Open AccessIdentifying Doppler Velocity Contamination Caused by Migrating Birds. Part II: Bayes Identification and Probability Tests
Author(s) -
Shun Liu,
Qin Xu,
Pengfei Zhang
Publication year - 2005
Publication title -
journal of atmospheric and oceanic technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.774
H-Index - 124
eISSN - 1520-0426
pISSN - 0739-0572
DOI - 10.1175/jtech1758.1
Subject(s) - bayes' theorem , identification (biology) , ground truth , computer science , bayesian probability , probabilistic logic , flag (linear algebra) , decision rule , statistics , quality (philosophy) , mathematics , data mining , artificial intelligence , physics , botany , quantum mechanics , pure mathematics , biology , algebra over a field
Based on the Bayesian statistical decision theory, a probabilistic quality control (QC) technique is developed to identify and flag migrating-bird-contaminated sweeps of level II velocity scans at the lowest elevation angle using the QC parameters presented in Part I. The QC technique can use either each single QC parameter or all three in combination. The single-parameter QC technique is shown to be useful for evaluating the effectiveness of each QC parameter based on the smallness of the tested percentages of wrong decision by using the ground truth information (if available) or based on the smallness of the estimated probabilities of wrong decision (if there is no ground truth information). The multiparameter QC technique is demonstrated to be much better than any of the three single-parameter QC techniques, as indicated by the very small value of the tested percentages of wrong decision for no-flag decisions (not contaminated by migrating birds). Since the averages of the estimated probabilities of wrong decision are quite close to the tested percentages of wrong decision, they can provide useful information about the probability of wrong decision when the multiparameter QC technique is used for real applications (with no ground truth information).