A new forecasting system-the System of Multigrid Nonlinear Least-squares Four-dimensional Variational(NLS-4DVar)Data Assimilation for Numerical Weather Prediction(SNAP)-was established by building upon the multigrid N...A new forecasting system-the System of Multigrid Nonlinear Least-squares Four-dimensional Variational(NLS-4DVar)Data Assimilation for Numerical Weather Prediction(SNAP)-was established by building upon the multigrid NLS-4DVar data assimilation scheme,the operational Gridpoint Statistical Interpolation(GSI)−based data-processing and observation operators,and the widely used Weather Research and Forecasting numerical model.Drawing upon lessons learned from the superiority of the operational GSI analysis system,for its various observation operators and the ability to assimilate multiple-source observations,SNAP adopts GSI-based data-processing and observation operator modules to compute the observation innovations.The multigrid NLS-4DVar assimilation framework is used for the analysis,which can adequately correct errors from large to small scales and accelerate iteration solutions.The analysis variables are model state variables,rather than the control variables adopted in the conventional 4DVar system.Currently,we have achieved the assimilation of conventional observations,and we will continue to improve the assimilation of radar and satellite observations in the future.SNAP was evaluated by case evaluation experiments and one-week cycling assimilation experiments.In the case evaluation experiments,two six-hour time windows were established for assimilation experiments and precipitation forecasts were verified against hourly precipitation observations from more than 2400 national observation sites.This showed that SNAP can absorb observations and improve the initial field,thereby improving the precipitation forecast.In the one-week cycling assimilation experiments,six-hourly assimilation cycles were run in one week.SNAP produced slightly lower forecast RMSEs than the GSI 4DEnVar(Four-dimensional Ensemble Variational)as a whole and the threat scores of precipitation forecasts initialized from the analysis of SNAP were higher than those obtained from the analysis of GSI 4DEnVar.展开更多
The potential predictability of climatological mean circulation and the interannual variation of the South China Sea summer monsoon (SCSSM) were investigated using hindcast results from the Institute of Atmospheric Ph...The potential predictability of climatological mean circulation and the interannual variation of the South China Sea summer monsoon (SCSSM) were investigated using hindcast results from the Institute of Atmospheric Physics Dynamical Seasonal Prediction System (IAP DCP),along with the National Centers for Environmental Prediction (NCEP) reanalysis data from the period of 1980-2000.The large-scale characteristics of the SCSSM monthly and seasonal mean low-level circulation have been well reproduced by IAP DCP,especially for the zonal wind at 850 hPa;furthermore,the hindcast variability also agrees quite well with observations.By introducing the South China Sea summer monsoon index,the potential predictability of IAP DCP for the intensity of the SCSSM has been evaluated.IAP DCP showed skill in predicting the interannual variation of SCSSM intensity.The result is highly encouraging;the correlation between the hindcasted and observed SCSSM Index was 0.58,which passes the 95% significance test.The result for the seasonal mean June-July-August SCSSM Index was better than that for the monthly mean,suggesting that seasonal forecasts are more reliable than monthly forecasts.展开更多
The recent progresses in the research and development of (NWP) in China are reviewed in this paper. The most impressive achievements are the development of direct assimilation of satellite irradiances with a 3DVAR (th...The recent progresses in the research and development of (NWP) in China are reviewed in this paper. The most impressive achievements are the development of direct assimilation of satellite irradiances with a 3DVAR (three-dimentional variational) data assimilation system and a non-hydrostatic modei with a semi-Lagrangian semi-implicit scheme. Progresses have also been made in modei physics and modei application to precipitation and environmental forecasts. Some scientific issues of great importance for further development are discussed.展开更多
In this paper, an analogue correction method of errors (ACE) based on a complicated atmospheric model is further developed and applied to numerical weather prediction (NWP). The analysis shows that the ACE can eff...In this paper, an analogue correction method of errors (ACE) based on a complicated atmospheric model is further developed and applied to numerical weather prediction (NWP). The analysis shows that the ACE can effectively reduce model errors by combining the statistical analogue method with the dynamical model together in order that the information of plenty of historical data is utilized in the current complicated NWP model, Furthermore, in the ACE, the differences of the similarities between different historical analogues and the current initial state are considered as the weights for estimating model errors. The results of daily, decad and monthly prediction experiments on a complicated T63 atmospheric model show that the performance of the ACE by correcting model errors based on the estimation of the errors of 4 historical analogue predictions is not only better than that of the scheme of only introducing the correction of the errors of every single analogue prediction, but is also better than that of the T63 model.展开更多
In this paper,the unsteady flow around a high-speed train is numerically simulated by detached eddy simulation method(DES),and the far-field noise is predicted using the Ffowcs Williams-Hawkings(FW-H)acoustic model.Th...In this paper,the unsteady flow around a high-speed train is numerically simulated by detached eddy simulation method(DES),and the far-field noise is predicted using the Ffowcs Williams-Hawkings(FW-H)acoustic model.The reliability of the numerical calculation is verified by wind tunnel experiments.The superposition relationship between the far-field radiated noise of the local aerodynamic noise sources of the high-speed train and the whole noise source is analyzed.Since the aerodynamic noise of high-speed trains is derived from its different components,a stepwise calculation method is proposed to predict the aerodynamic noise of high-speed trains.The results show that the local noise sources of high-speed trains and the whole noise source conform to the principle of sound source energy superposition.Using the head,middle and tail cars of the high-speed train as noise sources,different numerical models are established to obtain the far-field radiated noise of each aerodynamic noise source.The far-field total noise of high-speed trains is predicted using sound source superposition.A step-by-step calculation of each local aerodynamic noise source is used to obtain the superimposed value of the far-field noise.This is consistent with the far-field noise of the whole train model’s aerodynamic noise.The averaged sound pressure level of the far-field longitudinal noise measurement points differs by 1.92 dBA.The step-by-step numerical prediction method of aerodynamic noise of high-speed trains can provide a reference for the numerical prediction of aerodynamic noise generated by long marshalling high-speed trains.展开更多
