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Impacts of lateral boundary conditions from numerical models and data-driven networks on convective-scale ensemble forecasts 认领 引用 被引量：4
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作者 Junjie Deng Jin Zhang +3 位作者 Haoyan Liu Hongqi Li Feng Chen Jing Chen 《Atmospheric and Oceanic Science Letters》 CSCD 2025年第2期78-85,共8页
The impacts of lateral boundary conditions(LBCs)provided by numerical models and data-driven networks on convective-scale ensemble forecasts are investigated in this study.Four experiments are conducted on the Hangzho... The impacts of lateral boundary conditions(LBCs)provided by numerical models and data-driven networks on convective-scale ensemble forecasts are investigated in this study.Four experiments are conducted on the Hangzhou RDP(19th Hangzhou Asian Games Research Development Project on Convective-scale Ensemble Prediction and Application)testbed,with the LBCs respectively sourced from National Centers for Environmental Prediction(NCEP)Global Forecast System(GFS)forecasts with 33 vertical levels(Exp_GFS),Pangu forecasts with 13 vertical levels(Exp_Pangu),Fuxi forecasts with 13 vertical levels(Exp_Fuxi),and NCEP GFS forecasts with the vertical levels reduced to 13(the same as those of Exp_Pangu and Exp_Fuxi)(Exp_GFSRDV).In general,Exp_Pangu performs comparably to Exp_GFS,while Exp_Fuxi shows slightly inferior performance compared to Exp_Pangu,possibly due to its less accurate large-scale predictions.Therefore,the ability of using data-driven networks to efficiently provide LBCs for convective-scale ensemble forecasts has been demonstrated.Moreover,Exp_GFSRDV has the worst convective-scale forecasts among the four experiments,which indicates the potential improvement of using data-driven networks for LBCs by increasing the vertical levels of the networks.However,the ensemble spread of the four experiments barely increases with lead time.Thus,each experiment has insufficient ensemble spread to present realistic forecast uncertainties,which will be investigated in a future study. 展开更多
关键词 Ensemble forecast Convective scale Lateral boundary conditions Data-driven network
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A New Method to Calculate Nonlinear Optimal Perturbations for Ensemble Forecasting 认领 引用 被引量：3
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作者 Junjie MA Wansuo DUAN +1 位作者 Zhuomin LIU Ye WANG 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2025年第5期952-967,共16页
Orthogonal conditional nonlinear optimal perturbations(O-CNOPs)have been used to generate ensemble forecasting members for achieving high forecasting skill of high-impact weather and climate events.However,highly effi... Orthogonal conditional nonlinear optimal perturbations(O-CNOPs)have been used to generate ensemble forecasting members for achieving high forecasting skill of high-impact weather and climate events.However,highly efficient calculations for O-CNOPs are still challenging in the field of ensemble forecasting.In this study,we combine a gradient-based iterative idea with the Gram‒Schmidt orthogonalization,and propose an iterative optimization method to compute O-CNOPs.This method is different from the original sequential optimization method,and allows parallel computations of O-CNOPs,thus saving a large amount of computational time.We evaluate this method by using the Lorenz-96 model on the basis of the ensemble forecasting ability achieved and on the time consumed for computing O-CNOPs.The results demonstrate that the parallel iterative method causes O-CNOPs to yield reliable ensemble members and to achieve ensemble forecasting skills similar to or even slightly higher than those produced by the sequential method.Moreover,the parallel method significantly reduces the computational time for O-CNOPs.Therefore,the parallel iterative method provides a highly effective and efficient approach for calculating O-CNOPs for ensemble forecasts.Expectedly,it can play an important role in the application of the O-CNOPs to realistic ensemble forecasts for high-impact weather and climate events. 展开更多
关键词 initial uncertainty conditional nonlinear optimal perturbation optimization method ensemble forecasting
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Evaluation of WRF-based Convection-Permitting Ensemble Forecasts for an Extreme Rainfall Event in East China during the Mei-yu Season 认领 引用
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作者 Chengyi ZHANG Mengwen WU Yali LUO 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2025年第10期2102-2124,共23页
