Numerical prediction of climate/weather/environment is an important source for adequate policy making in an era of changing climate. It requires a coupled modeling system, such as atmosphere-land surface-chemistry, etc.; its performance can be improved through better estimation of parameters and initial conditions. Numerical climate/weather models provide not only the future state of climate/weather but also the analysis data of model variables at given horizontal/vertical grid resolutions, which are useful especially in data void areas. Some recent efforts to improve the regional weather/climate/environment prediction will be introduced as an integrated approach, such as developing/improving parameterizations of subgrid-scale phenomena, estimating optimal parameter values (especially for the quantitative precipitation forecasting), seeking an optimized set of parameterization schemes, combining optimizations of parameterization schemes and parameter values sequentially (i.e., superparameterization), and applying a hybrid ensemble-variational data assimilation, by employing the coupled models (e.g., WRF-Noah-MP and WRF-Chem) and satellite data. Based on these efforts, we have developed an integrated regional climate prediction system ― the Regional Environment/Climate Integrated Prediction System of Ewha Womans University (RECIPE). The RECIPE is based on a coupled modeling system of meteorology (WRF) and land surface (Noah-MP) with some improved features in the land surface processes, including vegetation phenology, stem index, and carbon assimilation and allocation. It is also equipped with the state-of-art techniques, including optimal parameter estimation using an evolutionary algorithm, and advanced data assimilation.