In order to investigate whether adaptive observations can improve tropical cyclone （TC） intensity forecasts,observing system simulation experiments （OSSEs） were conducted for 20 TC cases originating in the western...In order to investigate whether adaptive observations can improve tropical cyclone （TC） intensity forecasts,observing system simulation experiments （OSSEs） were conducted for 20 TC cases originating in the western North Pacific during the 2010 season according to the conditional nonlinear optimal perturbation （CNOP） sensitivity,using the fifth version of the PSU/NCAR mesoscale model （MM5） and its 3DVAR assimilation system.A new intensity index was defined as the sum of the number of grid points within an allocated square centered at the corresponding forecast TC central position,that satisfy constraints associated with the Sea Level Pressure （SLP）,near-surface horizontal wind speed,and accumulated convective precipitation.The higher the index value is,the more intense the TC is.The impacts of the CNOP sensitivity on the intensity forecast were then estimated.The OSSE results showed that for 15 of the 20 cases there were improvements,with reductions of forecast errors in the range of 0.12％-8.59％,which were much less than in track forecasts.The indication,therefore,is that the CNOP sensitivity has a generally positive effect on TC intensity forecasts,but only to a certain degree.We conclude that factors such as the use of a coupled model,or better initialization of the TC vortex,are more important for an accurate TC intensity forecast.展开更多
Valuable dropsonde data were obtained from multiple field campaigns targeting tropical cyclones,namely Higos,Nangka,Saudel,and Atsani,over the western North Pacific by the Hong Kong Observatory and Taiwan Central Weat...Valuable dropsonde data were obtained from multiple field campaigns targeting tropical cyclones,namely Higos,Nangka,Saudel,and Atsani,over the western North Pacific by the Hong Kong Observatory and Taiwan Central Weather Bureau in 2020.The conditional nonlinear optimal perturbation(CNOP)method has been utilized in real-time to identify the sensitive regions for targeting observations adhering to the procedure of real-time field campaigns for the first time.The observing system experiments were conducted to evaluate the effect of dropsonde data and CNOP sensitivity on TC forecasts in terms of track and intensity,using the Weather Research and Forecasting model.It is shown that the impact of assimilating all dropsonde data on both track and intensity forecasts is case-dependent.However,assimilation using only the dropsonde data inside the sensitive regions displays unanimously positive effects on both the track and intensity forecast,either of which obtains comparable benefits to or greatly reduces deterioration of the skill when assimilating all dropsonde data.Therefore,these results encourage us to further carry out targeting observations for the forecast of tropical cyclones according to CNOP sensitivity.展开更多
In this study,six intensity forecast guidance techniques from the East China Regional Meteorological Center are verified for the 2008 and 2009 typhoon seasons through an alternative forecast verification technique.Thi...In this study,six intensity forecast guidance techniques from the East China Regional Meteorological Center are verified for the 2008 and 2009 typhoon seasons through an alternative forecast verification technique.This technique is used to verify intensity forecasts if those forecasts call for a typhoon to dissipate or if the real typhoon dissipates.Using a contingency table,skill scores,chance,and probabilities are computed.It is shown that the skill of the six tropical cyclone intensity guidance techniques was highest for the 12-h forecasts,while the lowest skill of all the six models did not occur in 72-h forecasting.For both the 2008 and 2009 seasons,the average probabilities of the forecast intensity having a small error(6 m s-1) tended to decrease steadily.Some of the intensity forecasts had small skill scores,but the associated probabilities of the forecast intensity errors > 15 m s-1 were not the highest.展开更多
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...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.展开更多
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 fo...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.展开更多
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'...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.展开更多