This study focuses on an extreme rainfall event in East China during the mei-yu season,in which the capital city(Nanjing)of Jiangsu Province experienced a maximum 14-h rainfall accumulation of 209.6 mm and a peak hour... This study focuses on an extreme rainfall event in East China during the mei-yu season,in which the capital city(Nanjing)of Jiangsu Province experienced a maximum 14-h rainfall accumulation of 209.6 mm and a peak hourly rainfall of 118.8 mm.The performance of two sets of convection-permitting ensemble forecast systems(CEFSs),each with 30 members and a 3-km horizontal grid spacing,is evaluated.The CEFS_ICBCs,using multiple initial and boundary conditions(ICs and BCs),and the CEFS_ICBCs Phys,which incorporates both multi-physics schemes and ICs/BCs,are compared to the CMA-REPS(China Meteorological Administration-Regional Ensemble Prediction System)with a coarser 10-km grid spacing.The two CEFSs demonstrate more uniform rank histograms and lower Brier scores(with higher resolution),improving precipitation intensity predictions and providing more reliable probability forecasts,although they overestimate precipitation over Mt.Dabie.It is challenging for the CEFSs to capture the evolution of mesoscale rainstorms that are known to be related to the errors in predicting the southwesterly low-level winds.Sensitivity experiments reveal that the microphysics and radiation schemes introduce considerable uncertainty in predicting the intensity and location of heavy rainfall in and near Nanjing and Mt.Dabie.In particular,the Asymmetric Convection Model 2(ACM2)planetary boundary layer scheme combined with the Pleim-Xiu surface layer scheme tends to produce a biased northeastward extension of the boundary-layer jet,contributing to the northeastward bias of heavy precipitation around Nanjing in the CEFS_ICBCs. 展开更多
关键词 extreme rainfall mei-yu season convection-permitting ensemble forecasts forecast evaluation
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Bias-Corrected Short-Range Ensemble Forecasts for Near-Surface Variables during the Summer Season of 2010 in Northern China 认领 引用 被引量：2
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作者 ZHU Jiang-Shan KONG Fan-You LEI Heng-Chi 《Atmospheric and Oceanic Science Letters》 CSCD 2014年第4期334-339,共6页
A running mean bias （RMB） correction ap- proach was applied to the forecasts of near-surface variables in a seasonal short-range ensemble forecasting experiment with 57 consecutive cases during summer 2010 in the no... A running mean bias （RMB） correction ap- proach was applied to the forecasts of near-surface variables in a seasonal short-range ensemble forecasting experiment with 57 consecutive cases during summer 2010 in the northern China region. To determine a proper training window length for calculating RMB, window lengths from 2 to 20 days were evaluated, and 16 days was taken as an optimal window length, since it receives most of the benefit from extending the window length. The raw and 16-day RMB corrected ensembles were then evaluated for their ensemble mean forecast skills. The results show that the raw ensemble has obvious bias in all near-surface variables. The RMB correction can remove the bias reasonably well, and generate an unbiased ensemble. The bias correction not only reduces the ensemble mean forecast error, but also results in a better spreaderror relationship. Moreover, two methods for computing calibrated probabilistic forecast （PF） were also evaluated through the 57 case dates： 1） using the relative frequency from the RMB-eorrected ensemble; 2） computing the forecasting probabilities based on a historical rank histogram. The first method outperforms the second one, as it can improve both the reliability and the resolution of the PFs, while the second method only has a small effect on the reliability, indicating the necessity and importance of removing the systematic errors from the ensemble. 展开更多
关键词 short-range ensemble forecast bias-corrected ensemble forecast running mean bias correction near-surface variable forecast
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A Regional Ensemble Forecast System for Stratiform Precipitation Events in the Northern China Region.Part Ⅱ:Seasonal Evaluation for Summer 2010 认领 引用 被引量：8
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作者 朱江山 孔凡铀 雷恒池 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2013年第1期15-28,共14页
In this study, the Institute of Atmospheric Physics, Chinese Academy of Sciences - regional ensemble forecast system （IAP-REFS） described in Part I was further validated through a 65-day experiment using the summer ... In this study, the Institute of Atmospheric Physics, Chinese Academy of Sciences - regional ensemble forecast system （IAP-REFS） described in Part I was further validated through a 65-day experiment using the summer season of 2010. The verification results show that IAP-REFS is skillful for quantitative precipitation forecasts （QPF） and probabilistic QPF, but it has a systematic bias in forecasting near-surface variables. Applying a 7-day running mean bias correction to the forecasts of near-surface variables remarkably improved the reliability of the forecasts. In this study, the perturbation extraction and inflation method （proposed with the single case study in Part I） was further applied to the full season with different inflation factors. This method increased the ensemble spread and improved the accuracy of forecasts of precipitation and near-surface variables. The seasonal mean profiles of the IAP-REFS ensemble indicate good spread among ensemble members and some model biases at certain vertical levels. 展开更多
