After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve we...After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve weather observations,quantification, forecasting, and warnings. The weather radar networks in China and other countries are also being upgraded with dual-polarization capability. Now, with radar polarimetry technology having matured, and PRD available both nationally and globally, it is important to understand the current status and future challenges and opportunities. The potential impact of PRD has been limited by their oftentimes subjective and empirical use. More importantly, the community has not begun to regularly derive from PRD the state parameters, such as water mixing ratios and number concentrations, used in numerical weather prediction(NWP) models.In this review, we summarize the current status of weather radar polarimetry, discuss the issues and limitations of PRD usage, and explore potential approaches to more efficiently use PRD for quantitative precipitation estimation and forecasting based on statistical retrieval with physical constraints where prior information is used and observation error is included. This approach aligns the observation-based retrievals favored by the radar meteorology community with the model-based analysis of the NWP community. We also examine the challenges and opportunities of polarimetric phased array radar research and development for future weather observation.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
Accurate operational solar irradiance forecasts are crucial for better decision making by solar energy system operators due to the variability of resource and energy demand.Although numerical weather prediction(NWP)mo...Accurate operational solar irradiance forecasts are crucial for better decision making by solar energy system operators due to the variability of resource and energy demand.Although numerical weather prediction(NWP)models can forecast solar radiation variables,they often have significant errors,particularly in the direct normal irradiance(DNI),which is especially affected by the type and concentration of aerosols and clouds.This paper presents a method based on artificial neural networks(ANN)for generating operational DNI forecasts using weather and aerosol forecasts from the European Center for Medium-range Weather Forecasts(ECMWF)and the Copernicus Atmospheric Monitoring Service(CAMS),respectively.Two ANN models were designed:one uses as input the predicted weather and aerosol variables for a given instant,while the other uses a period of the improved DNI forecasts before the forecasted instant.The models were developed using observations for the location of´Evora,Portugal,resulting in 10 min DNI forecasts that for day 1 of forecast horizon showed an improvement over the downscaled original forecasts regarding R2,MAE and RMSE of 0.0646,21.1 W/m^(2)and 27.9 W/m^(2),respectively.The model was also evaluated for different timesteps and locations in southern Portugal,providing good agreement with experimental data.展开更多
It is not only meteorological problems for the medium-range numerical weather prediction (NWP) research to be in operation,but also engineering and technological problems.Here we gener- ally described the results of r...It is not only meteorological problems for the medium-range numerical weather prediction (NWP) research to be in operation,but also engineering and technological problems.Here we gener- ally described the results of research,engineering construction,operation information and testing,in the course of set-up of medium-range NWP operation system in the China National Meteorological Center.展开更多
With the fact that the main operational parameters of the construction process in mechanized tunneling are currently selected based on monitoring data and engineering experience without exploiting the advantages of co...With the fact that the main operational parameters of the construction process in mechanized tunneling are currently selected based on monitoring data and engineering experience without exploiting the advantages of computer methods,the focus of this work is to develop a simulation-based real-time assistant system to support the selection of operational parameters.The choice of an appropriate set of these parameters(i.e.,the face support pressure,the grouting pressure,and the advance speed)during the operation of tunnel boring machines(TBM)is determined by evaluating different tunneling-induced soil-structure interactions such as the surface settlement,the associated risks on existing structures and the tunnel lining behavior.To evaluate soil-structure behavior,an advanced process-oriented numerical simulation model based on the finite cell method is utilized.To enable the real-time prediction capability of the simulation model for a practical application during the advancement of TBMs,surrogate models based on the Proper Orthogonal Decomposition and Radial Basis Functions(POD-RBF)are adopted.The proposed approach is demonstrated through several synthetic numerical examples inspired by the data of real tunnel projects.The developed methods are integrated into a user-friendly application called SMART to serve as a support platform for tunnel engineers at construction sites.Corresponding to each user adjustment of the input parameters,i.e.,each TBM driving scenario,approximately two million outputs of soil-structure interactions are quickly predicted and visualized in seconds,which can provide the site engineers with a rough estimation of the impacts of the chosen scenario on structural responses of the tunnel and above ground structures.展开更多
