Activity Number:
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28
- Computation, Design, and Quality Assurance of Physical Science and Engineering Applications
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Type:
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Contributed
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Date/Time:
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Sunday, August 8, 2021 : 1:30 PM to 3:20 PM
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Sponsor:
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Section on Physical and Engineering Sciences
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Abstract #317865
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Title:
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Missing-Data Coherency Estimation
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Author(s):
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Charlotte Haley*
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Companies:
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Argonne National Laboratory
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Keywords:
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Time Series;
Spectrum analysis;
Coherency;
Wind speed;
Multitaper;
Missing-data problem
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Abstract:
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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.
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Authors who are presenting talks have a * after their name.
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