This study investigated the regime-dependent predictability using convective-scale ensemble forecasts initialized with different initial condition perturbations in the Yangtze and Huai River basin(YHRB)of East China.T...This study investigated the regime-dependent predictability using convective-scale ensemble forecasts initialized with different initial condition perturbations in the Yangtze and Huai River basin(YHRB)of East China.The scale-dependent error growth(ensemble variability)and associated impact on precipitation forecasts(precipitation uncertainties)were quantitatively explored for 13 warm-season convective events that were categorized in terms of strong forcing and weak forcing.The forecast error growth in the strong-forcing regime shows a stepwise increase with increasing spatial scale,while the error growth shows a larger temporal variability with an afternoon peak appearing at smaller scales under weak forcing.This leads to the dissimilarity of precipitation uncertainty and shows a strong correlation between error growth and precipitation across spatial scales.The lateral boundary condition errors exert a quasi-linear increase on error growth with time at the larger scale,suggesting that the large-scale flow could govern the magnitude of error growth and associated precipitation uncertainties,especially for the strong-forcing regime.Further comparisons between scale-based initial error sensitivity experiments show evident scale interaction including upscale transfer of small-scale errors and downscale cascade of larger-scale errors.Specifically,small-scale errors are found to be more sensitive in the weak-forcing regime than those under strong forcing.Meanwhile,larger-scale initial errors are responsible for the error growth after 4 h and produce the precipitation uncertainties at the meso-β-scale.Consequently,these results can be used to explain underdispersion issues in convective-scale ensemble forecasts and provide feedback for ensemble design over the YHRB.展开更多
以中尺度非静力WRF模式的格点预报结果作为云模式的初值集合,经云模式的多初值雷暴预报及预报结果的集合分析,建立了雷暴云的集合预报方法。将该方法应用于南京周边地区未来一天雷暴天气的特征预报,并利用南京夏季9个雷暴天气的多普勒...以中尺度非静力WRF模式的格点预报结果作为云模式的初值集合,经云模式的多初值雷暴预报及预报结果的集合分析,建立了雷暴云的集合预报方法。将该方法应用于南京周边地区未来一天雷暴天气的特征预报,并利用南京夏季9个雷暴天气的多普勒雷达资料(SCIT,storm cell identification and tracking)进行预报效果的检验。结果表明,雷暴云的集合预报对研究区域内未来一天雷暴强度、分布预报效果较好,尤其对强雷暴的分布有较强的预警预测能力。此外,雷暴持续时间概率密度分布的集合预报产品,在雷暴影响范围概率预报上的应用,提高了雷达对雷暴的预警监测能力。展开更多
Topology optimization of simplified convective heat transfer has been widely studied,but most existing studies are based on the finite element method(FEM);methods based on the finite volume method(FVM)have been less s...Topology optimization of simplified convective heat transfer has been widely studied,but most existing studies are based on the finite element method(FEM);methods based on the finite volume method(FVM)have been less studied.In this paper,a topology optimization method based on FVM was proposed for a simplified convective heat transfer problem.We developed a novel adjoint sensitivity analysis method applicable to FVM,which included adjoint equations,corresponding boundary conditions,and sensitivity analysis equations.Additionally,a program for the proposed topology optimization method was developed in open field operation and manipulation(OpenFOAM)and portable,extensibletoolkit for scientific computation(PETSc).Thus,large-scale topology optimizations could be performed in parallel.Furthermore,numerical examples of the classical two-dimensional(2D)and 3D optimization problems were considered.The results verified the effectiveness and feasibility of the proposed method.The results of large-scale 3D examples show an interesting phenomenon that for the optimized designs with few features,the large-scale topology optimization is still valuable for obtaining more effective structural shapes.展开更多
