Search Results
Abstract
Boundary layer wind profilers are increasingly being used in applications that require high-quality, rapidly updated winds. An example of this type of application is an airport wind hazard warning system. Wind shear can be a hazard to flight operations and is also associated with the production of turbulence. A method for calculating wind and wind shear using a linear wind field assumption is presented. This method, applied to four- or five-beam profilers, allows for the explicit accounting of the measurable shear terms. An error analysis demonstrates why some shears are more readily estimated than others, and the expected magnitudes of the variance for the wind and wind shear estimates are given. A method for computing a quality control index, or confidence, for the calculated wind is also presented. This confidence calculation is based on an assessment of the validity of the assumptions made in the calculations. Confidence values can be used as a quality control metric for the calculated wind and can also be used in generating a confidence-weighted average wind value from the rapid update values. Results are presented that show that errors in the wind estimates are reduced after removing values with low confidence. The wind and confidence methods are implemented in the NCAR Wind and Confidence Algorithm (NWCA), and have been used with the NCAR Improved Moments Algorithm (NIMA) method for calculating moments and associated moment confidence from Doppler spectra. However, NWCA may be used with any moment algorithm that also computes a first moment confidence. For example, a very simple confidence algorithm can be defined in terms of the signal-to-noise ratio.
Abstract
Boundary layer wind profilers are increasingly being used in applications that require high-quality, rapidly updated winds. An example of this type of application is an airport wind hazard warning system. Wind shear can be a hazard to flight operations and is also associated with the production of turbulence. A method for calculating wind and wind shear using a linear wind field assumption is presented. This method, applied to four- or five-beam profilers, allows for the explicit accounting of the measurable shear terms. An error analysis demonstrates why some shears are more readily estimated than others, and the expected magnitudes of the variance for the wind and wind shear estimates are given. A method for computing a quality control index, or confidence, for the calculated wind is also presented. This confidence calculation is based on an assessment of the validity of the assumptions made in the calculations. Confidence values can be used as a quality control metric for the calculated wind and can also be used in generating a confidence-weighted average wind value from the rapid update values. Results are presented that show that errors in the wind estimates are reduced after removing values with low confidence. The wind and confidence methods are implemented in the NCAR Wind and Confidence Algorithm (NWCA), and have been used with the NCAR Improved Moments Algorithm (NIMA) method for calculating moments and associated moment confidence from Doppler spectra. However, NWCA may be used with any moment algorithm that also computes a first moment confidence. For example, a very simple confidence algorithm can be defined in terms of the signal-to-noise ratio.