关键词 short-range ensemble forecast rain enhancement operation probabilistic forecast
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A STUDY ON THE ENSEMBLE FORECAST REAL-TIME CORRECTION METHOD 认领 引用 被引量：5
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作者 GUO Rong QI Liang-bo +1 位作者 GE Qian-qian WENG Yong-yuan 《Journal of Tropical Meteorology》 SCIE 2018年第1期42-48,共7页
Using real-time correction technology for typhoons, this paper discusses real-time correction for forecasting the track of four typhoons during 2009 and 2010 in Japan, Beijing, Guangzhou, and Shanghai. It was determin... Using real-time correction technology for typhoons, this paper discusses real-time correction for forecasting the track of four typhoons during 2009 and 2010 in Japan, Beijing, Guangzhou, and Shanghai. It was determined that the short-time forecast effect was better than the original objective mode. By selecting four types of integration schemes after multiple mode path integration for those four objective modes, the forecast effect of the multi-mode path integration is better, on average, than any single model. Moreover, multi-mode ensemble forecasting has obvious advantages during the initial 36 h. 展开更多
关键词 typhoon path real-time correction ensemble forecast track errors
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Dust Storm Ensemble Forecast Experiments in East Asia 认领 引用 被引量：4
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作者 朱江 林彩燕 王自发 《Advances in Atmospheric Sciences》 SCIE CAS 2009年第6期1053-1070,共18页
The ensemble Kalman filter （EnKF）, as a unified approach to both data assimilation and ensemble forecasting problems, is used to investigate the performance of dust storm ensemble forecasting targeting a dust episod... The ensemble Kalman filter （EnKF）, as a unified approach to both data assimilation and ensemble forecasting problems, is used to investigate the performance of dust storm ensemble forecasting targeting a dust episode in the East Asia during 23-30 May 2007. The errors in the input wind field, dust emission intensity, and dry deposition velocity are among important model uncertainties and are considered in the model error perturbations. These model errors are not assumed to have zero-means. The model error means representing the model bias are estimated as part of the data assimilation process. Observations from a LIDAR network are assimilated to generate the initial ensembles and correct the model biases. The ensemble forecast skills are evaluated against the observations and a benchmark/control forecast, which is a simple model run without assimilation of any observations. Another ensemble forecast experiment is also performed without the model bias correction in order to examine the impact of the bias correction. Results show that the ensemble-mean, as deterministic forecasts have substantial improvement over the control forecasts and correctly captures the major dust arrival and cessation timing at each observation site. However, the forecast skill decreases as the forecast lead time increases. Bias correction further improved the forecasts in down wind areas. The forecasts within 24 hours are most improved and better than those without the bias correction. The examination of the ensemble forecast skills using the Brier scores and the relative operating characteristic curves and areas indicates that the ensemble forecasting system has useful forecast skills. 展开更多
关键词 dust storm ensemble forecast data assimilation bias correction
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Sensitivity Analysis of the Super Heavy Rainfall Event in Henan on 20 July(2021)Using ECMWF Ensemble Forecasts 认领 引用 被引量：5
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作者 HUANG Qi-jun GE Xu-yang +1 位作者 PENG Melinda DENG Zhong-ren 《Journal of Tropical Meteorology》 SCIE 2022年第3期308-325,共18页
An unprecedented heavy rainfall event occurred in Henan Province,China,during the period of 1200 UTC 19-1200 UTC 20 July 2021 with a record of 522 mm accumulated rainfall.Zhengzhou,the capital city of Henan,received 2... An unprecedented heavy rainfall event occurred in Henan Province,China,during the period of 1200 UTC 19-1200 UTC 20 July 2021 with a record of 522 mm accumulated rainfall.Zhengzhou,the capital city of Henan,received 201.9 mm of rainfall in just one hour on the day.In the present study,the sensitivity of this event to atmospheric variables is investigated using the ECMWF ensemble forecasts.The sensitivity analysis first indicates that a local YellowHuai River low vortex(YHV)in the southern part of Henan played a crucial role in this extreme event.Meanwhile,the western Pacific subtropical high(WPSH)was stronger than the long-term average and to the west of its climatological position.Moreover,the