气候/天气/环境的数字预测是在气候变化时代的适当政策制定的重要来源。它需要一个耦合的建模系统,例如大气层地面化学;通过更好地估计参数和初始条件,可以提高其性能。数值气候/天气/环境模型不仅提供其未来状态,还提供给定网格大小的分析数据,这些数据在数据空隙区域中很有用。Recent efforts to improve regional climate/weather/environment prediction will be introduced as an integrated approach: estimating optimal parameter values, seeking an optimized set of parameterization schemes, combining optimizations of parameterization schemes and parameter values sequentially (i.e., opti-parameterization), and applying a hybrid ensemble-variational data assimilation through the coupled models (e.g., WRF-NOAH-MP和WRF-CHEM)和卫星数据。