A long-lived and loosely organized squall line moved rapidly across U¨ru¨mqi, the capital city of Xinjiang Uygur Autonomous Region of China on 26 June 2005, generating hail and strong winds. The squall line ...A long-lived and loosely organized squall line moved rapidly across U¨ru¨mqi, the capital city of Xinjiang Uygur Autonomous Region of China on 26 June 2005, generating hail and strong winds. The squall line was observed by a dual Doppler radar system in a field experiment conducted in 2004 and 2005 by the Chinese Academy of Meteorological Sciences and the local meteorological bureau in northwestern China. The 3D wind fields within the squall line were retrieved through dual Doppler analyses and a variational Doppler radar analysis system （VDRAS）. The formation and structure of the squall line as well as the genesis and evolution of embedded convective cells were investigated. During its life period, the squall line consisted of six storm cells extending about 100 km in length, and produced hail of about 25 mm in diameter and strong surface winds up to 11 m s^-1. Radar observations revealed a broad region of stratiform rain in a meso-β cyclone, with the squall line located to the west of this. Two meso-γ scale vortices were found within the squall line. Compared to typical squall lines in moist regions, such as Guangdong Province and Shanghai, which tend to be around 300–400 km in length, have echo tops of 17–19 km, and produce maximum surface winds of about 25 m s^-1 and temperature variations of about 8-C this squall line system had weaker maximum reflectivity （55 dBZ）, a lower echo top （13 km） and smaller extension （about 100 km）, relatively little stratiform rainfall preceding the convective line, and a similar moving speed and temperature variation at the surface.展开更多
Formulating model uncertainties for a convection-allowing ensemble prediction system(CAEPS)is a much more challenging problem compared to well-utilized approaches in synoptic weather forecasting.A new approach is prop...Formulating model uncertainties for a convection-allowing ensemble prediction system(CAEPS)is a much more challenging problem compared to well-utilized approaches in synoptic weather forecasting.A new approach is proposed and tested through assuming that the model uncertainty should reasonably describe the fast nonlinear error growth of the convection-allowing model,due to the fast developing character and strong nonlinearity of convective events.The Conditional Nonlinear Optimal Perturbation related to Parameters(CNOP-P)is applied in this study.Also,an ensemble approach is adopted to solve the CNOP-P problem.By using five locally developed strong convective events that occurred in pre-rainy season of South China,the most sensitive parameters were detected based on CNOP-P,which resulted in the maximum variations in precipitation.A formulation of model uncertainty is designed by adding stochastic perturbations into these sensitive parameters.Through comparison ensemble experiments by using all the 13 heavy rainfall cases that occurred in the flood season of South China in 2017,the advantages of the CNOP-P-based method are examined and verified by comparing with the well-utilized stochastically perturbed physics tendencies(SPPT)scheme.The results indicate that the CNOP-P-based method has potential in improving the under-dispersive problem of the current CAEPS.展开更多
The characteristics of convective-scale downdrafts in the outer core of tropical cyclones in the lower-and upper-layer vertical wind shear(VWS)are investigated based on two high-resolution idealized numerical experime...The characteristics of convective-scale downdrafts in the outer core of tropical cyclones in the lower-and upper-layer vertical wind shear(VWS)are investigated based on two high-resolution idealized numerical experiments.Four types of outer-core downdrafts,originating from the lower troposphere,the midtroposphere,the upper level,and the tropopause,respectively,are found.The downdrafts originating from the lower and mid troposphere can penetrate down near the surface,and those originating from the tropopause in upper-layer VWS tend to penetrate more downward than in lower-layer VWS.Downdrafts tend to be located in the more upwind portion of the downshear-right quadrant in lower-layer VWS than in upper-layer VWS.The frequency of downdrafts outside and upwind of the parent updraft increases with the increasing downdraft top height.Vertical momentum budgets indicate that downward-oriented buoyancy due to the evaporational cooling of rainwater and precipitation drag mainly contribute to the occurrence of low-level downdrafts,and the midlevel and upper-level downdrafts originate due to precipitation drag and are strengthened by the downward-oriented,buoyancy-induced perturbation pressure gradient.The processes governing the downdrafts from the tropopause are different between the two experiments.More icy-type particles are produced and transported outward at upper levels in the lower-layer shear experiment,resulting in larger downward-oriented buoyancy due to the sublimational cooling of icy-type particles and contributing to the development/maintenance of the downdraft from the tropopause in that experiment.However,the downwardoriented perturbation pressure gradient leads to the development/maintenance of the downdraft from the tropopause in the upper-layer shear experiment.展开更多
