Physics informed neural networks(PINNs)are a deep learning approach designed to solve partial differential equations(PDEs).Accurately learning the initial conditions is crucial when employing PINNs to solve PDEs.Howev...Physics informed neural networks(PINNs)are a deep learning approach designed to solve partial differential equations(PDEs).Accurately learning the initial conditions is crucial when employing PINNs to solve PDEs.However,simply adjusting weights and imposing hard constraints may not always lead to better learning of the initial conditions;sometimes it even makes it difficult for the neural networks to converge.To enhance the accuracy of PINNs in learning the initial conditions,this paper proposes a novel strategy named causally enhanced initial conditions(CEICs).This strategy works by embedding a new loss in the loss function:the loss is constructed by the derivative of the initial condition and the derivative of the neural network at the initial condition.Furthermore,to respect the causality in learning the derivative,a novel causality coefficient is introduced for the training when selecting multiple derivatives.Additionally,because CEICs can provide more accurate pseudo-labels in the first subdomain,they are compatible with the temporal-marching strategy.Experimental results demonstrate that CEICs outperform hard constraints and improve the overall accuracy of pre-training PINNs.For the 1D-Korteweg–de Vries,reaction and convection equations,the CEIC method proposed in this paper reduces the relative error by at least 60%compared to the previous methods.展开更多
Impacts of initial conditions on cloud-resolving model simulations are investigated using a series of sensitivity experiments. Five experiments with perturbed initial temperature, moisture, and cloud conditions are co...Impacts of initial conditions on cloud-resolving model simulations are investigated using a series of sensitivity experiments. Five experiments with perturbed initial temperature, moisture, and cloud conditions are conducted and compared to the control experiment. The model is forced by the large-scale vertical velocity and zonal wind observed and derived from NCEP/Global Data Assimilation System （GDAS）. The results indicate that model predictions of rainfall are much more sensitive to the initial conditions than those of temperature and moisture. Further analyses of the surface rainfall equation and the moisture and cloud hydrometeor budgets reveal that the calculations of vapor condensation and deposition rates in the model account for the large sensitivities in rainfall simulations.展开更多
Focusing on the role of initial condition uncertainty,we use WRF initial perturbation ensemble forecasts to investigate the uncertainty in intensity forecasts of Tropical Cyclone(TC)Rammasun(1409),which is the stronge...Focusing on the role of initial condition uncertainty,we use WRF initial perturbation ensemble forecasts to investigate the uncertainty in intensity forecasts of Tropical Cyclone(TC)Rammasun(1409),which is the strongest TC to have made landfall in China during the past 50 years.Forecast results indicate that initial condition uncertainty leads to TC forecast uncertainty,particularly for TC intensity.This uncertainty increases with forecast time,with a more rapid and significant increase after 24 h.The predicted TC develops slowly before 24 h,and at this stage the TC in the member forecasting the strongest final TC is not the strongest among all members.However,after 24 h,the TC in this member strengthens much more than that the TC in other members.The variations in convective instability,precipitation,surface upward heat flux,and surface upward water vapor flux show similar characteristics to the variation in TC intensity,and there is a strong correlation between TC intensity and both the surface upward heat flux and the surface upward water vapor flux.The initial condition differences that result in the maximum intensity difference are smaller than the errors in the analysis system.Differences in initial humidity,and to a lesser extent initial temperature differences,at the surface and at lower heights are the key factors leading to differences in the forecasted TC intensity.These differences in initial humidity and temperature relate to both the overall values and distribution of these parameters.展开更多
System identification is a method for using measured data to create or improve a mathematical model of the object being tested. From the measured data however, noise is noticed at the beginning of the response. One so...System identification is a method for using measured data to create or improve a mathematical model of the object being tested. From the measured data however, noise is noticed at the beginning of the response. One solution to avoid this noise problem is to skip the noisy data and then use the initial conditions as active parameters, to be found by using the system identification process. This paper describes the development of the equations for setting up the initial conditions as active parameters. The simulated data and response data from actual shear buildings were used to prove the accuracy of both the algorithm and the computer program, which include the initial conditions as active parameters. The numerical and experimental model analysis showed that the value of mass, stiffness and frequency were very reasonable and that the computed acceleration and measured acceleration matched very well.展开更多
Symmetrical passive running of a simple spring model is commonly used to predict the locomotion of real animals and develop the design strategies for legged systems. If the initial conditions for running can be found ...Symmetrical passive running of a simple spring model is commonly used to predict the locomotion of real animals and develop the design strategies for legged systems. If the initial conditions for running can be found automatically, we can expand the ranges of the model parameters freely. To achieve this objective, we derive an efcient searching procedure based on analysis of the symmetries. Using this process, the desired initial states of the passive running are obtained. Existence of the results reveals that the leg symmetries can be used to generate the symmetrical running. Moreover, the leg forces are associated with the running pattern, implying that we should choose suitable motion for the given model characteristics.展开更多