The movement of Typhoon Maggie (9903) in June 1999 is one of the rare cases ever seen in the history. At 00U on June 6 Maggie was located at about 70 km to the southwest of Taiwan. When it arrived at the coastal regio...The movement of Typhoon Maggie (9903) in June 1999 is one of the rare cases ever seen in the history. At 00U on June 6 Maggie was located at about 70 km to the southwest of Taiwan. When it arrived at the coastal region of Shanwei City (22.8N, 116.5E), it turned suddenly to move southwestward along the southern China coastal line. De June 7 Maggie finally turned to move northward, making landfall to the north of Shangchuan Island. The experimental numerical prediction system on typhoon movement that was designed based on MM5 is proved quite successful for the 48h prediction of Maggie's movement and rainfall. The mean prediction error of typhoon track is 81 km for 0-24 h and 74 km for 24-48 h. The location of typhoon center in the initial field of the model is approximately 100 km away from the actual observations. In order to modify the location of typhoon center, a bogus typhoon was intro- duced into the model and the prediction of typhoon track was improved in 0-24 h time interval. But the prediction error was enlarged in 24-36 h. We also performed a sensitivity experiment of changing the land of southern China into the ocean. It is found that the orientation of South China coastal line and the topography have no obvious effect on the movement of Typhoon Maggie.展开更多
The initial value error and the imperfect numerical model are usually considered as error sources of numerical weather prediction (NWP). By using past multi-time observations and model output, this study proposes a ...The initial value error and the imperfect numerical model are usually considered as error sources of numerical weather prediction (NWP). By using past multi-time observations and model output, this study proposes a method to estimate imperfect numerical model error. This method can be inversely estimated through expressing the model error as a Lagrange interpolation polynomial, while the coefficients of polyno- mial are determined by past model performance. However, for practical application in the full NWP model, it is necessary to determine the following criteria: (1) the length of past data sufficient for estimation of the model errors, (2) a proper method of estimating the term "model integration with the exact solution" when solving the inverse problem, and (3) the extent to which this scheme is sensitive to the observational errors. In this study, such issues are resolved using a simple linear model, and an advection diffusion model is applied to discuss the sensitivity of the method to an artificial error source. The results indicate that the forecast errors can be largely reduced using the proposed method if the proper length of past data is chosen. To address the three problems, it is determined that (1) a few data limited by the order of the corrector can be used, (2) trapezoidal approximation can be employed to estimate the "term" in this study; however, a more accurate method should be explored for an operational NWP model, and (3) the correction is sensitive to observational error.展开更多
Model error is one of the key factors restricting the accuracy of numerical weather prediction (NWP). Considering the continuous evolution of the atmosphere, the observed data (ignoring the measurement error) can ...Model error is one of the key factors restricting the accuracy of numerical weather prediction (NWP). Considering the continuous evolution of the atmosphere, the observed data (ignoring the measurement error) can be viewed as a series of solutions of an accurate model governing the actual atmosphere. Model error is represented as an unknown term in the accurate model, thus NWP can be considered as an inverse problem to uncover the unknown error term. The inverse problem models can absorb long periods of observed data to generate model error correction procedures. They thus resolve the deficiency and faultiness of the NWP schemes employing only the initial-time data. In this study we construct two inverse problem models to estimate and extrapolate the time-varying and spatial-varying model errors in both the historical and forecast periods by using recent observations and analogue phenomena of the atmosphere. Numerical experiment on Burgers' equation has illustrated the substantial forecast improvement using inverse problem algorithms. The proposed inverse problem methods of suppressing NWP errors will be useful in future high accuracy applications of NWP.展开更多
Numerical Weather Prediction(NWP)is a necessary input for short-term wind power forecasting.Existing NWP models are all based on purely physical models.This requires mainframe computers to perform large-scale numerica...Numerical Weather Prediction(NWP)is a necessary input for short-term wind power forecasting.Existing NWP models are all based on purely physical models.This requires mainframe computers to perform large-scale numerical calculations and the technical threshold of the assimilation process is high.There is a need to further improve the timeliness and accuracy of the assimilation process.In order to solve the above problems,NWP method based on artificial intelligence is proposed in this paper.It uses a convolutional neural network algorithm and a downscaling model from the global background field to establish a given wind turbine hub height position.We considered the actual data of a wind farm in north China as an example to analyze the calculation example.The results show that the prediction accuracy of the proposed method is equivalent to that of the traditional purely physical model.The prediction accuracy in some months is better than that of the purely physical model,and the calculation efficiency is considerably improved.The validity and advantages of the proposed method are verified from the results,and the traditional NWP method is replaced to a certain extent.展开更多
[Objective] The research aimed to analyze explanation effect of the European numerical prediction on temperature. [Method] Based on CMSVM regression method, by using 850 hPa grid point data of the European numerical p...[Objective] The research aimed to analyze explanation effect of the European numerical prediction on temperature. [Method] Based on CMSVM regression method, by using 850 hPa grid point data of the European numerical prediction from 2003 to 2009 and actual data of the maximum and minimum temperatures at 8 automatic stations in Qingyang City, prediction model of the temperature was established, and running effect of the business from 2008 to 2010 was tested and evaluated. [Result] The method had very good guidance role in real-time business running of the temperature prediction. Test and evaluation found that as forecast time prolonged, prediction accuracies of the maximum and minimum temperatures declined. When temperature anomaly was higher (actual temperature was higher than historical mean), prediction accuracy increased. Influence of the European numerical prediction was bigger. [Conclusion] Compared with other methods, operation of the prediction method was convenient, modeling was automatic, running time was short, system was stable, and prediction accuracy was high. It was suitable for implementing of the explanation work for numerical prediction product at meteorological station.展开更多
In earthquake early warning systems, real-time shake prediction through wave propagation simulation is a promising approach. Compared with traditional methods, it does not suffer from the inaccurate estimation of sour...In earthquake early warning systems, real-time shake prediction through wave propagation simulation is a promising approach. Compared with traditional methods, it does not suffer from the inaccurate estimation of source parameters. For computation efficiency, wave direction is assumed to propagate on the 2-D surface of the earth in these methods. In fact, since the seismic wave propagates in the 3-D sphere of the earth, the 2-D space modeling of wave direction results in inaccurate wave estimation. In this paper, we propose a 3-D space numerical shake pre- diction method, which simulates the wave propagation in 3-D space using radiative transfer theory, and incorporate data assimilation technique to estimate the distribution of wave energy. 2011 Tohoku earthquake is studied as an example to show the validity of the proposed model. 2-D space model and 3-D space model are compared in this article, and the prediction results show that numerical shake prediction based on 3-D space model can estimate the real-time ground motion precisely, and overprediction is alleviated when using 3-D space model.展开更多
In this paper, on the basis of the heat conduction equation without consideration of the advection and turbulence effects, one-dimensional model for describing surface sea temperature ( T1), bottom sea temperature ( T...In this paper, on the basis of the heat conduction equation without consideration of the advection and turbulence effects, one-dimensional model for describing surface sea temperature ( T1), bottom sea temperature ( Tt ) and the thickness of the upper homogeneous layer ( h ) is developed in terms of the dimensionless temperature θT and depth η and self-simulation function θT - f(η) of vertical temperature profile by means of historical temperature data.The results of trial prediction with our one-dimensional model on T, Th, h , the thickness and gradient of thermocline are satisfactory to some extent.展开更多
Can earthquakes be predicted? How should people overcome the difficulties encountered in the study of earthquake prediction? This issue can take inspiration from the experiences of weather forecast. Although weather...Can earthquakes be predicted? How should people overcome the difficulties encountered in the study of earthquake prediction? This issue can take inspiration from the experiences of weather forecast. Although weather forecasting took a period of about half a century to advance from empirical to numerical forecast, it has achieved significant success. A consensus has been reached among the Chinese seismological community that earth- quake prediction must also develop from empirical fore- casting to physical prediction. However, it is seldom mentioned that physical prediction is characterized by quantitatively numerical predictions based on physical laws. This article discusses five key components for numerical earthquake prediction and their current status. We conclude that numerical earthquake prediction should now be put on the planning agenda and its roadmap designed, seismic stations should be deployed and observations made according to the needs of numerical prediction, and theoretical research should be carried out.展开更多
A numerical simulation model for predicting residual stresses which arise during the solidification process of pressed glass bulb panel was developed. The solidification of a molten layer of glass between cooled paral...A numerical simulation model for predicting residual stresses which arise during the solidification process of pressed glass bulb panel was developed. The solidification of a molten layer of glass between cooled parallel plates was used to model the mechanics of the buildup of residual stresses in the forming process. A thermorheologically simple thermoviscoelastic model was assumed for the material. The finite element method employed was based on the theory of shells as an assembly of flat elements. This approach calculates residual stresses layer by layer like a truly three-dimensional calculation, which is well suited for thin pressed products of complex shape. An experimental comparison was employed to verify the proposed models and methods.展开更多
