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
Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational （4D-Vat） data assimilation system was developed for ...Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational （4D-Vat） data assimilation system was developed for an intermediate coupled model （ICM） and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer （Te）, which is empirically and explicitly related to sea level （SL） variation. The strength of the thermocline effect on SST （referred to simply as ＂the thermocline effect＂） is represented by an introduced parameter, （l＇Te. A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having their initial condition optimized only, and having their initial condition plus this additional model parameter optimized, are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameters and initial conditions together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Vat data assimilation system implemented in the ICM are also discussed.展开更多
An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating s...An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guantlng reservoir inlet and outlet （China）. The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What＇s more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting.展开更多
The upward lightning(UL) initiated from the top of tall buildings(at least above 100 m) is a type of atmospheric discharge. Currently, we understand the nature of the UL from ground observations, but the corresponding...The upward lightning(UL) initiated from the top of tall buildings(at least above 100 m) is a type of atmospheric discharge. Currently, we understand the nature of the UL from ground observations, but the corresponding theoretical research is lacking. Based on an existing bidirectional leader stochastic model, a stochastic parameterization scheme for the UL has been built and embedded in an existing two-dimensional thundercloud charge/discharge model. The ULs simulated from the experiments with two-dimensional high resolution agree generally with the observation results. By analyzing the charge structure of thunderstorm clouds, we determined the in-cloud environmental characteristics that favor the initiation of conventional cloud-to-ground(CG) flashes and analyzed the differences and similarities of some characteristics of the positive and the negative UL. Simulation results indicate that the positive ULs are typically other-lightning-triggered ULs(OLTUL) and are usually a discharge phenomenon between the ground and the lower positive charge region appearing below the main middle negative charge region. The effect of the previous in-cloud lightning(IC) process of space electrical field provides favorable conditions for the initiation of a positive UL. Its entire discharge process is limited, and the branches of the leader are fewer in number as its discharge is not sufficient. A negative UL is generally a discharge phenomenon of the dipole charge structure between the ground and the main negative charge region. The lower temperature stratification and the sinking of the hydrometeors typically initiate a negative UL. Negative ULs develop strongly and have more branches. The OLTUL is initiated mainly during the development stage of a thunderstorm, while the self-triggered UL(STUL) is initiated mainly during the dissipation stage of a thunderstorm.展开更多
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supported by the National Natural Science Foundation of China (Grant Nos. 41705082, 41475101, 41690122(41690120))a Chinese Academy of Sciences Strategic Priority Project-the Western Pacific Ocean System (Grant Nos. XDA11010105 and XDA11020306)+1 种基金the National Programme on Global Change and Air–Sea Interaction (Grant Nos. GASI-IPOVAI06 and GASI-IPOVAI-01-01)the China Postdoctoral Science Foundation, and a Qingdao Postdoctoral Application Research Project
文摘Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational （4D-Vat） data assimilation system was developed for an intermediate coupled model （ICM） and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer （Te）, which is empirically and explicitly related to sea level （SL） variation. The strength of the thermocline effect on SST （referred to simply as ＂the thermocline effect＂） is represented by an introduced parameter, （l＇Te. A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having their initial condition optimized only, and having their initial condition plus this additional model parameter optimized, are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameters and initial conditions together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Vat data assimilation system implemented in the ICM are also discussed.
基金supported by the National Natural Science Foundation of China (Nos. 51178018 and 71031001)
文摘An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guantlng reservoir inlet and outlet （China）. The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What＇s more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting.
基金supported by the National Key Basic Research Development Program of China (Grant No. 2014CB441403)the National Natural Science Foundation of China (Grant Nos. 41175003 & 41475003)
文摘The upward lightning(UL) initiated from the top of tall buildings(at least above 100 m) is a type of atmospheric discharge. Currently, we understand the nature of the UL from ground observations, but the corresponding theoretical research is lacking. Based on an existing bidirectional leader stochastic model, a stochastic parameterization scheme for the UL has been built and embedded in an existing two-dimensional thundercloud charge/discharge model. The ULs simulated from the experiments with two-dimensional high resolution agree generally with the observation results. By analyzing the charge structure of thunderstorm clouds, we determined the in-cloud environmental characteristics that favor the initiation of conventional cloud-to-ground(CG) flashes and analyzed the differences and similarities of some characteristics of the positive and the negative UL. Simulation results indicate that the positive ULs are typically other-lightning-triggered ULs(OLTUL) and are usually a discharge phenomenon between the ground and the lower positive charge region appearing below the main middle negative charge region. The effect of the previous in-cloud lightning(IC) process of space electrical field provides favorable conditions for the initiation of a positive UL. Its entire discharge process is limited, and the branches of the leader are fewer in number as its discharge is not sufficient. A negative UL is generally a discharge phenomenon of the dipole charge structure between the ground and the main negative charge region. The lower temperature stratification and the sinking of the hydrometeors typically initiate a negative UL. Negative ULs develop strongly and have more branches. The OLTUL is initiated mainly during the development stage of a thunderstorm, while the self-triggered UL(STUL) is initiated mainly during the dissipation stage of a thunderstorm.