Numerical weather prediction (NWP) has become one of the most important means for weather fore-casts in the world. It also mirrors a nation's comprehensive strength in meteorology. In 2000, China Meteorological Ad...Numerical weather prediction (NWP) has become one of the most important means for weather fore-casts in the world. It also mirrors a nation's comprehensive strength in meteorology. In 2000, China Meteorological Administration (CMA) established the National Innovative Base for Meteorological Numerical Prediction in the Chinese Academy of Meteorological Sciences (CAMS), to work on developing a new generation of the national operational NWP system――Global/Regional Assimilation and PrEdiction System (GRAPES), to enhance meteorological services in China in the new century. In recent years, the GRAPES has witnessed a fast development. The GRAPES has been set up as an integration of the model framework, data assimilation, regional and global NWP system, which can be commonly used for both operation and research. In this paper, a brief review is made for illustrating the GRAPES system, including the advanced designs of the GRAPES, its diverse applications in multifields, and efficiencies of the regional and global GRAPES in operational applications based on hindcast results.展开更多
根据超临界二氧化碳(supercritical carbon dioxide,SCO_(2))的物性特点,调用美国国家标准技术研究所(national institute of standards and technology,NIST)发布的二氧化碳物性参数,开发了SCO_(2)离心压缩机一维设计及性能预测的程序...根据超临界二氧化碳(supercritical carbon dioxide,SCO_(2))的物性特点,调用美国国家标准技术研究所(national institute of standards and technology,NIST)发布的二氧化碳物性参数,开发了SCO_(2)离心压缩机一维设计及性能预测的程序。利用该程序完成了-10 MW SCO_(2)布雷顿循环发电系统中的分流压缩机气动设计以及不同转速下的性能预测,并结合数值计算与流场分析,结果表明:在设计转速下,一维预测结果与三维数值模拟所得的压气机性能结果在小流量区域变化趋势与数值大小吻合较好,但是在堵塞工况点附近两者存在一定的偏差。在其他转速下,一维预测结果与三维数值模拟所得的压气机性能结果吻合较好,表明该一维性能预测能较好预测SCO_(2)离心压缩机的变工况运行特性。展开更多
尝试利用卫星遥感高分辨率海表温度资料GHRSST(Group for High Resolution Sea Surface Temperature)与海表温度(sea surface temperature,SST)数值预报产品之间的误差,建立一种南海SST模式预报订正方法。首先,利用南海的Argo浮标上层...尝试利用卫星遥感高分辨率海表温度资料GHRSST(Group for High Resolution Sea Surface Temperature)与海表温度(sea surface temperature,SST)数值预报产品之间的误差,建立一种南海SST模式预报订正方法。首先,利用南海的Argo浮标上层海温数据对GHRSST海温数据进行验证,结果表明两者之间均方根误差约为0.3℃,相关系数为0.98,GHRSST海温数据可用于南海业务化数值预报SST的订正。预报订正后的SST与Argo浮标海温数据相比,24h、48h和72h的均方根误差均由0.8℃左右下降到0.5℃以内。与GHRSST海温数据相比,南海北部海域(110°E—121°E,13°N—23°N)订正后的24h、48h和72h的SST预报空间误差均显著减小,在冷空气影响南海期间或中尺度涡存在的过程中,SST预报订正效果也较为显著。因此,该方法可考虑在南海业务化SST数值预报系统中应用。展开更多
基金supported by the NOAA (Grant Nos. NA16AOR4320115 and NA11OAR4320072)NSF (Grant No. AGS-1341878)
文摘After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve weather observations,quantification, forecasting, and warnings. The weather radar networks in China and other countries are also being upgraded with dual-polarization capability. Now, with radar polarimetry technology having matured, and PRD available both nationally and globally, it is important to understand the current status and future challenges and opportunities. The potential impact of PRD has been limited by their oftentimes subjective and empirical use. More importantly, the community has not begun to regularly derive from PRD the state parameters, such as water mixing ratios and number concentrations, used in numerical weather prediction(NWP) models.In this review, we summarize the current status of weather radar polarimetry, discuss the issues and limitations of PRD usage, and explore potential approaches to more efficiently use PRD for quantitative precipitation estimation and forecasting based on statistical retrieval with physical constraints where prior information is used and observation error is included. This approach aligns the observation-based retrievals favored by the radar meteorology community with the model-based analysis of the NWP community. We also examine the challenges and opportunities of polarimetric phased array radar research and development for future weather observation.
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funded by National funds through FCT-Fundaçäao para a Ciência e Tecnologia,I.P.(projects UIDB/04683/2020 and UIDP/04683/2020)support of FCT-Fundaçäao para a Ciência e Tecnologia through the grant with reference SFRH/BD/145378/2019.
文摘Accurate operational solar irradiance forecasts are crucial for better decision making by solar energy system operators due to the variability of resource and energy demand.Although numerical weather prediction(NWP)models can forecast solar radiation variables,they often have significant errors,particularly in the direct normal irradiance(DNI),which is especially affected by the type and concentration of aerosols and clouds.This paper presents a method based on artificial neural networks(ANN)for generating operational DNI forecasts using weather and aerosol forecasts from the European Center for Medium-range Weather Forecasts(ECMWF)and the Copernicus Atmospheric Monitoring Service(CAMS),respectively.Two ANN models were designed:one uses as input the predicted weather and aerosol variables for a given instant,while the other uses a period of the improved DNI forecasts before the forecasted instant.The models were developed using observations for the location of´Evora,Portugal,resulting in 10 min DNI forecasts that for day 1 of forecast horizon showed an improvement over the downscaled original forecasts regarding R2,MAE and RMSE of 0.0646,21.1 W/m^(2)and 27.9 W/m^(2),respectively.The model was also evaluated for different timesteps and locations in southern Portugal,providing good agreement with experimental data.
