Numerical weather prediction(NWP) is a core technology in weather forecast and disaster mitigation. China’s NWP research and operational applications have been attached great importance by the meteorological communit...Numerical weather prediction(NWP) is a core technology in weather forecast and disaster mitigation. China’s NWP research and operational applications have been attached great importance by the meteorological community.Fundamental achievements have been made in the theories, methods, and NWP model development in China, which are of certain international impacts. In this paper, the scientific and technological progress of NWP in China since1949 is summarized. The current status and recent progress of the domestically developed NWP system-GRAPES(Global/Regional Assimilation and Pr Ediction System) are presented. Through independent research and development in the past 10 years, the operational GRAPES system has been established, which includes both regional and global deterministic and ensemble prediction models, with resolutions of 3-10 km for regional and 25-50 km for global forecasts. Major improvements include establishment of a new non-hydrostatic dynamic core, setup of four-dimensional variational data assimilation, and development of associated satellite application. As members of the GRAPES system, prediction models for atmospheric chemistry and air pollution, tropical cyclones, and ocean waves have also been developed and put into operational use. The GRAPES system has been an important milestone in NWP science and technology in China.展开更多
Based on the atmospheric self_memorization principle, a complex memory function was introduced and the spectral form of atmospheric self_memorial equation was derived. Setting up and solving the equation constitute a ...Based on the atmospheric self_memorization principle, a complex memory function was introduced and the spectral form of atmospheric self_memorial equation was derived. Setting up and solving the equation constitute a new approach of the numerical weather prediction. Using the spectral model T42L9 as a dynamic kernel, a global self_memorial T42 model (SMT42) was established, with which twelve cases of 30_d integration experiments were carried out. Compared with the T42L9, the SMT42 is much better in 500 hPa forecast not only for daily circulation but also for monthly mean circulation. The anomaly correlation coefficient (ACC) of forecast for monthly mean circulation has been improved to 0.42, increased by 0.05, and the root_mean_square error (RMSE) has been reduced from 6.09 to 4.03 dagpm.展开更多
Each physical process in a numerical weather prediction(NWP)system may have many different parameterization schemes.Early studies have shown that the performance of different physical parameterization schemes varies w...Each physical process in a numerical weather prediction(NWP)system may have many different parameterization schemes.Early studies have shown that the performance of different physical parameterization schemes varies with the weather situation to be simulated.Thus,it is necessary to select a suitable combination of physical parameterization schemes according to the variation of weather systems.However,it is rather difficult to identify an optimal combination among millions of possible parameterization scheme combinations.This study applied a simple genetic algorithm(SGA)to optimizing the combination of parameterization schemes in NWP models for typhoon forecasting.The feasibility of SGA was verified with the simulation of Typhoon Mujigae(2015)by using the Weather Research and Forecasting(WRF)model and Typhoon Higos(2020)by using the Coupled Ocean–Atmosphere–Wave–Sediment Transport(COAWST)modeling system.The results show that SGA can efficiently obtain the optimal combination of schemes.For Typhoon Mujigae(2015),the optimal combination can be found from the 1,304,576 possible combinations by running only 488 trials.Similar results can be obtained for Typhoon Higos(2020).Compared to the default combination proposed by the COAWST model system,the optimal combination scheme significantly improves the simulation of typhoon track and intensity.This study provides a feasible way to search for the optimal combinations of physical parameterization schemes in WRF and COAWST for more accurate typhoon simulation.This can help provide references for future development of NWP models,and for analyzing the coordination and adaptability of different physical process parameterization schemes under specific weather backgrounds.展开更多