A chimera state consisting of both coherent and incoherent groups is a fascinating spatial pattern in non-locally coupled identical oscillators. It is thought that random initial conditions hardly evolve to chimera st...A chimera state consisting of both coherent and incoherent groups is a fascinating spatial pattern in non-locally coupled identical oscillators. It is thought that random initial conditions hardly evolve to chimera states. In this work, we study the dependence of chimera states on initial conditions. We show that random initial conditions may lead to chimera states and the chance of realizing chimera states becomes increasing when the model parameters axe moving away from the boundary of their stable regime.展开更多
The basic objects of investigation in this article are nonlinear impulsive dif- ferential equations. The impulsive moments coincide with the moments of meeting of the integral curve and some of the so-called barrier c...The basic objects of investigation in this article are nonlinear impulsive dif- ferential equations. The impulsive moments coincide with the moments of meeting of the integral curve and some of the so-called barrier curves. For such type of equations, suf- ficient conditions are found under which the solutions are continuously dependent on the perturbations with respect to the initial conditions and barrier curves. The results are applied to a mathematical model of population dynamics.展开更多
This study uses ECMWF fifth-generation reanalysis, ERA5, which extends to the mesopause, to construct the Initial Conditions(IC) for WACCM(Whole Atmosphere Community Climate Model) simulations. Because the biases betw...This study uses ECMWF fifth-generation reanalysis, ERA5, which extends to the mesopause, to construct the Initial Conditions(IC) for WACCM(Whole Atmosphere Community Climate Model) simulations. Because the biases between ERA5 and Sounding of the Atmosphere using Broadband Emission Radiometry(SABER) temperature data are within ±5 K below the lower mesosphere,ERA5 reanalysis is used to construct IC in the lower atmosphere. Four experiments are performed to simulate a Stratospheric Sudden Warming(SSW) event from 5 to 15 February 2016. The simulation using the WACCM default climatic IC cannot represent the sharp meteorological variation during SSW. In contrast, the 0～4 d forecast results driven by ERA5-constructed IC is consistent with ERA5 reanalysis below the middle mesosphere. Comparing with WACCM climatology ICs scheme, the ICs constructing method based on ERA5 reanalysis can obtain 67%, 40%, 22%, 4% and 6% reduction of temperature forecast RMSE at 10 hPa, 1 hPa, 0.1 hPa, 0.01 hPa and 0.001 hPa respectively. However,such improvement is not shown in the lower thermosphere.展开更多
A novel computationally efficient algorithm in terms of the time-varying symbolic dynamic method is proposed to estimate the unknown initial conditions of coupled map lattices （CMLs）. The presented method combines s...A novel computationally efficient algorithm in terms of the time-varying symbolic dynamic method is proposed to estimate the unknown initial conditions of coupled map lattices （CMLs）. The presented method combines symbolic dynamics with time-varying control parameters to develop a time-varying scheme for estimating the initial condition of multi-dimensional spatiotemporal chaotic signals. The performances of the presented time-varying estimator in both noiseless and noisy environments are analysed and compared with the common time-invariant estimator. Simulations are carried out and the obtained results show that the proposed method provides an efficient estimation of the initial condition of each lattice in the coupled system. The algorithm cannot yield an asymptotically unbiased estimation due to the effect of the coupling term, but the estimation with the time-varying algorithm is closer to the Cramer-Rao lower bound （CRLB） than that with the time-invariant estimation method, especially at high signal-to-noise ratios （SNRs）.展开更多
The existence,uniqueness,and continuous dependence to the mild solutions of the nonlocal Cauchy problem were proved for a class of semilinear fractional neutral differential equations.The results are obtained by using...The existence,uniqueness,and continuous dependence to the mild solutions of the nonlocal Cauchy problem were proved for a class of semilinear fractional neutral differential equations.The results are obtained by using the Krasnoselskii's fixed point theorem and the theory of resolvent operators for integral equations.展开更多
This study evaluated the simulation performance of mesoscale convective system(MCS)-induced precipitation,focusing on three selected cases that originated from the Yellow Sea and propagated toward the Korean Peninsula...This study evaluated the simulation performance of mesoscale convective system(MCS)-induced precipitation,focusing on three selected cases that originated from the Yellow Sea and propagated toward the Korean Peninsula.The evaluation was conducted for the European Centre for Medium-Range Weather Forecasts(ECMWF)and National Centers for Environmental Prediction(NCEP)analysis data,as well as the simulation result using them as initial and lateral boundary conditions for the Weather Research and Forecasting model.Particularly,temperature and humidity profiles from 3D dropsonde observations from the National Center for Meteorological Science of the Korea Meteorological Administration served as validation data.Results showed that the ECMWF analysis consistently had smaller errors compared to the NCEP analysis,which exhibited a cold and dry bias in the lower levels below 850 hPa.The model,in terms of the precipitation simulations,particularly for high-intensity precipitation over the Yellow Sea,demonstrated higher accuracy when applying ECMWF analysis data as the initial condition.This advantage also positively influenced the simulation of rainfall events on the Korean Peninsula by reasonably inducing convective-favorable thermodynamic features(i.e.,warm and humid lower-level atmosphere)over the Yellow Sea.In conclusion,this study provides specific information about two global analysis datasets and their impacts on MCS-induced heavy rainfall simulation by employing dropsonde observation data.Furthermore,it suggests the need to enhance the initial field for MCS-induced heavy rainfall simulation and the applicability of assimilating dropsonde data for this purpose in the future.展开更多
