Missing-Data Coherency Estimation

• Activity Number: 28 - Computation, Design, and Quality Assurance of Physical Science and Engineering Applications
• Type: Contributed
• Date/Time: Sunday, August 8, 2021 : 1:30 PM to 3:20 PM
• Sponsor: Section on Physical and Engineering Sciences
• Author(s): Charlotte Haley*
• Companies: Argonne National Laboratory
• Keywords: Time Series; Spectrum analysis; Coherency; Wind speed; Multitaper; Missing-data problem

Abstract

Chave recently proposed an estimator for multitaper spectral density where the time series contains missing values. In this article, we generalize this technique to a multitaper estimator of coherence and phase and show that one can also obtain bootstrapped confidence intervals. We give three examples, the first of which is a toy example in which the true coherence is known. In the second example we show that the multitaper missing-data coherence estimator computed on real data with a single gap comprising 11% of the data outperforms the Daniell-smoothed coherence estimator where there are no gaps. Finally, vertical wind speed time series collected by a Doppler lidar is punctuated by gaps at 15-minute intervals, which makes it impossible to observe convective boundary layer processes which typically evolve on time scales less than one hour. Spectrum and coherence estimation using missing-data methods shows boundary layer meteorological features at the time scales of interest.