- Nowcasting (NOW) Model (∆x of 5 and 2.5 km): uses input from the Variational Doppler Radar Analysis System (VDRAS) for 6 h real time forecasts, with ingested data from seven S-band weather radar and all AWS sites.
- Land data assimilation (LDAS) Model (∆x of 3 and 1 km): The Noah land surface model and the multi-layer building energy model BEP-BEM are coupled to obtain a better representation of land surface states for both natural and urban surfaces.
- Short Term (ST) Model (∆x = 9 and 3 km): uses WRF Data Assimilation (WRFDA), and either the WRF Noah (for rural grid points) or SLUCM (for urban grid points) land-surface modules for operational 72 h forecasts, for which regional and local data are assimilated.
- Urban Model (∆x =1 km): for urban weather forecasts with the multi-level BEP + Building Energy Model (BEM) urban PBL modules for 24 h real time (but not yet operational) forecasts and research studies, where BEM, BEP, and their urban LU/LC input data are described below and where its AWS assimilated input weather-data were described above.
- Rapid-refresh Integrated Seamless Ensemble (RISE) Model: combines observations into the NOW, ST, and Urban model forecasts for objective 12 h forecasts, where its input (QPE) are radar data and are calibrated by AWS rain-gauge observations.
- CHEM Model (∆x = 9 km and 3 km): for 96 h chemical forecasts from the WRF-Chem model.
- Large eddy simulation (LES) Model (∆x = 37 m): for complex terrain.
RMAPS analysis and forecast products are operationally provided to Beijing Meteorological Service (BMS) for weather warning and many forecasting applications, e.g., urban flooding, air pollution, weather modification, energy consumption, and emergency-response management. Model evaluations, application examples, and future directions for research, application, and service will be given.