Accurate initial soil conditions play a crucial role in simulating soil hydrothermal and surface energy fluxes in land surface process modeling.This study emphasized the influence of the initial soil temperature(ST)an...Accurate initial soil conditions play a crucial role in simulating soil hydrothermal and surface energy fluxes in land surface process modeling.This study emphasized the influence of the initial soil temperature(ST)and soil moisture(SM)conditions on a land surface energy and water simulation in the permafrost region in the Tibetan Plateau(TP)using the Community Land Model version 5.0(CLM5.0).The results indicate that the default initial schemes for ST and SM in CLM5.0 were simplistic,and inaccurately represented the soil characteristics of permafrost in the TP which led to underestimating ST during the freezing period while overestimating ST and underestimating SLW during the thawing period at the XDT site.Applying the long-term spin-up method to obtain initial soil conditions has only led to limited improvement in simulating soil hydrothermal and surface energy fluxes.The modified initial soil schemes proposed in this study comprehensively incorporate the characteristics of permafrost,which coexists with soil liquid water(SLW),and soil ice(SI)when the ST is below freezing temperature,effectively enhancing the accuracy of the simulated soil hydrothermal and surface energy fluxes.Consequently,the modified initial soil schemes greatly improved upon the results achieved through the long-term spin-up method.Three modified initial soil schemes experiments resulted in a 64%,88%,and 77%reduction in the average mean bias error(MBE)of ST,and a 13%,21%,and 19%reduction in the average root-mean-square error(RMSE)of SLW compared to the default simulation results.Also,the average MBE of net radiation was reduced by 7%,22%,and 21%.展开更多
Pangu-Weather(PGW),trained with deep learning–based methods(DL-based model),shows significant potential for global medium-range weather forecasting.However,the interpretability and trustworthiness of global medium-ra...Pangu-Weather(PGW),trained with deep learning–based methods(DL-based model),shows significant potential for global medium-range weather forecasting.However,the interpretability and trustworthiness of global medium-range DLbased models raise many concerns.This study uses the singular vector(SV)initial condition(IC)perturbations of the China Meteorological Administration's Global Ensemble Prediction System(CMA-GEPS)as inputs of PGW for global ensemble prediction(PGW-GEPS)to investigate the ensemble forecast sensitivity of DL-based models to the IC errors.Meanwhile,the CMA-GEPS forecasts serve as benchmarks for comparison and verification.The spatial structures and prediction performance of PGW-GEPS are discussed and compared to CMA-GEPS based on seasonal ensemble experiments.The results show that the ensemble mean and dispersion of PGW-GEPS are similar to those of CMA-GEPS in the medium range but with smoother forecasts.Meanwhile,PGW-GEPS is sensitive to the SV IC perturbations.Specifically,PGWGEPS can generate realistic ensemble spread beyond the sub-synoptic scale(wavenumbers≤64)with SV IC perturbations.However,PGW's kinetic energy is significantly reduced at the sub-synoptic scale,leading to error growth behavior inconsistent with CMA-GEPS at that scale.Thus,this behavior indicates that the effective resolution of PGW-GEPS is beyond the sub-synoptic scale and is limited to predicting mesoscale atmospheric motions.In terms of the global mediumrange ensemble prediction performance,the probability prediction skill of PGW-GEPS is comparable to CMA-GEPS in the extratropic when they use the same IC perturbations.That means that PGW has a general ability to provide skillful global medium-range forecasts with different ICs from numerical weather prediction.展开更多
New developed inverse differential operators incorporated into the semi- analytical treatment of the modified decomposition method （MDM） are used to solve the systems of first and second-order singular nonlinear par...New developed inverse differential operators incorporated into the semi- analytical treatment of the modified decomposition method （MDM） are used to solve the systems of first and second-order singular nonlinear partial differential equations （PDEs） with initial conditions arising in physics. The new proposed method is called the improved modified decomposition method （IMDM）, and is used to the treatment of a few case study initial-value problems. The results obtained by the IMDM are in full agreement with the existing exact analytical solutions.展开更多
This paper aims to assess the performances of different model initialization conditions(ICs)and lateral boundary conditions between two global models(GMs),i.e.,the European Centre for Medium-Range Weather Forecasts(EC...This paper aims to assess the performances of different model initialization conditions(ICs)and lateral boundary conditions between two global models(GMs),i.e.,the European Centre for Medium-Range Weather Forecasts(ECMWF)and National Centers for Environmental Prediction(NCEP),on the accuracy of the Global/Regional Assimilation and Prediction System(GRAPES)forecasts for south China.A total of 3-month simulations during the rainy season were examined and a specific case of torrential rain over Guangdong Province was verified.Both ICs exhibited cold biases over south China,as well as a strong dry bias over the Pearl River Delta(PRD).In particular,the ICs from the ECMWF had a stronger cold bias over the PRD region and a more detailed structure than NCEP.In general,the NCEP provided a realistic surface temperature compared to the ECMWF over south China.Moreover,GRAPES initialized by the NCEP had better simulations of both location and intensity of precipitation than by the ECWMF.The results presented in this paper could be used as a general guideline to the operational numerical weather prediction that uses regional models driven by the GMs.展开更多
