基于四维数据同化技术的千米格距网格化气象数据集:构建及初步应用

利用基于张弛逼近的四维数据同化技术，构建了广东深圳的千米格距网格化气象数据集，由于同化了深圳及周边可获得的高频次观测数据，气象数据集基本准确表现出几种关键气象要素的年际变化和月变化特征。在网格化气象数据集基础上开发了“深圳市细网格气候信息平台”，并通过平台推出了若干精细气候数据产品:精细风玫瑰、逐网格风能等。这些数据产品已经在格点气温预报、风能示范项目选址以及详细规划的自然通风评估中发挥了实际作用。这些探索表明，网格化气象数据集的建立，有望为城市的网格化精细管理和建设提供气象科技支撑。 

GRIDDED METEOROLOGICAL DATASET WITH A 1-KM RESOLUTION BY USING FOUR DIMENSIONAL DATA ASSIMILATION TECHNIQUE: ESTABLISHMENT OF THE DATA SET AND PRELIMINARY APPLICATIONS

By using a four-dimensional data assimilation technique based on the nudging method, a gridded meteorological dataset with a resolution of 1 km is established in Shenzhen. The comparison between the model data and the observational data shows that the gridded data can fairly well describe the characteristics of the local climate in Shenzhen, for there have been much observational data with high resolution from multi-sources assimilated in the dataset. Based on the gridded meteorological dataset, the Shenzhen fine-gridded climate information service platform is established, and many fine-scale products on local climate are provided through the platform, i.e. fine-scale wind roses and gridded wind energy distribution. The dataset has already successfully applied in practice such as gridded air temperature prediction, site-selection of wind energy projects and ventilation assessment on detailed urban planning. The current study shows that the establishment of the gridded meteorological dataset can be expected to provide services to gridded municipal management and construction.