operational track forecasts and warnings,such as the initial TC track forecast,which is based on a poor pre-genesis analysis,TC track forecasts during interaction between two or more TCs and track predictions after landfall.Recently,artificial intelligence(AI)methods such as machine learning or deep learning have been widely applied in the field of TC forecasting.For TC track forecasting,a more effective method of center location is obtained by combining data from various sources and fully exploring the potential of AI,which provides more possibilities for improving TC prediction.

INFLUENCE OF THE VERTICAL SHEAR OF ENVIRONMENTAL FLOWS ON TYPHOON MOTION

Typhoon is regarded as a convergent,modified Rankine vortex.Based on the vorticity equations written at two levels,higher and lower in the troposphere,typhoon motions are discussed in this study.The analytical expressions of vortex motion direction and speed have been derived for simple homogeneous basic flows at two levels.The expressions indicate that in the easterties,vertical wind shear enhances the steering of east flow, causing the vortex moving westward faster,otherwise,in the westerlies,it reduces the steering of the west flow, causing the vortex moving eastward slower.These results explain theoretically that“cyclones in the easterlies move to the right of,and faster than the basic flow;conversely,cyclones in the westerlies move to the left of,and slower than the basic flow.” With derived baroclinic diagnostic equations and a barotropical model,ten cases from 1980 to 1983 have been calculated for 24h typhoon motions.The results show that the baroclinic models are better than the baro- tropic ones.Therefore,the vertical wind shear is one of the important factors affecting typhoon movement.

Improvement of displacement error of rainfall and wind field forecast associated with landfalling tropical cyclone AMPHAN

Spatial distribution of rainfall and wind speed forecast errors associated with landfalling tropical cyclones(TC)occur significantly due to incorrect location forecast by numerical models.Two major areas of errors are:(i)over-estimation over the model forecast locations and(ii)underestimation over the observed locations of the TCs.A modification method is proposed for real-time improvement of rainfall and wind field forecasts and demonstrated for the typical TC AMPHAN over the Bay of Bengal in 2020.The proposed method to improve the model forecasts is a relocation method through shifting of model forecast locations of TC to the real-time official forecast locations of India Meteorological Department(IMD).The modification is applied to the forecasts obtained from the operational numerical model,the Global Forecast System(GFS)of IMD.Application of the proposed method shows considerable improvement of both the parameters over both the locations.The rainfall forecast errors due to displacement are found to have improved by 44.1%–69.8%and 72.1%–85.2%over the GFS forecast locations and over the observed locations respectively for the respective forecast lead times 48 h,72 h,and 96 h.Similarly,the wind speed forecasts have improved by 27.6%–56.0%and 63.7%–84.6%over the GFS forecast locations and over the observed locations respectively for the respective forecast lead times 60 h,72 h,and 84 h.The results show that the proposed technique has capacity to provide improved spatial distributions of rainfall and wind speed forecasts associated with landfalling TCs and useful guidance to operational forecasters.

THE IMPACT OF TROPICAL CYCLONES ON CHINA IN 2016

In 2016, the Northwest Pacific and the South China Sea registered the genesis of 26 tropical cyclones. 8 of them, including NEPARTAK(1601), MIRINAE(1603), NIDA(1604), DIANMU(1608), MERANTI(1614),MEGI(1617), SARIKA(1621) and HAIMA(1622), made landfall over China's coastal areas. The number one TC of 2016, NEPARTAK, was named on July 3. Although no typhoon generated in the first half of this year,which means 4.6 incidences less compared with the same period of a normal year, more tropical cyclones made landfall over China(the historical average in the same period of 1949-2015 is 6.7). And these 8 tropical cyclones had an averaged intensity up to 40.6 m/s, significantly enhanced compared with the multi-year average of 32.8 m/s.The death toll from the 11 tropical cyclones affected China in 2016 is 206. MERANTI was the most destructive one in 2016, which brought up the largest numbers of affected and evacuated population, damaged houses and direct economic losses. In 2016, China Meteorological Administration(CMA) 24-120 h mean official track forecast errors were 66, 127, 213, 292 and 364 km, respectively. The 24 h track forecast error has been kept within 70 km in two consecutive years.

Binary interaction of typhoons Soulik and Cimaron in 2018—Part Ⅰ:Observational characteristics and forecast error

To understand structural changes and forecast error,a case study of binary typhoons in the western North Pacific(WNP)of 2018 was investigated using best track and reanalysis data.Soulik was generated on August 16 and Cimaron was generated on August 18,respectively.The 19 th typhoon Soulik and 20 th typhoon Cimaron co-existed from August 18 to 24 and approached each other.Soulik was located on the western side and Cimaron was located on the eastern side of the WNP.They were located approximately 1300 km from each other at 00 UTC August 22.The Soulik structure began changing around August 22 and became weak and slow,while Cimaron maintained its intensity,size,and moving speed.This observational evidence is likely caused by the binary interaction between two typhoons within a certain distance and environmental steering flow,such as the location of the North Pacific high and strong jet stream of the northern flank of the North Pacific high.Soulik was initially forecasted to make landfall and reach Seoul;however,its track changed from northward to northeastward from August 21 to 23 according to both official guidance and unified model(UM).Four global numerical weather prediction models forecasted different tracks of Soulik.UM and JGSM forecasted a northward track whereas ECMWF and GFS showed a northeastward track for 12 UTC August 21 through 12 UTC August 24.The latter models were similar to the best track.The track forecast error and spread of Soulik were larger than those of Cimaron.The mean absolute error of the maximum wind speed of Soulik was similar to the average of total typhoons in 2018.