Based on the real case of a frontal precipitation process affecting South China, 27 controlled numerical experiments was made for the effects of hydrostatic and non-hydrostatic effects, different driving models, combi...Based on the real case of a frontal precipitation process affecting South China, 27 controlled numerical experiments was made for the effects of hydrostatic and non-hydrostatic effects, different driving models, combinations of initial/boundary conditions, updates of lateral values and initial time levels of forecast, on model predictions. Features about the impact of initial/boundary conditions on mesoscale numerical weather prediction (NWP) model are analyzed and discussed in detail. Some theoretically and practically valuable conclusions are drawn. It is found that the overall tendency of mesoscale NWP models is governed by its driving model, with the initial conditions showing remarkable impacts on mesoscale models for the first I0 hours of the predictions while leaving lateral boundary conditions to take care the period beyond; the latter affect the inner area of mesoscale predictions mainly through the propagation and movement of weather signals (waves) of different time scales; initial values of external model parameters such as soil moisture content may affect predictions of more longer time validity, while fast signals may be filtered away and only information with time scale 4 times as large as or more than the updated period of boundary values may be introduced, through lateral boundary, to mesoseale models, etc. Some results may be taken as important guidance on mesoseale model and its data a.ssimilation developments of the future.展开更多
By using GDS dynamic hollow cylinder torsional apparatus, a series of cyclic torsional triaxial tests under complex initial consolidation condition are performed on Nanjing saturated fine sand. The effects of the init...By using GDS dynamic hollow cylinder torsional apparatus, a series of cyclic torsional triaxial tests under complex initial consolidation condition are performed on Nanjing saturated fine sand. The effects of the initial principal stress direction αo, the initial ratio of deviatoric stress η0, the initial average effective principal stress Po and the initial intermediate principal stress parameter b0 on the threshold shear strain γt of Nanjing saturated fine sand are then systematically investigated. The results show that γt increases as η0,p0 and b0 increase respectively, while the other three parameters remain constant. ao has a great influence on γt, which is reduced when ao increases from 0° to 45°and increased when α0 increases from 45° to 90°. The effect of α0 on γt, plays a leading role and the effect of η0 will weaken when ao is approximately 45°.展开更多
Initial labor market conditions affect how individuals build their human capital and look for jobs and thus can have long-term effects on their income levels,work performance,and career development.Based on data from ...Initial labor market conditions affect how individuals build their human capital and look for jobs and thus can have long-term effects on their income levels,work performance,and career development.Based on data from the Urban Household Survey(UHS)of urban households in China from 1986 to 2009,we perform an empirical test of how initial labor market conditions affect the employability of individuals.Our research shows that people’s future incomes suffer if they start out in an adverse job market.Each percentage point of increase in the unemployment rate at an individual’s entry into the labor market is associated with a two-percentage-point drop in his or her average annual income.Even after looking at different parts of the job market and sample groups,this conclusion still holds.In the context of global economic instability,our findings may assist government policymakers in addressing adverse labor market conditions.展开更多
In this study, a series of sensitivity experiments were performed for two tropical cyclones （TCs）, TC Longwang （2005） and TC Sinlaku （2008）, to explore the roles of locations and patterns of initial errors in un...In this study, a series of sensitivity experiments were performed for two tropical cyclones （TCs）, TC Longwang （2005） and TC Sinlaku （2008）, to explore the roles of locations and patterns of initial errors in uncertainties of TC forecasts. Specifically, three types of initial errors were generated and three types of sensitive areas were determined using conditional nonlinear optimal perturbation （CNOP）, first singular vector （FSV）, and composite singular vector （CSV） methods. Additionally, random initial errors in randomly selected areas were considered. Based on these four types of initial errors and areas, we designed and performed 16 experiments to investigate the impacts of locations and patterns of initial errors on the nonlinear developments of the errors, and to determine which type of initial errors and areas has the greatest impact on TC forecasts. Overall, results from the experiments indicate the following： （1） The impact of random errors introduced into the sensitive areas was greater than that of errors themselves fixed in the randomly selected areas. From the perspective of statisticul analysis, and by comparison, the impact of random errors introduced into the CNOP target area was greatest. （2） The initial errors with CNOP, CSV, or FSV patterns were likely to grow faster than random errors. （3） The initial errors with CNOP patterns in the CNOP target areas had the greatest impacts on the final verification forecasts.展开更多
In order to understand the impact of initial conditions upon prediction accuracy of short-term forecast and nowcast of precipitation in South China, four experiments i.e. a control, an assimilation of conventional sou...In order to understand the impact of initial conditions upon prediction accuracy of short-term forecast and nowcast of precipitation in South China, four experiments i.e. a control, an assimilation of conventional sounding and surface data, testing with nudging rainwater data and the assimilation of radar-derived radial wind, are respectively conducted to simulate a case of warm-sector heavy rainfall that occurred over South China, by using the GRAPES_MESO model. The results show that (1) assimilating conventional surface and sounding observations helps improve the 24-h rainfall forecast in both the area and order of magnitude; (2) nudging rainwater contributes to a significant improvement of nowcast, and (3) the assimilation of radar-derived radial winds distinctly improves the 24-h rainfall forecast in both the area and order of magnitude. These results serve as significant technical reference for the study on short-term forecast and nowcast of precipitation over South China in the future.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.1217211 and 12372244).
