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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
Abstract #317865
Title: Missing-Data Coherency Estimation
Author(s): Charlotte Haley*
Companies: Argonne National Laboratory
Keywords: Time Series; Spectrum analysis; Coherency; Wind speed; Multitaper; Missing-data problem

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.

Authors who are presenting talks have a * after their name.

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