This review summarizes the rapporteur report on tropical cyclone(TC)intensity change from the operational perspective,as presented to the 10th International Workshop on TCs(IWTC-10)held in Bali,Indonesia,from Dec.5–9...This review summarizes the rapporteur report on tropical cyclone(TC)intensity change from the operational perspective,as presented to the 10th International Workshop on TCs(IWTC-10)held in Bali,Indonesia,from Dec.5–9,2022.The accuracy of TC intensity forecasts issued by operational forecast centers depends on three aspects:real-time observations,TC dynamical model forecast guidance,and techniques and methods used by forecasters.The rapporteur report covers the progress made over the past four years(2018–2021)in all three aspects.This review focuses on the progress of dynamical model forecast guidance.The companion paper(Part II)summarizes the advance from operational centers.The dynamical model forecast guidance continues to be the main factor leading to the improvement of operational TC intensity forecasts.Here,we describe recent advances and developments of major operational regional dynamical TC models and their intensity forecast performance,including HWRF,HMON,COAMPS-TC,Met Office Regional Model,CMA-TYM,and newly developed HAFS.The performance of global dynamical models,including NOAA's GFS,Met Office Global Model(MOGM),JMA's GSM,and IFS(ECMWF),has also been improved in recent years due to their increased horizontal and vertical resolution as well as improved data assimilation systems.Recent challenging cases of rapid intensification are presented and discussed.展开更多
Variations in the initial structure of tropical cyclones(TCs) inevitably affect prediction results;however, the bogus model cannot accurately describe the structure of a weak tropical cyclone with increased initial fi...Variations in the initial structure of tropical cyclones(TCs) inevitably affect prediction results;however, the bogus model cannot accurately describe the structure of a weak tropical cyclone with increased initial field resolution. This study aims to construct a model to improve the prediction of weak TC in southern China. Based on the ECMWF 0.1° analysis data, several vortices were filtered out from tropical depressions and tropical storms in 2018 and 2019 to represent a weak TC reservoir in the South China Sea. For different simulation objects, filtered vortices were combined with the TC environmental field to form ensemble members. The observed TC information was assimilated for simulating TCs Bebinca, Mun, and Ewiniar to verify the feasibility of the proposed model, based on the Global/Regional Assimilation and Prediction Enhanced System(GRAPES) 9-km model developed by the Guangzhou Institute of Tropical and Marine Meteorology. The results show that the initialization scheme of the weak tropical cyclone model improved the intensity prediction of the TC by 26.81%(Bebinca), 18.65%(Mun), and 47.00%(Ewiniar), compared with the control experiment. Because typhoon intensity forecasting has not notably improved for many years, this scheme has certain scientific and operational significance.展开更多
基金sponsored by the National Natural Science Foundation of China (Grant No. 41105040)
文摘In order to investigate whether adaptive observations can improve tropical cyclone （TC） intensity forecasts,observing system simulation experiments （OSSEs） were conducted for 20 TC cases originating in the western North Pacific during the 2010 season according to the conditional nonlinear optimal perturbation （CNOP） sensitivity,using the fifth version of the PSU/NCAR mesoscale model （MM5） and its 3DVAR assimilation system.A new intensity index was defined as the sum of the number of grid points within an allocated square centered at the corresponding forecast TC central position,that satisfy constraints associated with the Sea Level Pressure （SLP）,near-surface horizontal wind speed,and accumulated convective precipitation.The higher the index value is,the more intense the TC is.The impacts of the CNOP sensitivity on the intensity forecast were then estimated.The OSSE results showed that for 15 of the 20 cases there were improvements,with reductions of forecast errors in the range of 0.12％-8.59％,which were much less than in track forecasts.The indication,therefore,is that the CNOP sensitivity has a generally positive effect on TC intensity forecasts,but only to a certain degree.We conclude that factors such as the use of a coupled model,or better initialization of the TC vortex,are more important for an accurate TC intensity forecast.
基金jointly sponsored by the National Nature Scientific Foundation of China(Grant.Nos.41930971 and 41775061)the National Key Research and Development Program of China(Grant No.2018YFC1506402)。
文摘Valuable dropsonde data were obtained from multiple field campaigns targeting tropical cyclones,namely Higos,Nangka,Saudel,and Atsani,over the western North Pacific by the Hong Kong Observatory and Taiwan Central Weather Bureau in 2020.The conditional nonlinear optimal perturbation(CNOP)method has been utilized in real-time to identify the sensitive regions for targeting observations adhering to the procedure of real-time field campaigns for the first time.The observing system experiments were conducted to evaluate the effect of dropsonde data and CNOP sensitivity on TC forecasts in terms of track and intensity,using the Weather Research and Forecasting model.It is shown that the impact of assimilating all dropsonde data on both track and intensity forecasts is case-dependent.However,assimilation using only the dropsonde data inside the sensitive regions displays unanimously positive effects on both the track and intensity forecast,either of which obtains comparable benefits to or greatly reduces deterioration of the skill when assimilating all dropsonde data.Therefore,these results encourage us to further carry out targeting observations for the forecast of tropical cyclones according to CNOP sensitivity.
