Assessing Atmospheric Profiles from Microwave Radiometers and Radio Acoustic Sounding Systems

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 spring 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. 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 65 radiosonde launches. In this study we will show how these reference 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 1.5oC in the lower kilometers of the atmosphere, and a mean absolute error in the virtual temperature measured by the RASS very well below 1oC in the part of the atmosphere covered by RASS measurements (1-2 km). 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 both these remote sensing instruments can provide accurate information on atmospheric stability conditions in the lower boundary layer. Finally, our study unsurprisingly revealed that relative humidity profiles measured by the MWR lack high resolution details compared to radiosonde measurements and for this reason we investigate the retrieval of high-resolution atmospheric humidity profiles by synergetic use of a MWR and wind profiler radar.