The quantitative precipitation forecast(QPF) in very-short range(0-12 hours) has been investigated in this paper by using a convective-scale(3km) GRAPES_Meso model. At first, a latent heat nudging(LHN) scheme to assim...The quantitative precipitation forecast(QPF) in very-short range(0-12 hours) has been investigated in this paper by using a convective-scale(3km) GRAPES_Meso model. At first, a latent heat nudging(LHN) scheme to assimilate the hourly intensified surface precipitation data was set up to enhance the initialization of GRAPES_Meso integration. And then based on the LHN scheme, a convective-scale prediction system was built up in considering the initial "triggering"uncertainties by means of multi-scale initial analysis(MSIA), such as the three-dimensional variational data assimilation(3DVAR), the traditional LHN method(VAR0LHN3), the cycling LHN method(CYCLING), the spatial filtering(SS) and the temporal filtering(DFI) LHN methods. Furthermore, the probability matching(PM) method was used to generate the QPF in very-short range by combining the precipitation forecasts of the five runs. The experiments for one month were carried out to validate the MSIA and PM method for QPF in very-short range.The numerical simulation results showed that:(1) in comparison with the control run, the CYCLING run could generate the smaller-scale initial moist increments and was better for reducing the spin-up time and triggering the convection in a very-short time;(2) the DFI runs could generate the initial analysis fields with relatively larger-scale initial increments and trigger the weaker convections at the beginning time(0-3h) of integration, but enhance them at latter time(6-12h);(3) by combining the five runs with different convection triggering features, the PM method could significantly improve the QPF in very-short range in comparison to any single run. Therefore, the QPF with a small size of combining members proposed here is quite prospective in operation for its lower computation cost and better performance.展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2017YFC1502103)the National Natural Science Foundation of China(Grant Nos.41430427 and 41705035)+1 种基金the China Scholarship Councilthe Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX17_0876)。
文摘This study investigated the regime-dependent predictability using convective-scale ensemble forecasts initialized with different initial condition perturbations in the Yangtze and Huai River basin(YHRB)of East China.The scale-dependent error growth(ensemble variability)and associated impact on precipitation forecasts(precipitation uncertainties)were quantitatively explored for 13 warm-season convective events that were categorized in terms of strong forcing and weak forcing.The forecast error growth in the strong-forcing regime shows a stepwise increase with increasing spatial scale,while the error growth shows a larger temporal variability with an afternoon peak appearing at smaller scales under weak forcing.This leads to the dissimilarity of precipitation uncertainty and shows a strong correlation between error growth and precipitation across spatial scales.The lateral boundary condition errors exert a quasi-linear increase on error growth with time at the larger scale,suggesting that the large-scale flow could govern the magnitude of error growth and associated precipitation uncertainties,especially for the strong-forcing regime.Further comparisons between scale-based initial error sensitivity experiments show evident scale interaction including upscale transfer of small-scale errors and downscale cascade of larger-scale errors.Specifically,small-scale errors are found to be more sensitive in the weak-forcing regime than those under strong forcing.Meanwhile,larger-scale initial errors are responsible for the error growth after 4 h and produce the precipitation uncertainties at the meso-β-scale.Consequently,these results can be used to explain underdispersion issues in convective-scale ensemble forecasts and provide feedback for ensemble design over the YHRB.