Many weather radar networks in the world have now provided polarimetric radar data(PRD)that have the potential to improve our understanding of cloud and precipitation microphysics,and numerical weather prediction(NWP)...Many weather radar networks in the world have now provided polarimetric radar data(PRD)that have the potential to improve our understanding of cloud and precipitation microphysics,and numerical weather prediction(NWP).To realize this potential,an accurate and efficient set of polarimetric observation operators are needed to simulate and assimilate the PRD with an NWP model for an accurate analysis of the model state variables.For this purpose,a set of parameterized observation operators are developed to simulate and assimilate polarimetric radar data from NWP model-predicted hydrometeor mixing ratios and number concentrations of rain,snow,hail,and graupel.The polarimetric radar variables are calculated based on the T-matrix calculation of wave scattering and integrations of the scattering weighted by the particle size distribution.The calculated polarimetric variables are then fitted to simple functions of water content and volumeweighted mean diameter of the hydrometeor particle size distribution.The parameterized PRD operators are applied to an ideal case and a real case predicted by the Weather Research and Forecasting(WRF)model to have simulated PRD,which are compared with existing operators and real observations to show their validity and applicability.The new PRD operators use less than one percent of the computing time of the old operators to complete the same simulations,making it efficient in PRD simulation and assimilation usage.展开更多
Although the first successful numerical weather prediction(NWP)project led by Charney and von Neumann is widely known,little is known by the international community about the development of NWP during the 1950s in Chi...Although the first successful numerical weather prediction(NWP)project led by Charney and von Neumann is widely known,little is known by the international community about the development of NWP during the 1950s in China.Here,a detailed historical perspective on the early NWP experiments in China is provided.The leadership in NWP of the late Professor Chen-Chao Koo,a protége of C.G.Rossby at the University of Stockholm during the late 1940s and a key leader of modern meteorology(particularly of atmospheric dynamics and physics)in China during the 1950s−70s,is highlighted.The unique contributions to NWP by Koo and his students,such as the ideas of formulating NWP as an“evolution”problem,in which the past data over multiple time steps are utilized,rather than an initial-value problem,and on the cybernetic aspects of atmospheric processes,i.e.,regarding the motion of the atmosphere at various time scales as an optimal control system,are also emphasized.展开更多
A dynamic numerical prediction model of sea water temperature for limited sea area is used to predict the sea water temperature at the sea area near Fujian. Essential adjustments have been made in accordance with the ...A dynamic numerical prediction model of sea water temperature for limited sea area is used to predict the sea water temperature at the sea area near Fujian. Essential adjustments have been made in accordance with the characteristics of this region. Two Tests have been made. One is in summer (3 d) and the other is in winter (10 d). In the summer test, a typhoon is just passing by and the calculated current field well responds to typhoon. In the winter test, variation tendency of the predicted sea water temperature field agrees with that of the observation basically, the absolute mean error in the whole sea area is 0 .6 ℃. The variation of the sea water temperature is mostly af- fected by entrainment and pumping, which is related to the topography of the strait.展开更多
The dynamic process of the 2008 Wenehuan earthquake is simulated by finite-element method ( FEM), and the results suggest that we may be able to estimate the occurrence time, location, and magnitude of similar earth...The dynamic process of the 2008 Wenehuan earthquake is simulated by finite-element method ( FEM), and the results suggest that we may be able to estimate the occurrence time, location, and magnitude of similar earthquakes in the future. Thus a numerical earthquake prediction (NEP) program is proposed; the reliability of it is dependent on its gradual refinement and the parameters used in the models.展开更多
A mathematical formulation is applied to represent the phenomena in theincremental melting and solidification process (IMSP), and the temperature and electromagneticfields and the depth of steel liquid phase are calcu...A mathematical formulation is applied to represent the phenomena in theincremental melting and solidification process (IMSP), and the temperature and electromagneticfields and the depth of steel liquid phase are calculated by a finite difference technique using thecontrol volume method. The result shows that the predicted values are in good agreement with theobservations. In accordance with the calculated values for different kinds of materials anddifferent size of molds, the technological parameter of the IMS process such as the power supply andthe descending speed rate can be determined.展开更多
Ground motion prediction is important for earthquake early warning systems, because the region's peak ground motion indicates the potential disaster. In order to predict the peak ground motion quickly and pre- cisely...Ground motion prediction is important for earthquake early warning systems, because the region's peak ground motion indicates the potential disaster. In order to predict the peak ground motion quickly and pre- cisely with limited station wave records, we propose a real- time numerical shake prediction and updating method. Our method first predicts the ground motion based on the ground motion prediction equation after P waves detection of several stations, denoted as the initial prediction. In order to correct the prediction error of the initial prediction, an updating scheme based on real-time simulation of wave propagation is designed. Data assimilation technique is incorporated to predict the distribution of seismic wave energy precisely. Radiative transfer theory and Monte Carlo simulation are used for modeling wave propagation in 2-D space, and the peak ground motion is calculated as quickly as possible. Our method has potential to predict shakemap, making the potential disaster be predicted before the real disaster happens. 2008 Ms8.0 Wenchuan earthquake is studied as an example to show the validity of the proposed method.展开更多
基金the National Key Research and Development Program of China(Grant No.2016YFA0600203)the National Natural Science Foundation of China(Grant No.41575100)+1 种基金the Key Research Program of Frontier Sciences,Chinese Academy of Sciences(Grant No.QYZDY-SSW-DQC012)the CMA Special Public Welfare Research Fund(Grant No.GYHY201506002).