existence of a tropical cyclone(TC)In-Fa pushed into the peripheral of the WPSH and brought an enhanced easterly flow between the TC and WPSH channeling abundant moisture to inland China and feeding into the YHV.Members of the ECMWF ensemble are selected and grouped into the GOOD and the POOR groups based on their predicted maximum rainfall accumulations during the event.Some good members of ECMWF ensemble Prediction System(ECMWF-EPS)are able to capture good spatial distribution of the heavy rainfall,but still underpredict its extremity.The better prediction ability of these members comes from the better prediction of the evolution characteristics(i.e.,intensity and location)of the YHV and TC In-Fa.When the YHV was moving westward to the south of Henan,a relatively strong southerly wind in the southwestern part of Henan converged with the easterly flow from the channel wind between In-Fa and WPSH.The convergence and accompanying ascending motion induced heavy precipitation. 展开更多
关键词 ensemble forecast extremely heavy rainfall sensitivity analysis
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Typhoon storm surge ensemble forecast based on GPU technique 认领 引用 被引量：1
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作者 Qiuxing Liu Jinrong Jiang +4 位作者 Fujiang Yu Changkuan Zhang Jianxi Dong Xiaojiang Song Yuzhu Wang 《Acta Oceanologica Sinica》 SCIE CAS CSCD 2020年第5期77-86,共10页
The accuracy of typhoon forecasts plays an important role in the prediction of storm surges.The uncertainty of a typhoon’s intensity and track means it is necessary to use an ensemble model to predict typhoon storm s... The accuracy of typhoon forecasts plays an important role in the prediction of storm surges.The uncertainty of a typhoon’s intensity and track means it is necessary to use an ensemble model to predict typhoon storm surges.A hydrodynamic model,which is operational at the National Marine Environmental Forecasting Center,is applied to conduct surge simulations for South China coastal areas using the best track data with parametric wind and pressure models.The results agree well with tidal gauge observations.To improve the calculation efficiency,the hydrodynamic model is modified using CUDA Fortran.The calculation results are almost the same as those from the original model,but the calculation time is reduced by more than 99%.A total of 150 typhoon cases are generated by combining 50 typhoon tracks from the European Centre for Medium-Range Weather Forecasts with three possible typhoon intensity forecasts.The surge ensembles are computed by the improved hydrodynamic model.Based on the simulated storm surges for the different typhoon cases,ensemble and probability forecast products can be provided.The mean ensemble results and probability forecast products are shown to agree well with the observed storm surge caused by Typhoon Mangkhut.The improved model is highly suitable for ensemble numerical forecasts,providing better forecast products for decision-making,and can be easily implemented to run on regular workstations. 展开更多
关键词 typhoon storm surge ensemble forecast probability forecast CUDA Fortran
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AN ENSEMBLE FORECAST EXPERIMENT OF A LANDING TYPHOON 认领 引用 被引量：5
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作者 谭燕 梁旭东 《Journal of Tropical Meteorology》 SCIE 2012年第3期314-321,共8页
Based on the Global Regional Assimilation and Prediction System-Tropical Cyclone Model(GRAPES-TCM),an ensemble forecast experiment was performed,in which Typhoon Wipha during the period immediately prior to landfall w... Based on the Global Regional Assimilation and Prediction System-Tropical Cyclone Model(GRAPES-TCM),an ensemble forecast experiment was performed,in which Typhoon Wipha during the period immediately prior to landfall was selected for the study and the breeding of growing mode(BGM) method was used to perturb the initial conditions of the vortex field and the environment field.The results of the experiment indicate that each member had a different initial status in BGM processing and they show a reasonable spread among members along with the forecast phase.Changes in the large-scale field,thermodynamic structure,and spread among members took place when Wipha made landfall.The steering effect of the large-scale field and the interaction between the thermodynamics and the dynamics resulted in different tracks of the members.Meanwhile,the forecast uncertainty increased.In summary,the ensemble mean did not perform as well as the control forecast,but the cluster mean provided some useful information,and performed better than the control in some instances.The position error was 34 km for 24 h forecast,153 km for 48 h forecast,and 191 km for 66 h forecast.The strike probability chart qualitatively described the forecast uncertainty. 展开更多
关键词 landing typhoon ensemble forecast GRAPES-TCM breeding of growing mode method cluster analysis
