11B.1 Development of an Urbanized Land Data Assimilation System: RMAPS-LDAS

Wednesday, 15 January 2020: 3:00 PM
104C (Boston Convention and Exhibition Center)
Chengcheng Huang, Institute of Urban Meteorology, China Meteorological Administration, Beijing, China; and M. Barlage, S. Miao, F. Chen, and Y. Zhang

An urbanized land data assimilation system (LDAS) with a spatial resolution of 1 km is developed to provide a better estimation of land surface elements (e.g., soil moisture and temperature, road and roof temperature, etc.) for a regional weather forecast system named Rapid-refresh Multi-scale Analysis and Prediction System (RMAPS) in order to enhance the precision of short-term regional weather forecasts. 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 underlying surfaces. The RMAPS-LDAS runs offline with the input of fused meteorological data from in-situ observations and gridded meteorological data. Some static data (e.g., soil texture classes and monthly green vegetation fraction) are updated using local and satellite-based sources to improve the land modeling accuracy. The structure of the coupled Noah-BEP-BEM modeling system is reorganized to improve the computational and storage efficiency, which makes RMAPS-LDAS an operationally applicable system for regional weather forecasts. Evaluation results show that the land surface states simulated by RMAPS-LDAS improve temporal and spatial patterns of initial conditions and can improve short-term weather forecasts.
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