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
With more and more improvements of atmosphere or ocean models,a growing number of physical processes in the form of parameterization are incorporated into the models,which,on the one hand,makes the models capable of d...With more and more improvements of atmosphere or ocean models,a growing number of physical processes in the form of parameterization are incorporated into the models,which,on the one hand,makes the models capable of describing the at-mospheric or oceanic movement more precisely,and on the other hand,introduces non-smoothness in the form of "on-off" switches into the models."On-off" switches enhance the nonlinearity of the models and finally result in the loss of the effec-tiveness of variational data assimilation(VDA) based on the conventional adjoint method(ADJ).This study,in virtue of the optimization ability of a genetic algorithm(GA) for non-smooth problems,presents a new GA(referred to as GA NEW) to solve the problems of the VDA with discontinuous "on-off" processes.In the GA-NEW,adaptive selection and mutation oper-ators,blend crossover operator,and elitist strategy are combined in application.In order to verify the effectiveness and feasi-bility of the GA NEW in VDA,an idealized model of partial differential equation with discontinuous "on-off" switches in the forcing term is adopted as the governing equation.By comparison with the ADJ,it is shown that the GA NEW in VDA is more effective and can yield better assimilation retrievals.In addition,VDA experiments demonstrate that the performance of a GA is greatly related to the configuration of genetic operators(selection,crossover and mutation operators) and much better results may be attained with more proper genetic operations.Furthermore,the robustness of the GA NEW to observational noise,model errors and observation density is investigated,and the results show that the GA NEW has stronger robustness than the ADJ with respect to all the three observation noises,model errors,and sparse observation.展开更多
Bacteria need a high degree of genetic stability to maintain their species identities over long evolutionary times while retaining some mutability to adapt to the changing environment.It is a long unanswered question ...Bacteria need a high degree of genetic stability to maintain their species identities over long evolutionary times while retaining some mutability to adapt to the changing environment.It is a long unanswered question that how bacteria reconcile these seemingly contradictory biological properties.We hypothesized that certain mechanisms must maintain a dynamic balance between genetic stability and mutability for the survival and evolution of bacterial species.To identify such mechanisms,we analyzed bacterial genomes,focusing on the Salmonella mismatch repair(MMR)system.We found that the MMR gene mutL functions as a genetic switch through a slipped-strand mispairing mechanism,modulating and maintaining a dynamic balance between genetic stability and mutability during bacterial evolution.This mechanism allows bacteria to maintain their phylogenetic status,while also adapting to changing environments by acquiring novel traits.In this review,we outline the history of research into this genetic switch,from its discovery to the latest findings,and discuss its potential roles in the genomic evolution of bacteria.展开更多
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.
基金supported by National Natural Science Foundation of China (Grant Nos.40975063 and 40830955)
文摘With more and more improvements of atmosphere or ocean models,a growing number of physical processes in the form of parameterization are incorporated into the models,which,on the one hand,makes the models capable of describing the at-mospheric or oceanic movement more precisely,and on the other hand,introduces non-smoothness in the form of "on-off" switches into the models."On-off" switches enhance the nonlinearity of the models and finally result in the loss of the effec-tiveness of variational data assimilation(VDA) based on the conventional adjoint method(ADJ).This study,in virtue of the optimization ability of a genetic algorithm(GA) for non-smooth problems,presents a new GA(referred to as GA NEW) to solve the problems of the VDA with discontinuous "on-off" processes.In the GA-NEW,adaptive selection and mutation oper-ators,blend crossover operator,and elitist strategy are combined in application.In order to verify the effectiveness and feasi-bility of the GA NEW in VDA,an idealized model of partial differential equation with discontinuous "on-off" switches in the forcing term is adopted as the governing equation.By comparison with the ADJ,it is shown that the GA NEW in VDA is more effective and can yield better assimilation retrievals.In addition,VDA experiments demonstrate that the performance of a GA is greatly related to the configuration of genetic operators(selection,crossover and mutation operators) and much better results may be attained with more proper genetic operations.Furthermore,the robustness of the GA NEW to observational noise,model errors and observation density is investigated,and the results show that the GA NEW has stronger robustness than the ADJ with respect to all the three observation noises,model errors,and sparse observation.
基金supported by a Heilongjiang Innovation Endowment Award for graduate studies(YJSCX2012-197HLJ)to Tang Lea grant from the National Natural Science Foundation of China(NSFC30970078)+1 种基金the Natural Science Foundation of Heilongjiang Province to Liu GuiRongthe National Natural Science Foundation of China(NSFC30970119,81030029,81271786,NSFC-NIH 81161120416)to Liu ShuLin
文摘Bacteria need a high degree of genetic stability to maintain their species identities over long evolutionary times while retaining some mutability to adapt to the changing environment.It is a long unanswered question that how bacteria reconcile these seemingly contradictory biological properties.We hypothesized that certain mechanisms must maintain a dynamic balance between genetic stability and mutability for the survival and evolution of bacterial species.To identify such mechanisms,we analyzed bacterial genomes,focusing on the Salmonella mismatch repair(MMR)system.We found that the MMR gene mutL functions as a genetic switch through a slipped-strand mispairing mechanism,modulating and maintaining a dynamic balance between genetic stability and mutability during bacterial evolution.This mechanism allows bacteria to maintain their phylogenetic status,while also adapting to changing environments by acquiring novel traits.In this review,we outline the history of research into this genetic switch,from its discovery to the latest findings,and discuss its potential roles in the genomic evolution of bacteria.