Due to various technical issues,existing numerical weather prediction(NWP)models often perform poorly at forecasting rainfall in the first several hours.To correct the bias of an NWP model and improve the accuracy of ...Due to various technical issues,existing numerical weather prediction(NWP)models often perform poorly at forecasting rainfall in the first several hours.To correct the bias of an NWP model and improve the accuracy of short-range precipitation forecasting,we propose a deep learning-based approach called UNet Mask,which combines NWP forecasts with the output of a convolutional neural network called UNet.The UNet Mask involves training the UNet on historical data from the NWP model and gridded rainfall observations for 6-hour precipitation forecasting.The overlap of the UNet output and the NWP forecasts at the same rainfall threshold yields a mask.The UNet Mask blends the UNet output and the NWP forecasts by taking the maximum between them and passing through the mask,which provides the corrected 6-hour rainfall forecasts.We evaluated UNet Mask on a test set and in real-time verification.The results showed that UNet Mask outperforms the NWP model in 6-hour precipitation prediction by reducing the FAR and improving CSI scores.Sensitivity tests also showed that different small rainfall thresholds applied to the UNet and the NWP model have different effects on UNet Mask's forecast performance.This study shows that UNet Mask is a promising approach for improving rainfall forecasting of NWP models.展开更多
The Experiment on Typhoon Intensity Change in Coastal Area(EXOTICCA) was proposed by the China Meteorological Administration(CMA) and Hong Kong Observatory(HKO) and endorsed by the ESCAP/WMO Typhoon Committee(TC). The...The Experiment on Typhoon Intensity Change in Coastal Area(EXOTICCA) was proposed by the China Meteorological Administration(CMA) and Hong Kong Observatory(HKO) and endorsed by the ESCAP/WMO Typhoon Committee(TC). The major goals and objectives of the EXOTICCA are: 1) to conduct the field campaigns on the intensity and structural characteristics of the target offshore and landfall tropical cyclones by employing integrated and novel observation techniques, and 2) to conduct demonstration research on the utilization of the synergized field observation data with the aim of deepening the understanding of the mechanism of structure and intensity changes, to improve the relevant capability of operational analysis, numerical weather prediction(NWP) models forecast, reliable storm surge and flooding and associated risk assessment. The Organizational structure and implementation schedule etc. are also introduced in this paper.展开更多
Under the traditional framework of fluid dynamics,the problem of the numerical weather prediction is often expressed as the deterministic initial value problem of the classical Newtonian mechanics.The atmosphere is.ho...Under the traditional framework of fluid dynamics,the problem of the numerical weather prediction is often expressed as the deterministic initial value problem of the classical Newtonian mechanics.The atmosphere is.however,a many-body system,the methodology by which the system with two bodies could be precisely solved would cause bigger errors and problems when handling the many-body system by it.A kind of technique to incorporate “the irreversible thermodynamic operators” into the numerical weather prediction models is.therefore,suggesting in this paper,to control the evolutionary direction of the many-body system according to the constraining way of the second law of thermodynamics,and thus the forecasting accuracy of the numerical weather prediction has been noticeably improved.For example,in the MM4 the averaged relative root mean square error of the fields of the temperature,humidity,height and whole wind velocity has decreased by about 13%,among which the averaged error of the 48 h forecasts has decreased by more than 20%.Since the technique to introduce the irreversable thermodynamic operator suggested in this paper is based on the physical law that describes the dissipativity and does not come from the computational consideration only.it is thus named as the physical dissipative technique.In view of the universality of the principle incorporating the irreversible thermodynamics operators suggested in this paper for the fluid dynamics and atmospheric numerical models,the applications and generalization of this incorporating technique would produce a great impact on the field of geophysical fluid dynamics.展开更多
With increasing resolution in numerical weather prediction （NWP） models, the model topography can be described with finer resolution and includes steeper slopes. Consequently, negative effects of the traditional ter...With increasing resolution in numerical weather prediction （NWP） models, the model topography can be described with finer resolution and includes steeper slopes. Consequently, negative effects of the traditional terrain-following vertical coordinate on high-resolution numerical simulations become more distinct due to larger errors in the pressure gradient force （PGF） calculation and associated distortions of the gravity wave along the coordinate surface. A series of numerical experiments have been conducted in this study, including idealized test cases of gravity wave simulation over a complex mountain, error analysis of the PGF estimation over a real topography, and a suite of real-data test cases. The GRAPES-Meso model is utilized with four different coordinates, i.e., the traditional terrain-following vertical coordinate proposed by Gal-Chen and Somerville （hereinafter referred to as the Gal.C.S coordinate）, the one-scale smoothed level （SLEVE1）, the two-scale smoothed level （SLEVE2）, and the COSINE （COS） coordinates. The results of the gravity wave simulation indicate that the GRAPES-Meso model generally can reproduce the mountain-induced gravity