文摘Physics informed neural networks(PINNs)are a deep learning approach designed to solve partial differential equations(PDEs).Accurately learning the initial conditions is crucial when employing PINNs to solve PDEs.However,simply adjusting weights and imposing hard constraints may not always lead to better learning of the initial conditions;sometimes it even makes it difficult for the neural networks to converge.To enhance the accuracy of PINNs in learning the initial conditions,this paper proposes a novel strategy named causally enhanced initial conditions(CEICs).This strategy works by embedding a new loss in the loss function:the loss is constructed by the derivative of the initial condition and the derivative of the neural network at the initial condition.Furthermore,to respect the causality in learning the derivative,a novel causality coefficient is introduced for the training when selecting multiple derivatives.Additionally,because CEICs can provide more accurate pseudo-labels in the first subdomain,they are compatible with the temporal-marching strategy.Experimental results demonstrate that CEICs outperform hard constraints and improve the overall accuracy of pre-training PINNs.For the 1D-Korteweg–de Vries,reaction and convection equations,the CEIC method proposed in this paper reduces the relative error by at least 60%compared to the previous methods.
基金the National Key BasicResearch and Development Project of China under GrantNo. 2004CB418301the National Natural Sciences Foun-dation of China under Grant No. 40775031"Outstand-ing Oversea Scholars" Project No.2005-2-16.
文摘Impacts of initial conditions on cloud-resolving model simulations are investigated using a series of sensitivity experiments. Five experiments with perturbed initial temperature, moisture, and cloud conditions are conducted and compared to the control experiment. The model is forced by the large-scale vertical velocity and zonal wind observed and derived from NCEP/Global Data Assimilation System （GDAS）. The results indicate that model predictions of rainfall are much more sensitive to the initial conditions than those of temperature and moisture. Further analyses of the surface rainfall equation and the moisture and cloud hydrometeor budgets reveal that the calculations of vapor condensation and deposition rates in the model account for the large sensitivities in rainfall simulations.
基金financial support from the National Natural Science Foundation of China (Grant Nos. 41575108 and 41475082)
文摘Focusing on the role of initial condition uncertainty,we use WRF initial perturbation ensemble forecasts to investigate the uncertainty in intensity forecasts of Tropical Cyclone(TC)Rammasun(1409),which is the strongest TC to have made landfall in China during the past 50 years.Forecast results indicate that initial condition uncertainty leads to TC forecast uncertainty,particularly for TC intensity.This uncertainty increases with forecast time,with a more rapid and significant increase after 24 h.The predicted TC develops slowly before 24 h,and at this stage the TC in the member forecasting the strongest final TC is not the strongest among all members.However,after 24 h,the TC in this member strengthens much more than that the TC in other members.The variations in convective instability,precipitation,surface upward heat flux,and surface upward water vapor flux show similar characteristics to the variation in TC intensity,and there is a strong correlation between TC intensity and both the surface upward heat flux and the surface upward water vapor flux.The initial condition differences that result in the maximum intensity difference are smaller than the errors in the analysis system.Differences in initial humidity,and to a lesser extent initial temperature differences,at the surface and at lower heights are the key factors leading to differences in the forecasted TC intensity.These differences in initial humidity and temperature relate to both the overall values and distribution of these parameters.
文摘System identification is a method for using measured data to create or improve a mathematical model of the object being tested. From the measured data however, noise is noticed at the beginning of the response. One solution to avoid this noise problem is to skip the noisy data and then use the initial conditions as active parameters, to be found by using the system identification process. This paper describes the development of the equations for setting up the initial conditions as active parameters. The simulated data and response data from actual shear buildings were used to prove the accuracy of both the algorithm and the computer program, which include the initial conditions as active parameters. The numerical and experimental model analysis showed that the value of mass, stiffness and frequency were very reasonable and that the computed acceleration and measured acceleration matched very well.
文摘Symmetrical passive running of a simple spring model is commonly used to predict the locomotion of real animals and develop the design strategies for legged systems. If the initial conditions for running can be found automatically, we can expand the ranges of the model parameters freely. To achieve this objective, we derive an efcient searching procedure based on analysis of the symmetries. Using this process, the desired initial states of the passive running are obtained. Existence of the results reveals that the leg symmetries can be used to generate the symmetrical running. Moreover, the leg forces are associated with the running pattern, implying that we should choose suitable motion for the given model characteristics.
基金Supported by the National Natural Science Foundation of China under Grant No 71301012
文摘A chimera state consisting of both coherent and incoherent groups is a fascinating spatial pattern in non-locally coupled identical oscillators. It is thought that random initial conditions hardly evolve to chimera states. In this work, we study the dependence of chimera states on initial conditions. We show that random initial conditions may lead to chimera states and the chance of realizing chimera states becomes increasing when the model parameters axe moving away from the boundary of their stable regime.