文摘以中尺度非静力WRF模式的格点预报结果作为云模式的初值集合,经云模式的多初值雷暴预报及预报结果的集合分析,建立了雷暴云的集合预报方法。将该方法应用于南京周边地区未来一天雷暴天气的特征预报,并利用南京夏季9个雷暴天气的多普勒雷达资料(SCIT,storm cell identification and tracking)进行预报效果的检验。结果表明,雷暴云的集合预报对研究区域内未来一天雷暴强度、分布预报效果较好,尤其对强雷暴的分布有较强的预警预测能力。此外,雷暴持续时间概率密度分布的集合预报产品,在雷暴影响范围概率预报上的应用,提高了雷达对雷暴的预警监测能力。
基金supported by the Aeronautical Science Foundation of China(Grant No.2020Z009063001)the Fundamental Research Funds for the Central Universities(Grant No.DUT22GF303)。
文摘Topology optimization of simplified convective heat transfer has been widely studied,but most existing studies are based on the finite element method(FEM);methods based on the finite volume method(FVM)have been less studied.In this paper,a topology optimization method based on FVM was proposed for a simplified convective heat transfer problem.We developed a novel adjoint sensitivity analysis method applicable to FVM,which included adjoint equations,corresponding boundary conditions,and sensitivity analysis equations.Additionally,a program for the proposed topology optimization method was developed in open field operation and manipulation(OpenFOAM)and portable,extensibletoolkit for scientific computation(PETSc).Thus,large-scale topology optimizations could be performed in parallel.Furthermore,numerical examples of the classical two-dimensional(2D)and 3D optimization problems were considered.The results verified the effectiveness and feasibility of the proposed method.The results of large-scale 3D examples show an interesting phenomenon that for the optimized designs with few features,the large-scale topology optimization is still valuable for obtaining more effective structural shapes.
基金funded by the Na-tional Natural Science Foundation of China (Grant No.40375008)
文摘A long-lived and loosely organized squall line moved rapidly across U¨ru¨mqi, the capital city of Xinjiang Uygur Autonomous Region of China on 26 June 2005, generating hail and strong winds. The squall line was observed by a dual Doppler radar system in a field experiment conducted in 2004 and 2005 by the Chinese Academy of Meteorological Sciences and the local meteorological bureau in northwestern China. The 3D wind fields within the squall line were retrieved through dual Doppler analyses and a variational Doppler radar analysis system （VDRAS）. The formation and structure of the squall line as well as the genesis and evolution of embedded convective cells were investigated. During its life period, the squall line consisted of six storm cells extending about 100 km in length, and produced hail of about 25 mm in diameter and strong surface winds up to 11 m s^-1. Radar observations revealed a broad region of stratiform rain in a meso-β cyclone, with the squall line located to the west of this. Two meso-γ scale vortices were found within the squall line. Compared to typical squall lines in moist regions, such as Guangdong Province and Shanghai, which tend to be around 300–400 km in length, have echo tops of 17–19 km, and produce maximum surface winds of about 25 m s^-1 and temperature variations of about 8-C this squall line system had weaker maximum reflectivity （55 dBZ）, a lower echo top （13 km） and smaller extension （about 100 km）, relatively little stratiform rainfall preceding the convective line, and a similar moving speed and temperature variation at the surface.
文摘Formulating model uncertainties for a convection-allowing ensemble prediction system(CAEPS)is a much more challenging problem compared to well-utilized approaches in synoptic weather forecasting.A new approach is proposed and tested through assuming that the model uncertainty should reasonably describe the fast nonlinear error growth of the convection-allowing model,due to the fast developing character and strong nonlinearity of convective events.The Conditional Nonlinear Optimal Perturbation related to Parameters(CNOP-P)is applied in this study.Also,an ensemble approach is adopted to solve the CNOP-P problem.By using five locally developed strong convective events that occurred in pre-rainy season of South China,the most sensitive parameters were detected based on CNOP-P,which resulted in the maximum variations in precipitation.A formulation of model uncertainty is designed by adding stochastic perturbations into these sensitive parameters.Through comparison ensemble experiments by using all the 13 heavy rainfall cases that occurred in the flood season of South China in 2017,the advantages of the CNOP-P-based method are examined and verified by comparing with the well-utilized stochastically perturbed physics tendencies(SPPT)scheme.The results indicate that the CNOP-P-based method has potential in improving the under-dispersive problem of the current CAEPS.