文摘A new forecasting system-the System of Multigrid Nonlinear Least-squares Four-dimensional Variational(NLS-4DVar)Data Assimilation for Numerical Weather Prediction(SNAP)-was established by building upon the multigrid NLS-4DVar data assimilation scheme,the operational Gridpoint Statistical Interpolation(GSI)−based data-processing and observation operators,and the widely used Weather Research and Forecasting numerical model.Drawing upon lessons learned from the superiority of the operational GSI analysis system,for its various observation operators and the ability to assimilate multiple-source observations,SNAP adopts GSI-based data-processing and observation operator modules to compute the observation innovations.The multigrid NLS-4DVar assimilation framework is used for the analysis,which can adequately correct errors from large to small scales and accelerate iteration solutions.The analysis variables are model state variables,rather than the control variables adopted in the conventional 4DVar system.Currently,we have achieved the assimilation of conventional observations,and we will continue to improve the assimilation of radar and satellite observations in the future.SNAP was evaluated by case evaluation experiments and one-week cycling assimilation experiments.In the case evaluation experiments,two six-hour time windows were established for assimilation experiments and precipitation forecasts were verified against hourly precipitation observations from more than 2400 national observation sites.This showed that SNAP can absorb observations and improve the initial field,thereby improving the precipitation forecast.In the one-week cycling assimilation experiments,six-hourly assimilation cycles were run in one week.SNAP produced slightly lower forecast RMSEs than the GSI 4DEnVar(Four-dimensional Ensemble Variational)as a whole and the threat scores of precipitation forecasts initialized from the analysis of SNAP were higher than those obtained from the analysis of GSI 4DEnVar.
基金jointly supported by the National Basic Research Program of China (Grant No.2009CB421407)the National Key Technologies R&D Program of China (Grant Nos.2007BAC29B03 and 2006BAC02B04)the National Natural Science Foundation of China (Grant No.40605023)
文摘The potential predictability of climatological mean circulation and the interannual variation of the South China Sea summer monsoon (SCSSM) were investigated using hindcast results from the Institute of Atmospheric Physics Dynamical Seasonal Prediction System (IAP DCP),along with the National Centers for Environmental Prediction (NCEP) reanalysis data from the period of 1980-2000.The large-scale characteristics of the SCSSM monthly and seasonal mean low-level circulation have been well reproduced by IAP DCP,especially for the zonal wind at 850 hPa;furthermore,the hindcast variability also agrees quite well with observations.By introducing the South China Sea summer monsoon index,the potential predictability of IAP DCP for the intensity of the SCSSM has been evaluated.IAP DCP showed skill in predicting the interannual variation of SCSSM intensity.The result is highly encouraging;the correlation between the hindcasted and observed SCSSM Index was 0.58,which passes the 95% significance test.The result for the seasonal mean June-July-August SCSSM Index was better than that for the monthly mean,suggesting that seasonal forecasts are more reliable than monthly forecasts.
文摘The recent progresses in the research and development of (NWP) in China are reviewed in this paper. The most impressive achievements are the development of direct assimilation of satellite irradiances with a 3DVAR (three-dimentional variational) data assimilation system and a non-hydrostatic modei with a semi-Lagrangian semi-implicit scheme. Progresses have also been made in modei physics and modei application to precipitation and environmental forecasts. Some scientific issues of great importance for further development are discussed.
基金Project supported by the National Natural Science Foundation of China (Grant Nos 40575036 and 40325015).Acknowledgement The authors thank Drs Zhang Pei-Qun and Bao Ming very much for their valuable comments on the present paper.
文摘In this paper, an analogue correction method of errors (ACE) based on a complicated atmospheric model is further developed and applied to numerical weather prediction (NWP). The analysis shows that the ACE can effectively reduce model errors by combining the statistical analogue method with the dynamical model together in order that the information of plenty of historical data is utilized in the current complicated NWP model, Furthermore, in the ACE, the differences of the similarities between different historical analogues and the current initial state are considered as the weights for estimating model errors. The results of daily, decad and monthly prediction experiments on a complicated T63 atmospheric model show that the performance of the ACE by correcting model errors based on the estimation of the errors of 4 historical analogue predictions is not only better than that of the scheme of only introducing the correction of the errors of every single analogue prediction, but is also better than that of the T63 model.
基金Supported by National Key Research and Development Program of China(Grant No.2020YFA0710902)National Natural Science Foundation of China(Grant No.12172308).