waves, which are consistent with the analytic solution. However, the shapes, vertical structures, and intensities Of the waves are better simulated with the SLEVE2 coordinate than with the other three coordinates. The model with the COS coordinate also performs well, except at lower levels where it is not as effective as the SLEVE2 coordinate in suppressing the PGF errors. In contrast, the gravity waves simulated in both the Gal.C.S and SLEVE1 coordinates are relatively distorted. The estimated PGF errors in a rest atmosphere over the real complex topography are much smaller （even disappear at the middle and upper levels） in the GRAPES-Meso model using the SLEVE2 and COS coordinates than those using the Gal.C.S and SLEVE1 coordinates. The results of the real-data test cases conducted over a one-month period suggest that the three modified 展开更多
In an effort to assess the impact of the individual component of meteorological observations （ground-based CPS precipitable water vapor, automatic and conventional meteorological observations） on the torrential rain...In an effort to assess the impact of the individual component of meteorological observations （ground-based CPS precipitable water vapor, automatic and conventional meteorological observations） on the torrential rain event in 4-5 July 2000 in Beijing （with the 24-h accumulated precipitation reaching 240 mm）, 24-h observation system experiments are conducted numerically by using the MM5/WRF 3DVAR system and the nonhydrostatic MM5 model. Results indicate that, because the non-conventional GPS observations are directly assimilated into the initial analyses by 3DVAR system, better initial fields and 24-h simulation for the severe precipitation event are achieved than those under the MM5/Litter_R objective analysis scheme. Further analysis also shows that the individual component of meteorological observation network plays their special positive role in the improvement of initial field analysis and forecasting skills. 3DVAR scheme with or without radiosonde and pilot observation has the most significant influence on numerical simulation, and automatic and conventional surface meteorological observations rank second. After acquiring the supplement information from the other meteorological observations, the ground-based GPS precipitable water vapor data can more obviously reflect initial field assimilation and precipitation forecast. By incorporating the groundbased CPS precipitable water vapor data into the 3DVAR analyses at the initial time, the threat scores （TS） with thresholds of 1, 5, 10, and 20 mm are increased by 1%-8% for 6- and 24-h accumulated precipitation observations, respectively. This work gives one helpful example that assesses the impact of individual component of the existing meteorological observation network on the high influence weather event using 3DVAR numerical system.展开更多
基金Supported by the National Key Research and Development Program of China(2017YFC1501900)Middle-and Long-term Development Strategic Research Project of the Chinese Academy of Engineering(2019-ZCQ-06)。
文摘Numerical weather prediction(NWP) is a core technology in weather forecast and disaster mitigation. China’s NWP research and operational applications have been attached great importance by the meteorological community.Fundamental achievements have been made in the theories, methods, and NWP model development in China, which are of certain international impacts. In this paper, the scientific and technological progress of NWP in China since1949 is summarized. The current status and recent progress of the domestically developed NWP system-GRAPES(Global/Regional Assimilation and Pr Ediction System) are presented. Through independent research and development in the past 10 years, the operational GRAPES system has been established, which includes both regional and global deterministic and ensemble prediction models, with resolutions of 3-10 km for regional and 25-50 km for global forecasts. Major improvements include establishment of a new non-hydrostatic dynamic core, setup of four-dimensional variational data assimilation, and development of associated satellite application. As members of the GRAPES system, prediction models for atmospheric chemistry and air pollution, tropical cyclones, and ocean waves have also been developed and put into operational use. The GRAPES system has been an important milestone in NWP science and technology in China.
文摘Based on the atmospheric self_memorization principle, a complex memory function was introduced and the spectral form of atmospheric self_memorial equation was derived. Setting up and solving the equation constitute a new approach of the numerical weather prediction. Using the spectral model T42L9 as a dynamic kernel, a global self_memorial T42 model (SMT42) was established, with which twelve cases of 30_d integration experiments were carried out. Compared with the T42L9, the SMT42 is much better in 500 hPa forecast not only for daily circulation but also for monthly mean circulation. The anomaly correlation coefficient (ACC) of forecast for monthly mean circulation has been improved to 0.42, increased by 0.05, and the root_mean_square error (RMSE) has been reduced from 6.09 to 4.03 dagpm.
