High-resolution microscale weather and climate (re-)analysis and short-term forecasting at Shenzhen, China

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Thursday, 6 February 2014: 4:45 PM
Room C202 (The Georgia World Congress Center )
Yubao Liu, NCAR, Boulder, CO; and L. Li, Y. Jiang, L. Pan, Y. Liu, W. Y. Y. Cheng, G. Roux, and Y. Zhang

Shenzhen is a major and fast growing city located in the Pearl River Delta in southern China. The municipality covers an area of 2,050 square kilometers covering the metropolitan and the nearby rural areas. In order to improve the weather and climate service to the city, SZMB has implemented a high-density observation-network with advanced remote sensing instruments in the Shenzhen metropolitan and surrounding regions. The observation system includes ultra-dense surface Automatic Weather Station (AWS), wind profilers, radiometers, met-towers, Doppler radars, the Global Positioning System (GPS), lightning, and other platforms. These observational systems/networks provide unique ultra-high spatiotemporal resolution observations for leveraging urban-scale climate reanalysis and numerical weather prediction. Toward this end, the NCAR WRF-based RTFDDA (Realtime Four Dimensional Data Assimilation) forecasting system has been deployed at SZMB and configured for the Shenzhen area. The modeling system contains four nested domains with horizontal grid sizes at 27km, 9km, 3km and 1 km, respectively. The 1km finest-mesh domain covers the Shenzhen municipality, Hong Kong, and neighboring areas. The system has been run to produce 5-year 4D continuous high-resolution climate reanalysis, and also been running in real time to provide rapid-update current weather analysis and forecast, with assimilation of all available weather observations, in particular, the SZMB-operated uniquely-dense observation network. At this conference, we will describe the model system and the observation data, the data quality control and model analysis and forecast performance. Case studies will be presented to illustrate the importance of model system optimization for the region and the data impact, especially radar data on the forecast of high impact weather events.