The impact of moist physics on the sensitive areas identified by conditional nonlinear optimal perturbation(CNOP)is examined based on four typical heavy rainfall cases in northern China through performing numerical ex...The impact of moist physics on the sensitive areas identified by conditional nonlinear optimal perturbation(CNOP)is examined based on four typical heavy rainfall cases in northern China through performing numerical experiments with and without moist physics.Results show that the CNOP with moist physics identifies sensitive areas corresponding to both the lower-(850−700 hPa)and upper-level(300−100 hPa)weather systems,while the CNOP without moist physics fails to capture the sensitive areas at lower levels.The reasons for the CNOP peaking at different levels can be explained in both algorithm and physics aspects.Firstly,the gradient of the cost function with respect to initial perturbations peaks at the upper level without moist physics which results in the upper-level peak of the CNOP,while it peaks at both the upper and lower levels with moist physics which results in both the upper-and lower-level peaks of the CNOP.Secondly,the upper-level sensitive area is associated with high baroclinicity,and these dynamic features can be captured by both CNOPs with and without moist physics.The lower-level sensitive area is associated with moist processes,and this thermodynamic feature can be captured only by the CNOP with moist physics.This result demonstrates the important contribution of the initial error of lower-level systems that are related to water vapor transportation to the forecast error of heavy rainfall associated weather systems,which could be an important reference for heavy rainfall observation targeting.展开更多
The impacts of the enhanced model's moist physics and horizontal resolution upon the QPFs (quantitative precipitation forecasts)are investigated by applying the HIRLAM(high resolution limited area model)to the sum...The impacts of the enhanced model's moist physics and horizontal resolution upon the QPFs (quantitative precipitation forecasts)are investigated by applying the HIRLAM(high resolution limited area model)to the summer heavy-rain cases in China.The performance of the control run, for which a 0.5°×0.5°grid spacing and a traditional“grid-box supersaturation removal+Kuo type convective paramerization”are used as the moist physics,is compared with that of the sensitivity runs with an enhanced model's moist physics(Sundqvist scheme)and an increased horizontal resolution(0.25°×0.25°),respectively.The results show: (1)The enhanced moist physics scheme(Sundqvist scheme),by introducing the cloud water content as an additional prognostic variable and taking into account briefly of the microphysics involved in the cloud-rain conversion,does bring improvements in the model's QPFs.Although the deteriorated QPFs also occur occasionally,the improvements are found in the majority of the cases,indicating the great potential for the improvement of QPFs by enhancing the model's moist physics. (2)By increasing the model's horizontal resolution from 0.5°×0.5°,which is already quite high compared with that of the conventional atmospheric soundings,to 0.25°×0.25°without the simultaneous enhancement in model physics and objective analysis,the improvements in QPFs are very limited.With higher resolution,although slight amelioration in locating the rainfall centers and in resolving some finer structures of precipitation pattern are made,the number of the mis- predicted fine structures in rainfall field increases with the enhanced model resolution as well.展开更多
In this paper, a typical mei-yu front process with heavy rainfall from June 12 to 15 in 1998 is analyzed. The results show that the mei-yu front is a front system which consists of an iso-theta(e) dense area with stro...In this paper, a typical mei-yu front process with heavy rainfall from June 12 to 15 in 1998 is analyzed. The results show that the mei-yu front is a front system which consists of an iso-theta(e) dense area with strong horizontal gradient, a deep-convective cloud tower band, a passageway transporting warm and moist air flow from the summer monsoon surge in the mid and low levels to the south of the mei-yu front, and a migrating synoptic scale trough to the north of the mei-yu front, which transports cold and dry air southward in the mid and upper levels. The maintenance of the mei-yu front is realized by: (1) is a positive feedback between the moist physical process enhancing frontogenesis and the development of the strong convective system in front of the mei-yu front; (2) the sustaining system to the north of the mei-yu front which is a migrating synoptic scale trough transporting cold and dry air to the mei-yu front and positive vorticity to the mesoscale system in front of the mei-yu front.展开更多
In the typhoon adaptive observation based on conditional nonlinear optimal perturbation (CNOP), the ‘on-off’ switch caused by moist physical parameterization in prediction models prevents the conventional adjoint me...In the typhoon adaptive observation based on conditional nonlinear optimal perturbation (CNOP), the ‘on-off’ switch caused by moist physical parameterization in prediction models prevents the conventional adjoint method from providing correct gradient during the optimization process. To address this problem, the capture of CNOP, when the "on-off" switches are included in models, is treated as non-smooth optimization in this study, and the genetic algorithm (GA) is introduced. After detailed algorithm procedures are formulated using an idealized model with parameterization "on-off" switches in the forcing term, the impacts of "on-off" switches on the capture of CNOP are analyzed, and three numerical experiments are conducted to check the effectiveness of GA in capturing CNOP and to analyze the impacts of different initial populations on the optimization result. The result shows that GA is competent for the capture of CNOP in the context of the idealized model with parameterization ‘on-off’ switches in this study. Finally, the advantages and disadvantages of GA in capturing CNOP are analyzed in detail.展开更多
基金supported by the National Nat-ural Science Foundation of China(Grant Nos.42030604,41875051,and 41425018).