基金Supported by the National Natural Science Foundation of China(42130605)Shenzhen Science and Technology Program(JCYJ20210324131810029)Guangdong Province Introduction of Innovative Research and Development Team Project China(2019ZT08G669)。
文摘Each physical process in a numerical weather prediction(NWP)system may have many different parameterization schemes.Early studies have shown that the performance of different physical parameterization schemes varies with the weather situation to be simulated.Thus,it is necessary to select a suitable combination of physical parameterization schemes according to the variation of weather systems.However,it is rather difficult to identify an optimal combination among millions of possible parameterization scheme combinations.This study applied a simple genetic algorithm(SGA)to optimizing the combination of parameterization schemes in NWP models for typhoon forecasting.The feasibility of SGA was verified with the simulation of Typhoon Mujigae(2015)by using the Weather Research and Forecasting(WRF)model and Typhoon Higos(2020)by using the Coupled Ocean–Atmosphere–Wave–Sediment Transport(COAWST)modeling system.The results show that SGA can efficiently obtain the optimal combination of schemes.For Typhoon Mujigae(2015),the optimal combination can be found from the 1,304,576 possible combinations by running only 488 trials.Similar results can be obtained for Typhoon Higos(2020).Compared to the default combination proposed by the COAWST model system,the optimal combination scheme significantly improves the simulation of typhoon track and intensity.This study provides a feasible way to search for the optimal combinations of physical parameterization schemes in WRF and COAWST for more accurate typhoon simulation.This can help provide references for future development of NWP models,and for analyzing the coordination and adaptability of different physical process parameterization schemes under specific weather backgrounds.
基金jointly supported by the National Natural Science Foundation of China(Grant No.U1811464)the Hydraulic Innovation Project of Science and Technology of Guangdong Province of China(Grant No.2022-01)the Guangzhou Basic and Applied Basic Research Foundation(Grant No.202201011472)。
文摘Due to various technical issues,existing numerical weather prediction(NWP)models often perform poorly at forecasting rainfall in the first several hours.To correct the bias of an NWP model and improve the accuracy of short-range precipitation forecasting,we propose a deep learning-based approach called UNet Mask,which combines NWP forecasts with the output of a convolutional neural network called UNet.The UNet Mask involves training the UNet on historical data from the NWP model and gridded rainfall observations for 6-hour precipitation forecasting.The overlap of the UNet output and the NWP forecasts at the same rainfall threshold yields a mask.The UNet Mask blends the UNet output and the NWP forecasts by taking the maximum between them and passing through the mask,which provides the corrected 6-hour rainfall forecasts.We evaluated UNet Mask on a test set and in real-time verification.The results showed that UNet Mask outperforms the NWP model in 6-hour precipitation prediction by reducing the FAR and improving CSI scores.Sensitivity tests also showed that different small rainfall thresholds applied to the UNet and the NWP model have different effects on UNet Mask's forecast performance.This study shows that UNet Mask is a promising approach for improving rainfall forecasting of NWP models.
文摘The Experiment on Typhoon Intensity Change in Coastal Area(EXOTICCA) was proposed by the China Meteorological Administration(CMA) and Hong Kong Observatory(HKO) and endorsed by the ESCAP/WMO Typhoon Committee(TC). The major goals and objectives of the EXOTICCA are: 1) to conduct the field campaigns on the intensity and structural characteristics of the target offshore and landfall tropical cyclones by employing integrated and novel observation techniques, and 2) to conduct demonstration research on the utilization of the synergized field observation data with the aim of deepening the understanding of the mechanism of structure and intensity changes, to improve the relevant capability of operational analysis, numerical weather prediction(NWP) models forecast, reliable storm surge and flooding and associated risk assessment. The Organizational structure and implementation schedule etc. are also introduced in this paper.
基金Supported by the National Natural Science Foundation of China under Grants 49675268.40075024the National Key Program for Developing Basic Sciences G1998040911.
文摘Under the traditional framework of fluid dynamics,the problem of the numerical weather prediction is often expressed as the deterministic initial value problem of the classical Newtonian mechanics.The atmosphere is.however,a many-body system,the methodology by which the system with two bodies could be precisely solved would cause bigger errors and problems when handling the many-body system by it.A kind of technique to incorporate “the irreversible thermodynamic operators” into the numerical weather prediction models is.therefore,suggesting in this paper,to control the evolutionary direction of the many-body system according to the constraining way of the second law of thermodynamics,and thus the forecasting accuracy of the numerical weather prediction has been noticeably improved.For example,in the MM4 the averaged relative root mean square error of the fields of the temperature,humidity,height and whole wind velocity has decreased by about 13%,among which the averaged error of the 48 h forecasts has decreased by more than 20%.Since the technique to introduce the irreversable thermodynamic operator suggested in this paper is based on the physical law that describes the dissipativity and does not come from the computational consideration only.it is thus named as the physical dissipative technique.In view of the universality of the principle incorporating the irreversible thermodynamics operators suggested in this paper for the fluid dynamics and atmospheric numerical models,the applications and generalization of this incorporating technique would produce a great impact on the field of geophysical fluid dynamics.