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Evaluation of WRF-based Convection-Permitting Multi-Physics Ensemble Forecasts over China for an Extreme Rainfall Event on 21 July 2012 in Beijing 认领 引用 被引量：23
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作者 Kefeng ZHU Ming XUE 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2016年第11期1240-1258,共19页
On 21 July 2012,an extreme rainfall event that recorded a maximum rainfall amount over 24 hours of 460 mm,occurred in Beijing,China. Most operational models failed to predict such an extreme amount. In this study,a co... On 21 July 2012,an extreme rainfall event that recorded a maximum rainfall amount over 24 hours of 460 mm,occurred in Beijing,China. Most operational models failed to predict such an extreme amount. In this study,a convective-permitting ensemble forecast system（CEFS）,at 4-km grid spacing,covering the entire mainland of China,is applied to this extreme rainfall case. CEFS consists of 22 members and uses multiple physics parameterizations. For the event,the predicted maximum is 415 mm d^-1 in the probability-matched ensemble mean. The predicted high-probability heavy rain region is located in southwest Beijing,as was observed. Ensemble-based verification scores are then investigated. For a small verification domain covering Beijing and its surrounding areas,the precipitation rank histogram of CEFS is much flatter than that of a reference global ensemble. CEFS has a lower（higher） Brier score and a higher resolution than the global ensemble for precipitation,indicating more reliable probabilistic forecasting by CEFS. Additionally,forecasts of different ensemble members are compared and discussed. Most of the extreme rainfall comes from convection in the warm sector east of an approaching cold front. A few members of CEFS successfully reproduce such precipitation,and orographic lift of highly moist low-level flows with a significantly southeasterly component is suggested to have played important roles in producing the initial convection. Comparisons between good and bad forecast members indicate a strong sensitivity of the extreme rainfall to the mesoscale environmental conditions,and,to less of an extent,the model physics. 展开更多
关键词 extreme rainfall ensemble forecast Ensemble convective mesoscale convection mainland verification
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Ensemble Forecast: A New Approach to Uncertainty and Predictability 认领 引用 被引量：28
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作者 Yuejian ZHU 《Advances in Atmospheric Sciences》 SCIE CAS 2005年第6期781-788,共8页
Ensemble techniques have been used to generate daily numerical weather forecasts since the 1990s in numerical centers around the world due to the increase in computation ability. One of the main purposes of numerical ... Ensemble techniques have been used to generate daily numerical weather forecasts since the 1990s in numerical centers around the world due to the increase in computation ability. One of the main purposes of numerical ensemble forecasts is to try to assimilate the initial uncertainty （initial error） and the forecast uncertainty （forecast error） by applying either the initial perturbation method or the multi-model/multiphysics method. In fact, the mean of an ensemble forecast offers a better forecast than a deterministic （or control） forecast after a short lead time （3-5 days） for global modelling applications. There is about a 1-2-day improvement in the forecast skill when using an ensemble mean instead of a single forecast for longer lead-time. The skillful forecast （65% and above of an anomaly correlation） could be extended to 8 days （or longer） by present-day ensemble forecast systems. Furthermore, ensemble forecasts can deliver a probabilistic forecast to the users, which is based on the probability density function （PDF） instead of a single-value forecast from a traditional deterministic system. It has long been recognized that the ensemble forecast not only improves our weather forecast predictability but also offers a remarkable forecast for the future uncertainty, such as the relative measure of predictability （RMOP） and probabilistic quantitative precipitation forecast （PQPF）. Not surprisingly, the success of the ensemble forecast and its wide application greatly increase the confidence of model developers and research communities. 展开更多
关键词 ensemble forecast predictability uncertainty
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Ensemble Forecast for Tropical Cyclone Based on CNOP-P Method:A Case Study of WRF Model and Two Typhoons 认领 引用 被引量：1
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作者 YUAN Shi-jin SHI Bo +3 位作者 ZHAO Zi-jun MU Bin ZHOU Fei-fan DUAN Wan-suo 《Journal of Tropical Meteorology》 SCIE 2022年第2期121-138,共18页
