Modeling meso-gamma scale weather flows using nested-grid WRF LES scale models and FDDA for a wind farm in Northern Colorado

In collaboration with Xcel Energy and Vasaila Inc., the National Center for Atmospheric Research (NCAR) conducts modeling study to evaluate the existing and the enhanced intensive observation systems for wind power nowcasting and short-range forecasting at a northern Colorado wind farm. In an effort to study the microscale weather flow features at the wind farm, the NCAR WRF (Weather Research and Forecasting model) based Real-Time Four-Dimensional Data Assimilation (RTFDDA) and forecasting system is employed to perform multiscale nested-grid simulations from synoptic scales to microscales with LES modeling grids. The observational data include ten met-towers, one 915Hz wind profiler and a Windcube Doppler lidar, in addition to the in-farm met-towers and wind speed reports from more than 300 wind turbines and a variety of operational standard weather observations. The WRF-RTFDDA 4-dimensional data assimilation algorithm allows the spread and propagation of observation information in the WRF model space (x, y, z and time) with weighting functions built according to the observation location, time and local terrain and flow features. This paper focuses on feasibility study of extending WRF-FDDA for assimilation of the dense wind farm observations on sub-kilometer grid models (DX=100 – 900m) and several approaches for dealing with the representativeness issue and local correlation structures in order to maximize the data impact on analysis and nowcasting of the microscale flows in and around the wind farm. Findings from two case studies will be reported at the conference.