文摘The basic objects of investigation in this article are nonlinear impulsive dif- ferential equations. The impulsive moments coincide with the moments of meeting of the integral curve and some of the so-called barrier curves. For such type of equations, suf- ficient conditions are found under which the solutions are continuously dependent on the perturbations with respect to the initial conditions and barrier curves. The results are applied to a mathematical model of population dynamics.
基金Supported by the National Natural Science Foundation of China(41375105)
文摘This study uses ECMWF fifth-generation reanalysis, ERA5, which extends to the mesopause, to construct the Initial Conditions(IC) for WACCM(Whole Atmosphere Community Climate Model) simulations. Because the biases between ERA5 and Sounding of the Atmosphere using Broadband Emission Radiometry(SABER) temperature data are within ±5 K below the lower mesosphere,ERA5 reanalysis is used to construct IC in the lower atmosphere. Four experiments are performed to simulate a Stratospheric Sudden Warming(SSW) event from 5 to 15 February 2016. The simulation using the WACCM default climatic IC cannot represent the sharp meteorological variation during SSW. In contrast, the 0～4 d forecast results driven by ERA5-constructed IC is consistent with ERA5 reanalysis below the middle mesosphere. Comparing with WACCM climatology ICs scheme, the ICs constructing method based on ERA5 reanalysis can obtain 67%, 40%, 22%, 4% and 6% reduction of temperature forecast RMSE at 10 hPa, 1 hPa, 0.1 hPa, 0.01 hPa and 0.001 hPa respectively. However,such improvement is not shown in the lower thermosphere.
基金supported by the National Natural Science Foundation of China(Grant Nos 60271023 and 60571066)the Natural Science Foundation of Guangdong Province,China(Grant Nos 5008317 and 7118382)
文摘A novel computationally efficient algorithm in terms of the time-varying symbolic dynamic method is proposed to estimate the unknown initial conditions of coupled map lattices （CMLs）. The presented method combines symbolic dynamics with time-varying control parameters to develop a time-varying scheme for estimating the initial condition of multi-dimensional spatiotemporal chaotic signals. The performances of the presented time-varying estimator in both noiseless and noisy environments are analysed and compared with the common time-invariant estimator. Simulations are carried out and the obtained results show that the proposed method provides an efficient estimation of the initial condition of each lattice in the coupled system. The algorithm cannot yield an asymptotically unbiased estimation due to the effect of the coupling term, but the estimation with the time-varying algorithm is closer to the Cramer-Rao lower bound （CRLB） than that with the time-invariant estimation method, especially at high signal-to-noise ratios （SNRs）.
文摘The existence,uniqueness,and continuous dependence to the mild solutions of the nonlocal Cauchy problem were proved for a class of semilinear fractional neutral differential equations.The results are obtained by using the Krasnoselskii's fixed point theorem and the theory of resolvent operators for integral equations.
基金supported by the Korea Meteorological Administration Research and Development Program “Developing Application Technology for Atmospheric Research Aircraft” (Grant No. KMA2018-00222)
文摘This study evaluated the simulation performance of mesoscale convective system(MCS)-induced precipitation,focusing on three selected cases that originated from the Yellow Sea and propagated toward the Korean Peninsula.The evaluation was conducted for the European Centre for Medium-Range Weather Forecasts(ECMWF)and National Centers for Environmental Prediction(NCEP)analysis data,as well as the simulation result using them as initial and lateral boundary conditions for the Weather Research and Forecasting model.Particularly,temperature and humidity profiles from 3D dropsonde observations from the National Center for Meteorological Science of the Korea Meteorological Administration served as validation data.Results showed that the ECMWF analysis consistently had smaller errors compared to the NCEP analysis,which exhibited a cold and dry bias in the lower levels below 850 hPa.The model,in terms of the precipitation simulations,particularly for high-intensity precipitation over the Yellow Sea,demonstrated higher accuracy when applying ECMWF analysis data as the initial condition.This advantage also positively influenced the simulation of rainfall events on the Korean Peninsula by reasonably inducing convective-favorable thermodynamic features(i.e.,warm and humid lower-level atmosphere)over the Yellow Sea.In conclusion,this study provides specific information about two global analysis datasets and their impacts on MCS-induced heavy rainfall simulation by employing dropsonde observation data.Furthermore,it suggests the need to enhance the initial field for MCS-induced heavy rainfall simulation and the applicability of assimilating dropsonde data for this purpose in the future.
基金the National Natural Science Foundation of China(Grant No.U20A2081)West Light Foundation of the Chinese Academy of Sciences(Grant No.xbzg-zdsys-202102)the Second Tibetan Plateau Scientific Expedition and Research(STEP)Project(Grant No.2019QZKK0105).