文摘In this paper,the unsteady flow around a high-speed train is numerically simulated by detached eddy simulation method(DES),and the far-field noise is predicted using the Ffowcs Williams-Hawkings(FW-H)acoustic model.The reliability of the numerical calculation is verified by wind tunnel experiments.The superposition relationship between the far-field radiated noise of the local aerodynamic noise sources of the high-speed train and the whole noise source is analyzed.Since the aerodynamic noise of high-speed trains is derived from its different components,a stepwise calculation method is proposed to predict the aerodynamic noise of high-speed trains.The results show that the local noise sources of high-speed trains and the whole noise source conform to the principle of sound source energy superposition.Using the head,middle and tail cars of the high-speed train as noise sources,different numerical models are established to obtain the far-field radiated noise of each aerodynamic noise source.The far-field total noise of high-speed trains is predicted using sound source superposition.A step-by-step calculation of each local aerodynamic noise source is used to obtain the superimposed value of the far-field noise.This is consistent with the far-field noise of the whole train model’s aerodynamic noise.The averaged sound pressure level of the far-field longitudinal noise measurement points differs by 1.92 dBA.The step-by-step numerical prediction method of aerodynamic noise of high-speed trains can provide a reference for the numerical prediction of aerodynamic noise generated by long marshalling high-speed trains.
文摘The movement of Typhoon Maggie (9903) in June 1999 is one of the rare cases ever seen in the history. At 00U on June 6 Maggie was located at about 70 km to the southwest of Taiwan. When it arrived at the coastal region of Shanwei City (22.8N, 116.5E), it turned suddenly to move southwestward along the southern China coastal line. De June 7 Maggie finally turned to move northward, making landfall to the north of Shangchuan Island. The experimental numerical prediction system on typhoon movement that was designed based on MM5 is proved quite successful for the 48h prediction of Maggie's movement and rainfall. The mean prediction error of typhoon track is 81 km for 0-24 h and 74 km for 24-48 h. The location of typhoon center in the initial field of the model is approximately 100 km away from the actual observations. In order to modify the location of typhoon center, a bogus typhoon was intro- duced into the model and the prediction of typhoon track was improved in 0-24 h time interval. But the prediction error was enlarged in 24-36 h. We also performed a sensitivity experiment of changing the land of southern China into the ocean. It is found that the orientation of South China coastal line and the topography have no obvious effect on the movement of Typhoon Maggie.
基金funded by the Special Scientific Research Project for Public Interest (GYHY201206009)the National Key Technologies Research and Development Program (Grant No. 2012BAC22B02)+2 种基金the National Natural Science Foundation Science Fund for Creative Research Groups (Grant No.41221064)the Special Scientific Research Project for Public Interest (Grant No. GYHY201006013)the National Natural Science Foundation of China (Grant No. 41105070 )
文摘The initial value error and the imperfect numerical model are usually considered as error sources of numerical weather prediction (NWP). By using past multi-time observations and model output, this study proposes a method to estimate imperfect numerical model error. This method can be inversely estimated through expressing the model error as a Lagrange interpolation polynomial, while the coefficients of polyno- mial are determined by past model performance. However, for practical application in the full NWP model, it is necessary to determine the following criteria: (1) the length of past data sufficient for estimation of the model errors, (2) a proper method of estimating the term "model integration with the exact solution" when solving the inverse problem, and (3) the extent to which this scheme is sensitive to the observational errors. In this study, such issues are resolved using a simple linear model, and an advection diffusion model is applied to discuss the sensitivity of the method to an artificial error source. The results indicate that the forecast errors can be largely reduced using the proposed method if the proper length of past data is chosen. To address the three problems, it is determined that (1) a few data limited by the order of the corrector can be used, (2) trapezoidal approximation can be employed to estimate the "term" in this study; however, a more accurate method should be explored for an operational NWP model, and (3) the correction is sensitive to observational error.
基金Project supported by the Special Scientific Research Project for Public Interest(Grant No.GYHY201206009)the Fundamental Research Funds for the Central Universities,China(Grant Nos.lzujbky-2012-13 and lzujbky-2013-11)the National Basic Research Program of China(Grant Nos.2012CB955902 and 2013CB430204)
文摘Model error is one of the key factors restricting the accuracy of numerical weather prediction (NWP). Considering the continuous evolution of the atmosphere, the observed data (ignoring the measurement error) can be viewed as a series of solutions of an accurate model governing the actual atmosphere. Model error is represented as an unknown term in the accurate model, thus NWP can be considered as an inverse problem to uncover the unknown error term. The inverse problem models can absorb long periods of observed data to generate model error correction procedures. They thus resolve the deficiency and faultiness of the NWP schemes employing only the initial-time data. In this study we construct two inverse problem models to estimate and extrapolate the time-varying and spatial-varying model errors in both the historical and forecast periods by using recent observations and analogue phenomena of the atmosphere. Numerical experiment on Burgers' equation has illustrated the substantial forecast improvement using inverse problem algorithms. The proposed inverse problem methods of suppressing NWP errors will be useful in future high accuracy applications of NWP.