基金jointly supported by the National Key Research and Development Program of China(Grant No.2017YFC1501601)the Key Program of the Ministry of Science and Technology of China(Grant No.2017YFE0107700)the National Natural Science Foundation of China(Grant Nos.41875054,41730961,41730960,and 41775065)
文摘The characteristics of convective-scale downdrafts in the outer core of tropical cyclones in the lower-and upper-layer vertical wind shear(VWS)are investigated based on two high-resolution idealized numerical experiments.Four types of outer-core downdrafts,originating from the lower troposphere,the midtroposphere,the upper level,and the tropopause,respectively,are found.The downdrafts originating from the lower and mid troposphere can penetrate down near the surface,and those originating from the tropopause in upper-layer VWS tend to penetrate more downward than in lower-layer VWS.Downdrafts tend to be located in the more upwind portion of the downshear-right quadrant in lower-layer VWS than in upper-layer VWS.The frequency of downdrafts outside and upwind of the parent updraft increases with the increasing downdraft top height.Vertical momentum budgets indicate that downward-oriented buoyancy due to the evaporational cooling of rainwater and precipitation drag mainly contribute to the occurrence of low-level downdrafts,and the midlevel and upper-level downdrafts originate due to precipitation drag and are strengthened by the downward-oriented,buoyancy-induced perturbation pressure gradient.The processes governing the downdrafts from the tropopause are different between the two experiments.More icy-type particles are produced and transported outward at upper levels in the lower-layer shear experiment,resulting in larger downward-oriented buoyancy due to the sublimational cooling of icy-type particles and contributing to the development/maintenance of the downdraft from the tropopause in that experiment.However,the downwardoriented perturbation pressure gradient leads to the development/maintenance of the downdraft from the tropopause in the upper-layer shear experiment.
基金National(Key)Basic Research and Development(973)Program of China(2013CB430106)the National Natural Science Foundation of China(41375108)
文摘The quantitative precipitation forecast(QPF) in very-short range(0-12 hours) has been investigated in this paper by using a convective-scale(3km) GRAPES_Meso model. At first, a latent heat nudging(LHN) scheme to assimilate the hourly intensified surface precipitation data was set up to enhance the initialization of GRAPES_Meso integration. And then based on the LHN scheme, a convective-scale prediction system was built up in considering the initial "triggering"uncertainties by means of multi-scale initial analysis(MSIA), such as the three-dimensional variational data assimilation(3DVAR), the traditional LHN method(VAR0LHN3), the cycling LHN method(CYCLING), the spatial filtering(SS) and the temporal filtering(DFI) LHN methods. Furthermore, the probability matching(PM) method was used to generate the QPF in very-short range by combining the precipitation forecasts of the five runs. The experiments for one month were carried out to validate the MSIA and PM method for QPF in very-short range.The numerical simulation results showed that:(1) in comparison with the control run, the CYCLING run could generate the smaller-scale initial moist increments and was better for reducing the spin-up time and triggering the convection in a very-short time;(2) the DFI runs could generate the initial analysis fields with relatively larger-scale initial increments and trigger the weaker convections at the beginning time(0-3h) of integration, but enhance them at latter time(6-12h);(3) by combining the five runs with different convection triggering features, the PM method could significantly improve the QPF in very-short range in comparison to any single run. Therefore, the QPF with a small size of combining members proposed here is quite prospective in operation for its lower computation cost and better performance.