文摘Accurate initial soil conditions play a crucial role in simulating soil hydrothermal and surface energy fluxes in land surface process modeling.This study emphasized the influence of the initial soil temperature(ST)and soil moisture(SM)conditions on a land surface energy and water simulation in the permafrost region in the Tibetan Plateau(TP)using the Community Land Model version 5.0(CLM5.0).The results indicate that the default initial schemes for ST and SM in CLM5.0 were simplistic,and inaccurately represented the soil characteristics of permafrost in the TP which led to underestimating ST during the freezing period while overestimating ST and underestimating SLW during the thawing period at the XDT site.Applying the long-term spin-up method to obtain initial soil conditions has only led to limited improvement in simulating soil hydrothermal and surface energy fluxes.The modified initial soil schemes proposed in this study comprehensively incorporate the characteristics of permafrost,which coexists with soil liquid water(SLW),and soil ice(SI)when the ST is below freezing temperature,effectively enhancing the accuracy of the simulated soil hydrothermal and surface energy fluxes.Consequently,the modified initial soil schemes greatly improved upon the results achieved through the long-term spin-up method.Three modified initial soil schemes experiments resulted in a 64%,88%,and 77%reduction in the average mean bias error(MBE)of ST,and a 13%,21%,and 19%reduction in the average root-mean-square error(RMSE)of SLW compared to the default simulation results.Also,the average MBE of net radiation was reduced by 7%,22%,and 21%.
基金supported by the joint funds of the Chinese National Natural Science Foundation(NSFC)(Grant No.U2242213)the funds of the NSFC(Grant No.42341209)+2 种基金the National Key Research and Development(R&D)Program of the Ministry of Science and Technology of China(Grant No.2021YFC3000902)the National Science Foundation for Young Scholars(Grant No.42205166)the Joint Research Project for Meteorological Capacity Improvement(Grant No.22NLTSQ008)。
文摘Pangu-Weather(PGW),trained with deep learning–based methods(DL-based model),shows significant potential for global medium-range weather forecasting.However,the interpretability and trustworthiness of global medium-range DLbased models raise many concerns.This study uses the singular vector(SV)initial condition(IC)perturbations of the China Meteorological Administration's Global Ensemble Prediction System(CMA-GEPS)as inputs of PGW for global ensemble prediction(PGW-GEPS)to investigate the ensemble forecast sensitivity of DL-based models to the IC errors.Meanwhile,the CMA-GEPS forecasts serve as benchmarks for comparison and verification.The spatial structures and prediction performance of PGW-GEPS are discussed and compared to CMA-GEPS based on seasonal ensemble experiments.The results show that the ensemble mean and dispersion of PGW-GEPS are similar to those of CMA-GEPS in the medium range but with smoother forecasts.Meanwhile,PGW-GEPS is sensitive to the SV IC perturbations.Specifically,PGWGEPS can generate realistic ensemble spread beyond the sub-synoptic scale(wavenumbers≤64)with SV IC perturbations.However,PGW's kinetic energy is significantly reduced at the sub-synoptic scale,leading to error growth behavior inconsistent with CMA-GEPS at that scale.Thus,this behavior indicates that the effective resolution of PGW-GEPS is beyond the sub-synoptic scale and is limited to predicting mesoscale atmospheric motions.In terms of the global mediumrange ensemble prediction performance,the probability prediction skill of PGW-GEPS is comparable to CMA-GEPS in the extratropic when they use the same IC perturbations.That means that PGW has a general ability to provide skillful global medium-range forecasts with different ICs from numerical weather prediction.
文摘New developed inverse differential operators incorporated into the semi- analytical treatment of the modified decomposition method （MDM） are used to solve the systems of first and second-order singular nonlinear partial differential equations （PDEs） with initial conditions arising in physics. The new proposed method is called the improved modified decomposition method （IMDM）, and is used to the treatment of a few case study initial-value problems. The results obtained by the IMDM are in full agreement with the existing exact analytical solutions.
基金National Key R&D Program of China(2018YFC1506901)National Natural Science Foundation of China(41505084)Guangzhou Science and Technology Project(201804020038)
文摘This paper aims to assess the performances of different model initialization conditions(ICs)and lateral boundary conditions between two global models(GMs),i.e.,the European Centre for Medium-Range Weather Forecasts(ECMWF)and National Centers for Environmental Prediction(NCEP),on the accuracy of the Global/Regional Assimilation and Prediction System(GRAPES)forecasts for south China.A total of 3-month simulations during the rainy season were examined and a specific case of torrential rain over Guangdong Province was verified.Both ICs exhibited cold biases over south China,as well as a strong dry bias over the Pearl River Delta(PRD).In particular,the ICs from the ECMWF had a stronger cold bias over the PRD region and a more detailed structure than NCEP.In general,the NCEP provided a realistic surface temperature compared to the ECMWF over south China.Moreover,GRAPES initialized by the NCEP had better simulations of both location and intensity of precipitation than by the ECWMF.The results presented in this paper could be used as a general guideline to the operational numerical weather prediction that uses regional models driven by the GMs.
