Turbulence Dissipation Rates from Wind Profiling Radars at the BAO and in the Second Wind Forecast Improvement Project

Katherine McCaffrey

PSL Boundary Layer Observations and Processes Team

Tuesday, Apr 04, 2017, 2:00 pm
DSRC Room 2A305

Abstract

When forecasting wind speed for energy production, turbulence parameterizations are crucial for predicting wind plant performance. Recent research shows that the turbulence (eddy) dissipation rate in planetary boundary layer (PBL) parameterization schemes introduces significant uncertainty in the Weather Research and Forecasting model. Locations of complex topography are especially susceptible to these errors since the flows tend to be more turbulent than regions with flat topography. Thus developing the capability to measure dissipation rates in complex terrain will allow for identifying the weaknesses in the model. We use data from 915-MHz and 449-MHz wind profiling radars (WPRs) at the Boulder Atmospheric Observatory to identify the optimal set-up and post-processing procedures for accurately measuring eddy dissipation rates from Doppler spectral widths. Comparisons with 6 levels of sonic anemometers on a 300m tower during the XPIA field campaign showed promising results, which are now being applied to a 915-MHz WPR in Wasco, OR as part of the second Wind Forecasting Improvement Project (WFIP2). This large collaborative project, including scientists from all four divisions of NOAA-ESRL, aims to improve the ESRL HRRR forecast models in complex topography of the Columbia River Basin, using a suite of field observations including the Wasco WPR measuring turbulence. Early results from the observational portion of the experiment will be shown, including turbulence, wind, and temperature profiles, PBL heights, and surface radiation measurements. Each of these observations indicates that the diurnal cycle of heating and mixing is over-estimated in the model. Experimental models are being developed to improve the PBL parameterizations that impact these quantities which will ultimately improve the forecasting of winds in this region of complex terrain and elsewhere.