基金supported by the Science and Technology Project of State Grid Corporation of China:Key technology for high-resolution and centralized wind power forecasting for deep-offshore wind power base (No. SGSXDK00YJJS2000879)
文摘Numerical Weather Prediction(NWP)is a necessary input for short-term wind power forecasting.Existing NWP models are all based on purely physical models.This requires mainframe computers to perform large-scale numerical calculations and the technical threshold of the assimilation process is high.There is a need to further improve the timeliness and accuracy of the assimilation process.In order to solve the above problems,NWP method based on artificial intelligence is proposed in this paper.It uses a convolutional neural network algorithm and a downscaling model from the global background field to establish a given wind turbine hub height position.We considered the actual data of a wind farm in north China as an example to analyze the calculation example.The results show that the prediction accuracy of the proposed method is equivalent to that of the traditional purely physical model.The prediction accuracy in some months is better than that of the purely physical model,and the calculation efficiency is considerably improved.The validity and advantages of the proposed method are verified from the results,and the traditional NWP method is replaced to a certain extent.
文摘[Objective] The research aimed to analyze explanation effect of the European numerical prediction on temperature. [Method] Based on CMSVM regression method, by using 850 hPa grid point data of the European numerical prediction from 2003 to 2009 and actual data of the maximum and minimum temperatures at 8 automatic stations in Qingyang City, prediction model of the temperature was established, and running effect of the business from 2008 to 2010 was tested and evaluated. [Result] The method had very good guidance role in real-time business running of the temperature prediction. Test and evaluation found that as forecast time prolonged, prediction accuracies of the maximum and minimum temperatures declined. When temperature anomaly was higher (actual temperature was higher than historical mean), prediction accuracy increased. Influence of the European numerical prediction was bigger. [Conclusion] Compared with other methods, operation of the prediction method was convenient, modeling was automatic, running time was short, system was stable, and prediction accuracy was high. It was suitable for implementing of the explanation work for numerical prediction product at meteorological station.
基金supported by the National Key Technology Research and Development Program of the Ministry of Science and Technology of China(grant No.2014BAK03B02)Science for Earthquake Resilience(grant Nos XH16021 and XH16022Y)
文摘In earthquake early warning systems, real-time shake prediction through wave propagation simulation is a promising approach. Compared with traditional methods, it does not suffer from the inaccurate estimation of source parameters. For computation efficiency, wave direction is assumed to propagate on the 2-D surface of the earth in these methods. In fact, since the seismic wave propagates in the 3-D sphere of the earth, the 2-D space modeling of wave direction results in inaccurate wave estimation. In this paper, we propose a 3-D space numerical shake pre- diction method, which simulates the wave propagation in 3-D space using radiative transfer theory, and incorporate data assimilation technique to estimate the distribution of wave energy. 2011 Tohoku earthquake is studied as an example to show the validity of the proposed model. 2-D space model and 3-D space model are compared in this article, and the prediction results show that numerical shake prediction based on 3-D space model can estimate the real-time ground motion precisely, and overprediction is alleviated when using 3-D space model.
文摘In this paper, on the basis of the heat conduction equation without consideration of the advection and turbulence effects, one-dimensional model for describing surface sea temperature ( T1), bottom sea temperature ( Tt ) and the thickness of the upper homogeneous layer ( h ) is developed in terms of the dimensionless temperature θT and depth η and self-simulation function θT - f(η) of vertical temperature profile by means of historical temperature data.The results of trial prediction with our one-dimensional model on T, Th, h , the thickness and gradient of thermocline are satisfactory to some extent.
基金supported by the CAS/CAFEA international partnership Program for creative research teams (No.KZZD-EW-TZ-19)China National Science and Technology Support Program ‘‘Practical Techniques for Earthquake Analysis and Prediction Research’’ 2012BAK19B03-5
文摘Can earthquakes be predicted? How should people overcome the difficulties encountered in the study of earthquake prediction? This issue can take inspiration from the experiences of weather forecast. Although weather forecasting took a period of about half a century to advance from empirical to numerical forecast, it has achieved significant success. A consensus has been reached among the Chinese seismological community that earth- quake prediction must also develop from empirical fore- casting to physical prediction. However, it is seldom mentioned that physical prediction is characterized by quantitatively numerical predictions based on physical laws. This article discusses five key components for numerical earthquake prediction and their current status. We conclude that numerical earthquake prediction should now be put on the planning agenda and its roadmap designed, seismic stations should be deployed and observations made according to the needs of numerical prediction, and theoretical research should be carried out.
基金Project supported by the National Natural Science Foundation of China (No.50205011)
文摘A numerical simulation model for predicting residual stresses which arise during the solidification process of pressed glass bulb panel was developed. The solidification of a molten layer of glass between cooled parallel plates was used to model the mechanics of the buildup of residual stresses in the forming process. A thermorheologically simple thermoviscoelastic model was assumed for the material. The finite element method employed was based on the theory of shells as an assembly of flat elements. This approach calculates residual stresses layer by layer like a truly three-dimensional calculation, which is well suited for thin pressed products of complex shape. An experimental comparison was employed to verify the proposed models and methods.