基金National Project "973" (Research on Heavy Rain in China) and BMBF of Germany (WTZ- Project CHN01/106)
文摘Based on the real case of a frontal precipitation process affecting South China, 27 controlled numerical experiments was made for the effects of hydrostatic and non-hydrostatic effects, different driving models, combinations of initial/boundary conditions, updates of lateral values and initial time levels of forecast, on model predictions. Features about the impact of initial/boundary conditions on mesoscale numerical weather prediction (NWP) model are analyzed and discussed in detail. Some theoretically and practically valuable conclusions are drawn. It is found that the overall tendency of mesoscale NWP models is governed by its driving model, with the initial conditions showing remarkable impacts on mesoscale models for the first I0 hours of the predictions while leaving lateral boundary conditions to take care the period beyond; the latter affect the inner area of mesoscale predictions mainly through the propagation and movement of weather signals (waves) of different time scales; initial values of external model parameters such as soil moisture content may affect predictions of more longer time validity, while fast signals may be filtered away and only information with time scale 4 times as large as or more than the updated period of boundary values may be introduced, through lateral boundary, to mesoseale models, etc. Some results may be taken as important guidance on mesoseale model and its data a.ssimilation developments of the future.
基金supported by the Key Research Project of National Natural Science Foundation of China under grant No. 90715018the Special Fund for the Commonweal Industry of China under grant No. 200808022the Key Basic Research Program of Natural Science of University in Jiangsu Province under grant No. 08KJA560001
文摘By using GDS dynamic hollow cylinder torsional apparatus, a series of cyclic torsional triaxial tests under complex initial consolidation condition are performed on Nanjing saturated fine sand. The effects of the initial principal stress direction αo, the initial ratio of deviatoric stress η0, the initial average effective principal stress Po and the initial intermediate principal stress parameter b0 on the threshold shear strain γt of Nanjing saturated fine sand are then systematically investigated. The results show that γt increases as η0,p0 and b0 increase respectively, while the other three parameters remain constant. ao has a great influence on γt, which is reduced when ao increases from 0° to 45°and increased when α0 increases from 45° to 90°. The effect of α0 on γt, plays a leading role and the effect of η0 will weaken when ao is approximately 45°.
基金supported by the General Project of the National Natural Science Fund of China(NSFC)“China’s Labor Market Matching Efficiency and Economic Effects”(Grant No.71973015)the Major Project of the National Social Science Fund of China(NSSFC)“Study on Enhancing Employment Priority for Stable Job Growth”(Grant No.21ZDA098).
文摘Initial labor market conditions affect how individuals build their human capital and look for jobs and thus can have long-term effects on their income levels,work performance,and career development.Based on data from the Urban Household Survey(UHS)of urban households in China from 1986 to 2009,we perform an empirical test of how initial labor market conditions affect the employability of individuals.Our research shows that people’s future incomes suffer if they start out in an adverse job market.Each percentage point of increase in the unemployment rate at an individual’s entry into the labor market is associated with a two-percentage-point drop in his or her average annual income.Even after looking at different parts of the job market and sample groups,this conclusion still holds.In the context of global economic instability,our findings may assist government policymakers in addressing adverse labor market conditions.
基金sponsored by the National Natural Science Foundation of China(Grant Nos. 40830955)the China Meteorological Administration (Grant No. GYHY200906009)
文摘In this study, a series of sensitivity experiments were performed for two tropical cyclones （TCs）, TC Longwang （2005） and TC Sinlaku （2008）, to explore the roles of locations and patterns of initial errors in uncertainties of TC forecasts. Specifically, three types of initial errors were generated and three types of sensitive areas were determined using conditional nonlinear optimal perturbation （CNOP）, first singular vector （FSV）, and composite singular vector （CSV） methods. Additionally, random initial errors in randomly selected areas were considered. Based on these four types of initial errors and areas, we designed and performed 16 experiments to investigate the impacts of locations and patterns of initial errors on the nonlinear developments of the errors, and to determine which type of initial errors and areas has the greatest impact on TC forecasts. Overall, results from the experiments indicate the following： （1） The impact of random errors introduced into the sensitive areas was greater than that of errors themselves fixed in the randomly selected areas. From the perspective of statisticul analysis, and by comparison, the impact of random errors introduced into the CNOP target area was greatest. （2） The initial errors with CNOP, CSV, or FSV patterns were likely to grow faster than random errors. （3） The initial errors with CNOP patterns in the CNOP target areas had the greatest impacts on the final verification forecasts.
基金Public Welfare Project (GYHX(QX)2007-6-14)Basic operational fees for highest-level public welfare research institutes
文摘In order to understand the impact of initial conditions upon prediction accuracy of short-term forecast and nowcast of precipitation in South China, four experiments i.e. a control, an assimilation of conventional sounding and surface data, testing with nudging rainwater data and the assimilation of radar-derived radial wind, are respectively conducted to simulate a case of warm-sector heavy rainfall that occurred over South China, by using the GRAPES_MESO model. The results show that (1) assimilating conventional surface and sounding observations helps improve the 24-h rainfall forecast in both the area and order of magnitude; (2) nudging rainwater contributes to a significant improvement of nowcast, and (3) the assimilation of radar-derived radial winds distinctly improves the 24-h rainfall forecast in both the area and order of magnitude. These results serve as significant technical reference for the study on short-term forecast and nowcast of precipitation over South China in the future.