In this paper,we set out to study the ensemble forecast for tropical cyclones.The case study is based on the Conditional Nonlinear Optimal Perturbation related to Parameter(CNOP-P)method and the WRF model to improve t... In this paper,we set out to study the ensemble forecast for tropical cyclones.The case study is based on the Conditional Nonlinear Optimal Perturbation related to Parameter(CNOP-P)method and the WRF model to improve the prediction accuracy for track and intensity,and two different typhoons are selected as cases for analysis.We first select perturbed parameters in the YSU and WSM6 schemes,and then solve CNOP-Ps with simulated annealing algorithm for single parameters as well as the combination of multiple parameters.Finally,perturbations are imposed on default parameter values to generate the ensemble members.The whole proposed procedures are referred to as the PerturbedParameter Ensemble(PPE).We also conduct two experiments,which are control forecast and ensemble forecast,termed Ctrl and perturbed-physics ensemble(PPhyE)respectively,to demonstrate the performance for contrast.In the article,we compare the effects of three experiments on tropical cyclones in aspects of track and intensity,respectively.For track,the prediction errors of PPE are smaller.The ensemble mean of PPE filters the unpredictable situation and retains the reasonably predictable components of the ensemble members.As for intensity,ensemble mean values of the central minimum sea-level pressure and the central maximum wind speed are closer to CMA data during most of the simulation time.The predicted values of the PPE ensemble members included the intensity of CMA data when the typhoon made landfall.The PPE also shows uncertainty in the forecast.Moreover,we also analyze the track and intensity from physical variable fields of PPE.Experiment results show PPE outperforms the other two benchmarks in track and intensity prediction. 展开更多
关键词 ensemble forecast Conditional Nonlinear Optimal Perturbation related to Parameter(CNOP-P) WRF parameter perturbation ensemble members simulated annealing algorithm
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Comparison of aircraft observations with ensemble forecast model results in terms of the microphysical characteristics of stratiform precipitation 认领 引用 被引量：1
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作者 FU Yuan LEI Hengchi +2 位作者 YANG Jiefan GUO Jiaxu ZHU Jiangshan 《Atmospheric and Oceanic Science Letters》 CSCD 2020年第5期452-461,共10页
The prediction of the particle number concentration and liquid/ice water content of cloud is significant for many aspects of atmospheric science.However,given the uncertainties in the initial and boundary conditions a... The prediction of the particle number concentration and liquid/ice water content of cloud is significant for many aspects of atmospheric science.However,given the uncertainties in the initial and boundary conditions and imperfections of microphysical schemes,the accurate prediction of these microphysical properties of cloud is still a big challenge.The ensemble approach may be a viable way to reduce forecast uncertainties.In this paper,a large-scale stratiform cloud precipitation process is studied by comparing results of a 10-member ensemble forecast model with aircraft observation data.By means of the ensemble average,the prediction of bulk parameters such as liquid water content and ice water content can be improved in comparison with the control member,but the particle number concentrations are still one to two orders of magnitude less than those from observations.Intercomparison of raindrop size spectra reveals a big distinction between observations and predictions for particles with a diameter less than 1000μm. 展开更多
关键词 Aircraft observation ensemble forecast model particle number concentration liquid/ice water content
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Key Deviation Analysis of Initial Fields on Ensemble Forecast in South China During the Rainfall Event on May 21,2020 认领 引用 被引量：1
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作者 LI Ji-hang XIAO Hui +5 位作者 DING Wei-yu ZHANG Xu-bin YIN Tian-xiang ZHENG Yan-ping WEN Qiu-shi LI Hui-qi 《Journal of Tropical Meteorology》 SCIE 2021年第4期418-427,共10页
Extreme rainfall is common from May to October in south China.This study investigates the key deviation of initial fields on ensemble forecast of a persistent heavy rainfall event from May 20 to 22,2020 in Guangdong P... Extreme rainfall is common from May to October in south China.This study investigates the key deviation of initial fields on ensemble forecast of a persistent heavy rainfall event from May 20 to 22,2020 in Guangdong Province,south China by comparing ensemble members with different performances.Based on the rainfall distribution and pattern,two types are selected for analysis compared with the observed precipitation.Through the comparison of the thermal and dynamic fields in the middle and lower layers,it can be found that the thermal difference between the middle and lower layers was an important factor which led to the deviation of precipitation distribution.The dynamic factors also have some effects on the precipitation area although they were not as important as the thermal factors in this case.Correlating accumulated precipitation with atmospheric state variables further corroborates the above conclusion.This study suggests that the uncertainty of the thermal and dynamic factors in the numerical model can have a strong impact on the quantitative skills of heavy rainfall forecasts. 展开更多