文摘The impact of moist physics on the sensitive areas identified by conditional nonlinear optimal perturbation(CNOP)is examined based on four typical heavy rainfall cases in northern China through performing numerical experiments with and without moist physics.Results show that the CNOP with moist physics identifies sensitive areas corresponding to both the lower-(850−700 hPa)and upper-level(300−100 hPa)weather systems,while the CNOP without moist physics fails to capture the sensitive areas at lower levels.The reasons for the CNOP peaking at different levels can be explained in both algorithm and physics aspects.Firstly,the gradient of the cost function with respect to initial perturbations peaks at the upper level without moist physics which results in the upper-level peak of the CNOP,while it peaks at both the upper and lower levels with moist physics which results in both the upper-and lower-level peaks of the CNOP.Secondly,the upper-level sensitive area is associated with high baroclinicity,and these dynamic features can be captured by both CNOPs with and without moist physics.The lower-level sensitive area is associated with moist processes,and this thermodynamic feature can be captured only by the CNOP with moist physics.This result demonstrates the important contribution of the initial error of lower-level systems that are related to water vapor transportation to the forecast error of heavy rainfall associated weather systems,which could be an important reference for heavy rainfall observation targeting.
基金Financially supported by the Chinese State Education Committee's Research Foundation for scholars returning from abroad and by Danish Government's Danida Foundation.
文摘The impacts of the enhanced model's moist physics and horizontal resolution upon the QPFs (quantitative precipitation forecasts)are investigated by applying the HIRLAM(high resolution limited area model)to the summer heavy-rain cases in China.The performance of the control run, for which a 0.5°×0.5°grid spacing and a traditional“grid-box supersaturation removal+Kuo type convective paramerization”are used as the moist physics,is compared with that of the sensitivity runs with an enhanced model's moist physics(Sundqvist scheme)and an increased horizontal resolution(0.25°×0.25°),respectively.The results show: (1)The enhanced moist physics scheme(Sundqvist scheme),by introducing the cloud water content as an additional prognostic variable and taking into account briefly of the microphysics involved in the cloud-rain conversion,does bring improvements in the model's QPFs.Although the deteriorated QPFs also occur occasionally,the improvements are found in the majority of the cases,indicating the great potential for the improvement of QPFs by enhancing the model's moist physics. (2)By increasing the model's horizontal resolution from 0.5°×0.5°,which is already quite high compared with that of the conventional atmospheric soundings,to 0.25°×0.25°without the simultaneous enhancement in model physics and objective analysis,the improvements in QPFs are very limited.With higher resolution,although slight amelioration in locating the rainfall centers and in resolving some finer structures of precipitation pattern are made,the number of the mis- predicted fine structures in rainfall field increases with the enhanced model resolution as well.
文摘In this paper, a typical mei-yu front process with heavy rainfall from June 12 to 15 in 1998 is analyzed. The results show that the mei-yu front is a front system which consists of an iso-theta(e) dense area with strong horizontal gradient, a deep-convective cloud tower band, a passageway transporting warm and moist air flow from the summer monsoon surge in the mid and low levels to the south of the mei-yu front, and a migrating synoptic scale trough to the north of the mei-yu front, which transports cold and dry air southward in the mid and upper levels. The maintenance of the mei-yu front is realized by: (1) is a positive feedback between the moist physical process enhancing frontogenesis and the development of the strong convective system in front of the mei-yu front; (2) the sustaining system to the north of the mei-yu front which is a migrating synoptic scale trough transporting cold and dry air to the mei-yu front and positive vorticity to the mesoscale system in front of the mei-yu front.
基金Application investigation of conditional nonlinear optimal perturbation in typhoon adaptive observation (40830955)
文摘In the typhoon adaptive observation based on conditional nonlinear optimal perturbation (CNOP), the ‘on-off’ switch caused by moist physical parameterization in prediction models prevents the conventional adjoint method from providing correct gradient during the optimization process. To address this problem, the capture of CNOP, when the "on-off" switches are included in models, is treated as non-smooth optimization in this study, and the genetic algorithm (GA) is introduced. After detailed algorithm procedures are formulated using an idealized model with parameterization "on-off" switches in the forcing term, the impacts of "on-off" switches on the capture of CNOP are analyzed, and three numerical experiments are conducted to check the effectiveness of GA in capturing CNOP and to analyze the impacts of different initial populations on the optimization result. The result shows that GA is competent for the capture of CNOP in the context of the idealized model with parameterization ‘on-off’ switches in this study. Finally, the advantages and disadvantages of GA in capturing CNOP are analyzed in detail.
