Short-term Weather Forecast Platform Based on the WRF-GSI Data Model and Radar Data
Background and contents:
This platform relies on the analysis and application of WRF-GSI Data Model and Radar Data to forecast the short-term severe weather. Such system consists of the mesoscale numerical model, multi-source data assimilation system, the improvement to localization of model and assimilation system, post-processing to output, the analysis and application of doppler weather radar data. Among those, the mesoscale system adopts advanced WRF model system, which takes NCEP GFS global model data in the United States for the initial and boundary conditions, at the same time, it utilizes the GSI data assimilation system of NCEP business to assimilate conventional observation data and sounding data, radar data and satellite data, combining observations and the initial data of the model into the WRF model.
Functions and features:
1.It Covers numerical model pretreatment, data assimilation, model integration, and analysis and application of model results, can be directly applied to forecasting system.
2.Revise to the localization results of forecasting model and data assimilation system, it make the general model system is applicable to local business.
3.The platform fully utilizes radar data, the conventional observation data and satellite data, through post-processing, it organically combines the weather analysis and mode forecast.
1.Improvements to the localization of WRF Mode System:
1.1.Mode evaluation：Conventional-elements-validation，Precipitation QPF validation， Validation based on cloud cover
1.2.Mode revise：Training of mode power revise，nested grid design，optimization to reanalysis
1.3.Parameter revise：localized construction to the parameter of Cloud micro-physical, Cumulus convection, boundary layer, road condition； eradicate using validation results to revise parameter
1.4.Integrated forecast: Integrated forecast based on parameters, Integrated forecast based on the initial conditions, the analysis and application of Integrated forecast
2.Improvement to the GSI Data assimilation system:
2.1.Optimized choice of assimilation data sorts: Conventional data, radar Data, Cloud observation data, sounding data,etc.
2.2.Optimized choice to assimilation way: Cyclic assimilation, choice of assimilation time interval, inversion scheme selection
2.3.Outcome Assessment of assimilation: Impact assessment to different data, Short-term impact assessment, Long-term impact assessment, Impact of Specific factors, etc.
3.Technology of Radar data analysis and application:
Radar data analysis and application mainly includes quality control of radar data, and that by using the three dimensional distribution characteristics of radar reflectivity, divides convection cloud system into nuclear area, stratiform precipitation area, transitional anvil cloud area and thick anvil cloud area. The division to these areas is more in line with the synoptic characteristics of the convective system, the division to convection system can make the weatherman do more intuitive and clear analysis to the radar data.
3.1.Not only realize the division to radar observation data, but also realize the division to simulation data based on model
3.2.Combine with the static satellite data to make joint inversion to the characteristic of convection system.