Assessing Microwave Radiometer's Retrievals and Radio Acoustic Sounding System's Measurements for Wind Energy Applications

To assess current remote sensing capabilities for wind energy applications, a remote sensing system evaluation study called XPIA (eXperimental Planetary boundary layer Instrument Assessment), was held in 2015 at NOAA's Boulder Atmospheric Observatory (BAO) facility. Several remote sensing platforms were evaluated to determine their suitability for the verification and validation processes used to test the accuracy of numerical weather prediction models in future field campaigns, particularly the Second Wind Forecast Improvement Project (WFIP2) that will start in fall 2015. WFIP2 is aimed at improving the parameterizations of WRF-based models in complex terrain for wind energy purposes. The evaluation of these platforms was performed with respect to well-defined references, the BAO's 300-m tower equipped at 6 levels (50, 100, 150, 200, 250, and 300m) with 12 sonic anemometers and T/RH sensors, and approximately 60 radiosonde launches. In this study we will show how these radiosonde launches and the 300-m tower measurements were used to validate temperature profiles observed by two microwave radiometers (MWR) located next to each other, as well as virtual temperature measured by a co-located radio acoustic sounding system (RASS). Results indicate a mean absolute error in the temperature retrieved by the MWRs below 1.5°C in the lower part of the atmosphere, and a mean absolute error in the virtual temperature measured by the RASS very well below 1°C in the part of the atmosphere covered by RASS measurements, when compared to the radiosonde and tower measurements. Also, the correlation coefficient between the lapse rate measured by the microwave radiometer and the tower measurements between 50 and 300 m was 0.92, while the correlation coefficient between the lapse rate measured by the RASS and the tower measurements was equal to 0.81, proving that these remote sensing instruments can also provide accurate information on atmospheric stability conditions within the wind turbine rotor layer.