基金the University of Oklahoma(OU)Supercomputing Center for Education&Research(OSCER).
文摘Many weather radar networks in the world have now provided polarimetric radar data(PRD)that have the potential to improve our understanding of cloud and precipitation microphysics,and numerical weather prediction(NWP).To realize this potential,an accurate and efficient set of polarimetric observation operators are needed to simulate and assimilate the PRD with an NWP model for an accurate analysis of the model state variables.For this purpose,a set of parameterized observation operators are developed to simulate and assimilate polarimetric radar data from NWP model-predicted hydrometeor mixing ratios and number concentrations of rain,snow,hail,and graupel.The polarimetric radar variables are calculated based on the T-matrix calculation of wave scattering and integrations of the scattering weighted by the particle size distribution.The calculated polarimetric variables are then fitted to simple functions of water content and volumeweighted mean diameter of the hydrometeor particle size distribution.The parameterized PRD operators are applied to an ideal case and a real case predicted by the Weather Research and Forecasting(WRF)model to have simulated PRD,which are compared with existing operators and real observations to show their validity and applicability.The new PRD operators use less than one percent of the computing time of the old operators to complete the same simulations,making it efficient in PRD simulation and assimilation usage.
基金the National Natural Science Foundation of China(Grant No.42042011)is appreciated.
文摘Although the first successful numerical weather prediction(NWP)project led by Charney and von Neumann is widely known,little is known by the international community about the development of NWP during the 1950s in China.Here,a detailed historical perspective on the early NWP experiments in China is provided.The leadership in NWP of the late Professor Chen-Chao Koo,a protége of C.G.Rossby at the University of Stockholm during the late 1940s and a key leader of modern meteorology(particularly of atmospheric dynamics and physics)in China during the 1950s−70s,is highlighted.The unique contributions to NWP by Koo and his students,such as the ideas of formulating NWP as an“evolution”problem,in which the past data over multiple time steps are utilized,rather than an initial-value problem,and on the cybernetic aspects of atmospheric processes,i.e.,regarding the motion of the atmosphere at various time scales as an optimal control system,are also emphasized.
基金The project was financially supported by the Natural Science Foundation of Province under contract No. Q99E02 andthe special f
文摘A dynamic numerical prediction model of sea water temperature for limited sea area is used to predict the sea water temperature at the sea area near Fujian. Essential adjustments have been made in accordance with the characteristics of this region. Two Tests have been made. One is in summer (3 d) and the other is in winter (10 d). In the summer test, a typhoon is just passing by and the calculated current field well responds to typhoon. In the winter test, variation tendency of the predicted sea water temperature field agrees with that of the observation basically, the absolute mean error in the whole sea area is 0 .6 ℃. The variation of the sea water temperature is mostly af- fected by entrainment and pumping, which is related to the topography of the strait.
基金supported by the National Natural Science Foundation ofChina(40974020,40074024)National 973 Project of China2008(B425704)State Key Laboratory of Earthguake Dynamics Project(LED2008B02)
文摘The dynamic process of the 2008 Wenehuan earthquake is simulated by finite-element method ( FEM), and the results suggest that we may be able to estimate the occurrence time, location, and magnitude of similar earthquakes in the future. Thus a numerical earthquake prediction (NEP) program is proposed; the reliability of it is dependent on its gradual refinement and the parameters used in the models.
文摘A mathematical formulation is applied to represent the phenomena in theincremental melting and solidification process (IMSP), and the temperature and electromagneticfields and the depth of steel liquid phase are calculated by a finite difference technique using thecontrol volume method. The result shows that the predicted values are in good agreement with theobservations. In accordance with the calculated values for different kinds of materials anddifferent size of molds, the technological parameter of the IMS process such as the power supply andthe descending speed rate can be determined.
基金supported by the National Key Technology Research and Development Program of the Ministry of Science and Technology of China(grant No.2014BAK03B02)Science for Earthquake Resilience(grant Nos XH16021 and XH16022Y)
文摘Ground motion prediction is important for earthquake early warning systems, because the region's peak ground motion indicates the potential disaster. In order to predict the peak ground motion quickly and pre- cisely with limited station wave records, we propose a real- time numerical shake prediction and updating method. Our method first predicts the ground motion based on the ground motion prediction equation after P waves detection of several stations, denoted as the initial prediction. In order to correct the prediction error of the initial prediction, an updating scheme based on real-time simulation of wave propagation is designed. Data assimilation technique is incorporated to predict the distribution of seismic wave energy precisely. Radiative transfer theory and Monte Carlo simulation are used for modeling wave propagation in 2-D space, and the peak ground motion is calculated as quickly as possible. Our method has potential to predict shakemap, making the potential disaster be predicted before the real disaster happens. 2008 Ms8.0 Wenchuan earthquake is studied as an example to show the validity of the proposed method.