文摘晨昏卫星(晨昏轨道极轨气象卫星,也简称晨昏轨道卫星)是指太阳同步近极地轨道卫星中轨道降交点地方时间(Equator Cross Time,ETC)在6:00左右的卫星,观测地方时间总在凌晨和傍晚。在介绍晨昏卫星的基础上,分析了晨昏卫星的平台特征、观测特点和潜在应用。对轨道模拟仿真和多国观测系统试验(observing system experiments,OSE)的分析表明:晨昏卫星同上午卫星和下午卫星共同构成极轨气象卫星业务观测系统,可以每6h提供一次无缝隙的全球大气探测资料,改进NWP的初始场,对南北半球预报和行星尺度的区域预报均有积极的贡献。利用FY-1D卫星观测资料的分析表明:晨昏卫星对气候和环境监测也具有独特的作用。根据现有风云气象卫星的发展规划,还讨论了发展晨昏卫星的可能途径。
基金Supported by the National(Key)Basic Research and Development(973)Program of China(2013CB430106)National Natural Science Foundation of China(41375108)National Science and Technology Support Program of China(2012BAC22B01)
文摘With increasing resolution in numerical weather prediction （NWP） models, the model topography can be described with finer resolution and includes steeper slopes. Consequently, negative effects of the traditional terrain-following vertical coordinate on high-resolution numerical simulations become more distinct due to larger errors in the pressure gradient force （PGF） calculation and associated distortions of the gravity wave along the coordinate surface. A series of numerical experiments have been conducted in this study, including idealized test cases of gravity wave simulation over a complex mountain, error analysis of the PGF estimation over a real topography, and a suite of real-data test cases. The GRAPES-Meso model is utilized with four different coordinates, i.e., the traditional terrain-following vertical coordinate proposed by Gal-Chen and Somerville （hereinafter referred to as the Gal.C.S coordinate）, the one-scale smoothed level （SLEVE1）, the two-scale smoothed level （SLEVE2）, and the COSINE （COS） coordinates. The results of the gravity wave simulation indicate that the GRAPES-Meso model generally can reproduce the mountain-induced gravity waves, which are consistent with the analytic solution. However, the shapes, vertical structures, and intensities Of the waves are better simulated with the SLEVE2 coordinate than with the other three coordinates. The model with the COS coordinate also performs well, except at lower levels where it is not as effective as the SLEVE2 coordinate in suppressing the PGF errors. In contrast, the gravity waves simulated in both the Gal.C.S and SLEVE1 coordinates are relatively distorted. The estimated PGF errors in a rest atmosphere over the real complex topography are much smaller （even disappear at the middle and upper levels） in the GRAPES-Meso model using the SLEVE2 and COS coordinates than those using the Gal.C.S and SLEVE1 coordinates. The results of the real-data test cases conducted over a one-month period suggest that the three modified
基金Supported by project of the Ministry of Science and Technology under Nos.2005DIB3J098,2003DFB00011 and 2002BA904B05,project of the Beijing New Star under No.H013610330119,and projects of Beijing Municipal Science Technology Commission under Nos.H010510120119 and H020620250330,and project of GPS application of Beijing Meteorological Bureau.
文摘In an effort to assess the impact of the individual component of meteorological observations （ground-based CPS precipitable water vapor, automatic and conventional meteorological observations） on the torrential rain event in 4-5 July 2000 in Beijing （with the 24-h accumulated precipitation reaching 240 mm）, 24-h observation system experiments are conducted numerically by using the MM5/WRF 3DVAR system and the nonhydrostatic MM5 model. Results indicate that, because the non-conventional GPS observations are directly assimilated into the initial analyses by 3DVAR system, better initial fields and 24-h simulation for the severe precipitation event are achieved than those under the MM5/Litter_R objective analysis scheme. Further analysis also shows that the individual component of meteorological observation network plays their special positive role in the improvement of initial field analysis and forecasting skills. 3DVAR scheme with or without radiosonde and pilot observation has the most significant influence on numerical simulation, and automatic and conventional surface meteorological observations rank second. After acquiring the supplement information from the other meteorological observations, the ground-based GPS precipitable water vapor data can more obviously reflect initial field assimilation and precipitation forecast. By incorporating the groundbased CPS precipitable water vapor data into the 3DVAR analyses at the initial time, the threat scores （TS） with thresholds of 1, 5, 10, and 20 mm are increased by 1%-8% for 6- and 24-h accumulated precipitation observations, respectively. This work gives one helpful example that assesses the impact of individual component of the existing meteorological observation network on the high influence weather event using 3DVAR numerical system.
