Friday, 24 June 2016: 3:45 PM
The Canyons (Sheraton Salt Lake City Hotel)
The synthesis of new measurement technologies with advances in high performance computing provides an unprecedented opportunity to advance our understanding of the atmosphere, particularly with regard to the complex flows in the atmospheric boundary layer. To assess current measurement capabilities for quantifying features of atmospheric flow within wind farms, the U.S. Dept. of Energy sponsored the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign at the Boulder Atmospheric Observatory (BAO) in spring 2015. Herein, we summarize the XPIA field experiment design, highlight novel approaches to boundary-layer measurements, and quantify measurement uncertainties associated with these experimental methods. Line-of-sight velocities measured by scanning lidars and radars exhibit close agreement with tower measurements, despite differences in measurement volumes. Virtual towers of wind measurements, from multiple lidars or dual radars, also agree well with tower and profiling lidar measurements. Estimates of winds over volumes, conducted with rapid lidar scans, agree with those from scanning radars, enabling assessment of spatial variability. Microwave radiometers provide temperature profiles within and above the boundary layer with approximately the same uncertainty as operational remote sensing measurements. Using a motion platform, we assess motion-compensation algorithms for lidars to be mounted on offshore platforms. Finally, we highlight cases that could be useful for validation of large-eddy simulations or mesoscale numerical weather prediction, providing information on accessing the archived dataset. We conclude that modern remote sensing systems provide a generational improvement in observational capabilities, enabling resolution of refined processes critical to understanding inhomogeneous boundary-layer flows such as those found in wind farms.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner