Doppler Lidar Evaluation of HRRR Model Skill at Simulating Summertime Wind Regimes in the Columbia River Basin during WFIP2

Complex-terrain locations often have repeatable near-surface wind patterns, such as synoptic gap flows and local thermally forced flows. An example is the Columbia River Valley in east-central Oregon-Washington, a significant wind energy generation region and the site of the Second Wind Forecast Improvement Project (WFIP2). Data from three Doppler lidars deployed during WFIP2 define and characterize summertime wind regimes and their large-scale contexts, and provide insight into NWP model errors by examining differences in the ability of a model [NOAA's High-Resolution Rapid Refresh (HRRR version 1)] to forecast wind speed profiles for different flow regimes. Seven regimes were identified based on daily time series of the lidar-measured rotor-layer winds, which then suggested two broad categories. First, in three of the regimes the primary dynamic forcing was the large-scale pressure gradient. Second, in two other regimes the dominant forcing was the diurnal heating-cooling cycle (regional sea-breeze-type dynamics), including the marine intrusion previously described, which generates strong nocturnal winds over the region. For the large-scale pressure gradient regimes, HRRR had wind speed biases of similar to 1 m s(-1) and RMSEs of 2-3 m s(-1). Errors were much larger for the thermally forced regimes, owing to the premature demise of the strong nocturnal flow in HRRR. Thus, the more dominant the role of surface heating in generating the flow, the larger the errors. Major errors could result from surface heating of the atmosphere, boundary layer responses to that heating, and associated terrain interactions. Measurement/modeling research programs should be designed to determine which of these modeled processes produce the largest errors, so those processes can be improved and errors reduced. SIGNIFICANCE STATEMENT Modeling and forecasting low-level winds over complex terrain are a significant challenge. Here we verify NOAA's HRRR model against wind speed data from three Doppler lidars at a complex-terrain location in central Oregon and Washington. We grouped summertime days according to daily patterns or regimes of wind behavior. Regimes where synoptic pressure gradients dominated the physical forcing showed model errors of 2-3 m s(-1) rms. Regimes where the forcing was dominated by thermal contrast-regional sea-breeze type forcing-had much larger errors, reaching twice as big. The more dominant the role of surface heating in generating the flow, the larger the model errors. Characterizing and diagnosing model errors in this way can be an important step in improving NWP model skill.