关键词 ensemble forecast rainfall in south China key deviation initial field
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Impact of Soil Moisture Uncertainty on Summertime Short-range Ensemble Forecasts 认领 引用 被引量：2
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作者 Jiangshan ZHU Fanyou KONG +3 位作者 Xiao-Ming HU Yan GUO Lingkun RAN Hengchi LEI 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2018年第7期839-852,共14页
To investigate the impact of soil moisture uncertainty on summertime short-range ensemble forecasts（SREFs）, a fivemember SREF experiment with perturbed initial soil moisture（ISM） was performed over a northern Chin... To investigate the impact of soil moisture uncertainty on summertime short-range ensemble forecasts（SREFs）, a fivemember SREF experiment with perturbed initial soil moisture（ISM） was performed over a northern China domain in summertime from July to August 2014. Five soil moisture analyses from three different operationalesearch centers were used as the ISM for the ensemble. The ISM perturbation produced notable ensemble spread in near-surface variables and atmospheric variables below 800 h Pa, and produced skillful ensemble-mean 24-h accumulated precipitation（APCP24） forecasts that outperformed any single ensemble member. Compared with a second SREF experiment with mixed microphysics parameterization options, the ISM-perturbed ensemble produced comparable ensemble spread in APCP24 forecasts, and had better Brier scores and resolution in probabilistic APCP24 forecasts for 10-mm, 25-mm and 50-mm thresholds. The ISM-perturbed ensemble produced obviously larger ensemble spread in near-surface variables. It was, however, still under-dispersed, indicating that perturbing ISM alone may not be adequate in representing all the uncertainty at the near-surface level, indicating further SREF studies are needed to better represent the uncertainties in land surface processes and their coupling with the atmosphere. 展开更多
关键词 ensemble forecast soil moisture perturbation probabilistic quantitative precipitation forecast
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SAMPLE OPTIMIZATION OF ENSEMBLE FORECAST TO SIMULATE TROPICAL STORMS(MERBOK, MAWAR, AND GUCHOL) USING THE OBSERVED TRACK 认领 引用 被引量：1
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作者 LI Ji-hang GAO Yu-dong +1 位作者 WAN Qi-lin ZHANG Xu-bin 《Journal of Tropical Meteorology》 SCIE 2020年第1期14-26,共13页
Nowadays,ensemble forecasting is popular in numerical weather prediction(NWP).However,an ensemble may not produce a perfect Gaussian probability distribution due to limited members and the fact that some members signi... Nowadays,ensemble forecasting is popular in numerical weather prediction(NWP).However,an ensemble may not produce a perfect Gaussian probability distribution due to limited members and the fact that some members significantly deviate from the true atmospheric state.Therefore,event samples with small probabilities may downgrade the accuracy of an ensemble forecast.In this study,the evolution of tropical storms(weak typhoon)was investigated and an observed tropical storm track was used to limit the probability distribution of samples.The ensemble forecast method used pure observation data instead of assimilated data.In addition,the prediction results for three tropical storm systems,Merbok,Mawar,and Guchol,showed that track and intensity errors could be reduced through sample optimization.In the research,the vertical structures of these tropical storms were compared,and the existence of different thermal structures was discovered.One possible reason for structural differences is sample optimization,and it may affect storm intensity and track. 展开更多
关键词 ensemble forecast sample optimization tropical storm observed track
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EXPERIMENTS OF ENSEMBLE FORECAST OF TYPHOON TRACK USING BDA PERTURBING METHOD 认领 引用 被引量：1
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作者 黄燕燕 万齐林 +1 位作者 袁金南 丁伟钰 《Journal of Tropical Meteorology》 2006年第2期159-164,共6页
A new method, BDA perturbing, is used in ensemble forecasting of typhoon track. This method is based on the Bogus Data Assimilation scheme. It perturbs the initial position and intensity of typhoons and gets; a series... A new method, BDA perturbing, is used in ensemble forecasting of typhoon track. This method is based on the Bogus Data Assimilation scheme. It perturbs the initial position and intensity of typhoons and gets; a series of bogus vortex. Then each bogus vortex is used in data assimilation to obtain initial conditions. Ensemble forecast members are constructed by conducting simulation with these initial conditions. Some cases of typhoon are chosen to test the validity of this new method and the results show that： using the BDA perturbing method to perturb initial position and intensity of typhoon for track tbrecast can improve accuracy, compared with the direct use of the BDA assimilation scheme. And it is concluded that a perturbing amplitude of intensity of 5 hPa is probably more appropriate than 10 hPa if the BDA perturbing method is used in combination with initial position perturbation. 展开更多
关键词 ensemble forecast typhoon track BDA perturbing method typhoon numerical forecast
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Comparison of different land-surface perturbation methods in short-range ensemble forecasts 认领 引用
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作者 Zhibo Gao Jiangshan Zhu +4 位作者 Yan Guo Xiaodong Yan Xiujuan Wang Huoqing Li Shuwen Li 《Atmospheric and Oceanic Science Letters》 CSCD 2021年第3期60-65,共6页
In order to compare the sensitivity of short-range ensemble forecasts to different land-surface parameters in the South China region,three perturbation experiments related to the land surface model(LSM),initial soil m... In order to compare the sensitivity of short-range ensemble forecasts to different land-surface parameters in the South China region,three perturbation experiments related to the land surface model(LSM),initial soil moisture(ISM),and land–atmosphere coupling coefficient(LCC)were designed,and another control experiment driven by the Global Ensemble Forecast System(GEFS)was also performed.All ensemble members were initiated at 0000 UTC each day,and integrated for 24 h for a total of 40 days from the period 1 April to 10 May 2019 based on the Weather Research and Forecasting model.The results showed that the perturbation experiment of the LSM(LSMPE)had the largest ensemble spread,as well as the lowest ensemble-mean root-mean-square error among the three sets of land-surface perturbed experiments,which indicated that it could represent more uncertainty and less error.The ensemble spread of the perturbation experiment of the ISM(ISMPE)was generally less than that of LSMPE but greater than that of LCCPE(the perturbation experiment of the LCC).In particular,although the perturbation of the LCC could not produce greater spread,it had an effective influence on the intensity of precipitation.However,the ensemble spread of all the land-surface perturbed experiments was smaller than that of GEFSPE(the control experiment).Therefore,in future,land-surface perturbations and atmospheric perturbations should be combined in the design of ensemble forecasting systems to make the model represent more uncertainties. 展开更多
关键词 Short-range ensemble forecast Land-surface parameter South china region
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Improvement in Background Error Covariances Using Ensemble Forecasts for Assimilation of High-Resolution Satellite Data 认领 引用
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作者 Seung-Woo LEE Dong-Kyou LEE 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2011年第4期758-774,共17页
Satellite data obtained over synoptic data-sparse regions such as an ocean contribute toward improving the quality of the initial state of limited-area models. Background error covariances are crucial to the proper di... Satellite data obtained over synoptic data-sparse regions such as an ocean contribute toward improving the quality of the initial state of limited-area models. Background error covariances are crucial to the proper distribution of satellite-observed information in variational data assimilation. In the NMC （National Meteorological Center） method, background error covariances are underestimated over data-sparse regions such as an ocean because of small differences between different forecast times. Thus, it is necessary to reconstruct and tune the background error covariances so as to maximize the usefulness of the satellite data for the initial state of limited-area models, especially over an ocean where there is a lack of conventional data. In this study, we attempted to estimate background error covariances so as to provide adequate error statistics for data-sparse regions by using ensemble forecasts of optimal perturbations using bred vectors. The background error covariances estimated by the ensemble method reduced the overestimation of error amplitude obtained by the NMC method. By employing an appropriate horizontal length scale to exclude spurious correlations, the ensemble method produced better results than the NMC method in the assimilation of retrieved satellite data. Because the ensemble method distributes observed information over a limited local area, it would be more useful in the analysis of high-resolution satellite data. Accordingly, the performance of forecast models can be improved over the area where the satellite data are assimilated. 展开更多
关键词 3DVAR background error covariances retrieved satellite data assimilation ensemble forecasts.
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