基金supported by the National Basic Research Program of China (2009CB421505)the Shanghai Typhoon Foundation (2009ST09)+1 种基金the National Natural Science Foundation of China (40775060)the Program of China Mete-orological Administration (GYHY201006008 and GYHY200906002)
文摘In this study,six intensity forecast guidance techniques from the East China Regional Meteorological Center are verified for the 2008 and 2009 typhoon seasons through an alternative forecast verification technique.This technique is used to verify intensity forecasts if those forecasts call for a typhoon to dissipate or if the real typhoon dissipates.Using a contingency table,skill scores,chance,and probabilities are computed.It is shown that the skill of the six tropical cyclone intensity guidance techniques was highest for the 12-h forecasts,while the lowest skill of all the six models did not occur in 72-h forecasting.For both the 2008 and 2009 seasons,the average probabilities of the forecast intensity having a small error(6 m s-1) tended to decrease steadily.Some of the intensity forecasts had small skill scores,but the associated probabilities of the forecast intensity errors > 15 m s-1 were not the highest.
基金jointly supported by the National Key Research and Development Program of China (2021YFC3101500)the National Natural Science Foundation of China (Grant Nos. 41830964, 42275062)
文摘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.
文摘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.
基金supported jointly by Innovation and Development Special Program of China Meteorological Administration (Grant Nos.CXFZ2024J006)National Natural Science Foundation of China (Grant Nos.42075056)+4 种基金Research Program from Science and Technology Committee of Shanghai (Grant Nos.23DZ204700,22ZR1476400)Shanghai Science and Technology Commission Project (Grant Nos.23DZ1204701)Ningbo Key R&D Program (Grant Nos.2023Z139)East China Regional Meteorological Science and Technology Collaborative Innovation Fund (Grant Nos.QYHZ202318)Special Fund Project of Basic Scientific Research Business Expenses of Shanghai Typhoon Institute, (Grant Nos.2024JB03).
文摘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.
文摘This review summarizes the rapporteur report on tropical cyclone(TC)intensity change from the operational perspective,as presented to the 10th International Workshop on TCs(IWTC-10)held in Bali,Indonesia,from Dec.5–9,2022.The accuracy of TC intensity forecasts issued by operational forecast centers depends on three aspects:real-time observations,TC dynamical model forecast guidance,and techniques and methods used by forecasters.The rapporteur report covers the progress made over the past four years(2018–2021)in all three aspects.This review focuses on the progress of dynamical model forecast guidance.The companion paper(Part II)summarizes the advance from operational centers.The dynamical model forecast guidance continues to be the main factor leading to the improvement of operational TC intensity forecasts.Here,we describe recent advances and developments of major operational regional dynamical TC models and their intensity forecast performance,including HWRF,HMON,COAMPS-TC,Met Office Regional Model,CMA-TYM,and newly developed HAFS.The performance of global dynamical models,including NOAA's GFS,Met Office Global Model(MOGM),JMA's GSM,and IFS(ECMWF),has also been improved in recent years due to their increased horizontal and vertical resolution as well as improved data assimilation systems.Recent challenging cases of rapid intensification are presented and discussed.
基金the National Key Research and Development Program of China (2018YFC1507602)Science and Technology Planning Project of Guangdong Province (2017B020244002 and 2018B020208004)+1 种基金Natural Science Foundation of Guangdong Province(2019A1515011118)National Natural Science Foundation of China (41705089)。
文摘Variations in the initial structure of tropical cyclones(TCs) inevitably affect prediction results;however, the bogus model cannot accurately describe the structure of a weak tropical cyclone with increased initial field resolution. This study aims to construct a model to improve the prediction of weak TC in southern China. Based on the ECMWF 0.1° analysis data, several vortices were filtered out from tropical depressions and tropical storms in 2018 and 2019 to represent a weak TC reservoir in the South China Sea. For different simulation objects, filtered vortices were combined with the TC environmental field to form ensemble members. The observed TC information was assimilated for simulating TCs Bebinca, Mun, and Ewiniar to verify the feasibility of the proposed model, based on the Global/Regional Assimilation and Prediction Enhanced System(GRAPES) 9-km model developed by the Guangzhou Institute of Tropical and Marine Meteorology. The results show that the initialization scheme of the weak tropical cyclone model improved the intensity prediction of the TC by 26.81%(Bebinca), 18.65%(Mun), and 47.00%(Ewiniar), compared with the control experiment. Because typhoon intensity forecasting has not notably improved for many years, this scheme has certain scientific and operational significance.