文摘It is not only meteorological problems for the medium-range numerical weather prediction (NWP) research to be in operation,but also engineering and technological problems.Here we gener- ally described the results of research,engineering construction,operation information and testing,in the course of set-up of medium-range NWP operation system in the China National Meteorological Center.
基金Financial support was provided by German Science Foundation(DFG)in the framework of subprojects C1&T2 of Collaborative Research Center SFB 837"Interaction Modeling in Mechanized Tunneling"(Project No.77309832)。
文摘With the fact that the main operational parameters of the construction process in mechanized tunneling are currently selected based on monitoring data and engineering experience without exploiting the advantages of computer methods,the focus of this work is to develop a simulation-based real-time assistant system to support the selection of operational parameters.The choice of an appropriate set of these parameters(i.e.,the face support pressure,the grouting pressure,and the advance speed)during the operation of tunnel boring machines(TBM)is determined by evaluating different tunneling-induced soil-structure interactions such as the surface settlement,the associated risks on existing structures and the tunnel lining behavior.To evaluate soil-structure behavior,an advanced process-oriented numerical simulation model based on the finite cell method is utilized.To enable the real-time prediction capability of the simulation model for a practical application during the advancement of TBMs,surrogate models based on the Proper Orthogonal Decomposition and Radial Basis Functions(POD-RBF)are adopted.The proposed approach is demonstrated through several synthetic numerical examples inspired by the data of real tunnel projects.The developed methods are integrated into a user-friendly application called SMART to serve as a support platform for tunnel engineers at construction sites.Corresponding to each user adjustment of the input parameters,i.e.,each TBM driving scenario,approximately two million outputs of soil-structure interactions are quickly predicted and visualized in seconds,which can provide the site engineers with a rough estimation of the impacts of the chosen scenario on structural responses of the tunnel and above ground structures.
基金Key Technologies Research & Development Program (Grant No. 2001BA607B)National Key Technology Research and Development Program (Grant No. 2006BAC02B02)National Basic Research Program of China (Grant No. 2004CB418300)
文摘Numerical weather prediction (NWP) has become one of the most important means for weather fore-casts in the world. It also mirrors a nation's comprehensive strength in meteorology. In 2000, China Meteorological Administration (CMA) established the National Innovative Base for Meteorological Numerical Prediction in the Chinese Academy of Meteorological Sciences (CAMS), to work on developing a new generation of the national operational NWP system――Global/Regional Assimilation and PrEdiction System (GRAPES), to enhance meteorological services in China in the new century. In recent years, the GRAPES has witnessed a fast development. The GRAPES has been set up as an integration of the model framework, data assimilation, regional and global NWP system, which can be commonly used for both operation and research. In this paper, a brief review is made for illustrating the GRAPES system, including the advanced designs of the GRAPES, its diverse applications in multifields, and efficiencies of the regional and global GRAPES in operational applications based on hindcast results.
文摘根据超临界二氧化碳(supercritical carbon dioxide,SCO_(2))的物性特点,调用美国国家标准技术研究所(national institute of standards and technology,NIST)发布的二氧化碳物性参数,开发了SCO_(2)离心压缩机一维设计及性能预测的程序。利用该程序完成了-10 MW SCO_(2)布雷顿循环发电系统中的分流压缩机气动设计以及不同转速下的性能预测,并结合数值计算与流场分析,结果表明:在设计转速下,一维预测结果与三维数值模拟所得的压气机性能结果在小流量区域变化趋势与数值大小吻合较好,但是在堵塞工况点附近两者存在一定的偏差。在其他转速下,一维预测结果与三维数值模拟所得的压气机性能结果吻合较好,表明该一维性能预测能较好预测SCO_(2)离心压缩机的变工况运行特性。
文摘尝试利用卫星遥感高分辨率海表温度资料GHRSST(Group for High Resolution Sea Surface Temperature)与海表温度(sea surface temperature,SST)数值预报产品之间的误差,建立一种南海SST模式预报订正方法。首先,利用南海的Argo浮标上层海温数据对GHRSST海温数据进行验证,结果表明两者之间均方根误差约为0.3℃,相关系数为0.98,GHRSST海温数据可用于南海业务化数值预报SST的订正。预报订正后的SST与Argo浮标海温数据相比,24h、48h和72h的均方根误差均由0.8℃左右下降到0.5℃以内。与GHRSST海温数据相比,南海北部海域(110°E—121°E,13°N—23°N)订正后的24h、48h和72h的SST预报空间误差均显著减小,在冷空气影响南海期间或中尺度涡存在的过程中,SST预报订正效果也较为显著。因此,该方法可考虑在南海业务化SST数值预报系统中应用。
