Storm-scale ensemble forecast based on breeding of growth modes

How to obtain fast-growth errors, which is comparable to the actual forecast growth error, is a crucial problem in ensemble forecast （EF）. The method, Breeding of Growth Modes （BGM）, which has been used to generate perturbations for medium-range EF at NCEP, simulates the development of fast-growth errors in the analysis cycle, and is a reasonable choice in capturing growing errors modes, especially for extreme weather by BGM. An ideal supercell storm, simulated by Weather Research Forecast model （WRF）, occurred in central Oklahoma on 20 May 1977. This simulation was used to study the application of BGM methods in the meso-scale strong convective Ensemble Prediction System （EPS）. We compared the forecasting skills of EPS by different pertubation methods, like Monte-Carlo and BGM. The results show that the ensemble average forecast based on Monte-Carlo with statistics meaning is superior to the single-deterministic prediction, but a less dynamic process of the method leads to a smaller spread than expected. The fast-growth errors of BGM are comparable to the actual short-range forecast error and a more appropriate ensemble spread. Considering evaluation indexes and scores, the forecast skills of EPS by BGM is higher than Monte-Carlo＇s. Furthermore, various breeding cycles have different effects on precipitation and non-precipitation fields, confirmation of reasonable cycles need consider balance between variables.

AN ENSEMBLE FORECAST EXPERIMENT OF A LANDING TYPHOON

Based on the Global Regional Assimilation and Prediction System-Tropical Cyclone Model(GRAPES-TCM),an ensemble forecast experiment was performed,in which Typhoon Wipha during the period immediately prior to landfall was selected for the study and the breeding of growing mode(BGM) method was used to perturb the initial conditions of the vortex field and the environment field.The results of the experiment indicate that each member had a different initial status in BGM processing and they show a reasonable spread among members along with the forecast phase.Changes in the large-scale field,thermodynamic structure,and spread among members took place when Wipha made landfall.The steering effect of the large-scale field and the interaction between the thermodynamics and the dynamics resulted in different tracks of the members.Meanwhile,the forecast uncertainty increased.In summary,the ensemble mean did not perform as well as the control forecast,but the cluster mean provided some useful information,and performed better than the control in some instances.The position error was 34 km for 24 h forecast,153 km for 48 h forecast,and 191 km for 66 h forecast.The strike probability chart qualitatively described the forecast uncertainty.

Application of Gaussian Weight to Improve Perturbation Features of Convection-Permitting Ensemble Forecast Based on Local Breeding of Growing Modes

Local breeding of growing modes(LBGM)is a method used to generate initial condition perturbation(ICP)for convection-permitting ensemble forecasts.Equal weights(EWs)are usually presumed in LBGM during the localization of ICP,without considering different contributions of the grid points within the local radius.To address this problem,Gaussian weights(GWs)are proposed in this study,which can accommodate the varied influences of the grids inside the local radius on the central grid through a Gaussian function.Specifically,two convection-permitting ensemble forecast experiments based on LBGM with GWs and EWs are compared and analyzed respectively for two squall line cases.The results showed that the use of the GWs intensified the local characteristics of the ICP and made the distribution of the ICP fields more flow-dependent.Kinetic energy spectrum of the ICP indicated that there could be more large-scale information in the ICP by using the GWs.In addition,mesoscale information also improved slightly.For forecast of nonprecipitation variables,GWs improved the relationship between the root-mean-square error and the spread and contributed to the forecasting accuracy of wind,temperature,geopotential height,and humidity.For the precipitation forecast,GWs simulated the precipitation structure successfully and provided better probability forecasting during the evolution of the two squall line processes than the EWs.

Modern Ecological Chicken Raising and Its Research Progress

Modern ecological breeding has the characteristics of protecting the ecological environment,health,nutrition,delicious,and so on.In the ecological breeding of traditional breeding chicken,using non antibiotic breeding,traditional Chinese medicine and other breeding technologies can not only obtain green,non-harmful and safe food products,but also reduce the cost of farmers and provide breeding efficiency This is a sustainable development path.This paper gave a brief overview of this field.

A Convection-Allowing Ensemble Forecast Based on the Breeding Growth Mode and Associated Optimization of Precipitation Forecast

A convection-allowing ensemble forecast experiment on a squall line was conducted based on the breeding growth mode （BGM）. Meanwhile, the probability matched mean （PMM） and neighborhood ensemble probability （NEP） methods were used to optimize the associated precipitation forecast. The ensemble forecast predicted the precipita- tion tendency accurately, which was closer to the observation than in the control forecast. For heavy rainfall, the pre- cipitation center produced by the ensemble forecast was also better. The Fractions Skill Score （FSS） results indicated that the ensemble mean was skillful in light rainfall, while the PMM produced better probability distribution of pre- cipitation for heavy rainfall. Preliminary results demonstrated that convection-allowing ensemble forecast could im- prove precipitation forecast skill through providing valuable probability forecasts. It is necessary to employ new methods, such as the PMM and NEP, to generate precipitation probability forecasts. Nonetheless, the lack of spread and the overprediction of precipitation by the ensemble members are still problems that need to be solved.