Search Results
Abstract
The National Center for Atmospheric Research (NCAR) Improved Moments Algorithm (NIMA) calculates the first and second moments (radial velocity and spectral width) of wind-profiler Doppler spectra and provides an evaluation of confidence in these calculations. The first moments and their confidences are used by the NCAR Winds And Confidence Algorithm (NWCA), to estimate the horizontal wind. NIMA–NWCA has been used for several years in a real-time application for three wind profilers in Juneau, Alaska. This paper presents results of an effort to evaluate the first moments produced by NIMA and horizontal winds produced by NIMA–NWCA through comparison with estimates from “human experts” and also presents a comparison of NIMA–NWCA winds with in situ aircraft measurements. NIMA uses fuzzy logic to separate the atmospheric component of Doppler spectra from ground clutter and other sources of interference. The fuzzy logic rules are based on similar features humans consider when identifying atmospheric and contamination signals in Doppler spectra. Furthermore, NIMA attempts to mimic the human experts’ assignment of confidence to the moments. A Human Moment Analysis (HMA) tool was developed to assist the human experts in quantifying moments. This tool is described and a methodology of tuning NIMA rules based on human truth specification is presented. NIMA performed well on a dataset specifically chosen to be difficult. The average absolute error between the HMA estimate and NIMA-derived radial wind estimate was slightly more than 0.3 m s−1 when data with low NIMA confidence were excluded, which is comparable to the Doppler spectrum resolution. The correlation between winds derived from NIMA–NWCA and from HMA first-moment estimates exceeded 0.96 when the data with low NWCA confidence were excluded. The correlation coefficient between NIMA winds and in situ measurements by aircraft was 0.93 when aircraft winds that were believed to be accurate were used.
Abstract
The National Center for Atmospheric Research (NCAR) Improved Moments Algorithm (NIMA) calculates the first and second moments (radial velocity and spectral width) of wind-profiler Doppler spectra and provides an evaluation of confidence in these calculations. The first moments and their confidences are used by the NCAR Winds And Confidence Algorithm (NWCA), to estimate the horizontal wind. NIMA–NWCA has been used for several years in a real-time application for three wind profilers in Juneau, Alaska. This paper presents results of an effort to evaluate the first moments produced by NIMA and horizontal winds produced by NIMA–NWCA through comparison with estimates from “human experts” and also presents a comparison of NIMA–NWCA winds with in situ aircraft measurements. NIMA uses fuzzy logic to separate the atmospheric component of Doppler spectra from ground clutter and other sources of interference. The fuzzy logic rules are based on similar features humans consider when identifying atmospheric and contamination signals in Doppler spectra. Furthermore, NIMA attempts to mimic the human experts’ assignment of confidence to the moments. A Human Moment Analysis (HMA) tool was developed to assist the human experts in quantifying moments. This tool is described and a methodology of tuning NIMA rules based on human truth specification is presented. NIMA performed well on a dataset specifically chosen to be difficult. The average absolute error between the HMA estimate and NIMA-derived radial wind estimate was slightly more than 0.3 m s−1 when data with low NIMA confidence were excluded, which is comparable to the Doppler spectrum resolution. The correlation between winds derived from NIMA–NWCA and from HMA first-moment estimates exceeded 0.96 when the data with low NWCA confidence were excluded. The correlation coefficient between NIMA winds and in situ measurements by aircraft was 0.93 when aircraft winds that were believed to be accurate were used.
