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Turbulence Time Series Data Hole Filling using Karhunen-Loeve and ARIMA methods

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M.P.J.L. Chang, H. Nazari, C.O. Font, G.C. Gilbreath, E Oh

Data Analysis, Statistics and Probability · Submitted 22 Jan 2007

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim We report on the quality of the correction by examining the Intrinsic Mode Functions generated by Empirical Mode Decomposition.

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arXiv IDphysics/0701238 (version 1)
Pith IDMBX2JWOH, Pith's permanent record of this paper and its review
CitationC.O. Font, E Oh, G.C. Gilbreath, H. Nazari, M.P.J.L. Chang. "Turbulence Time Series Data Hole Filling using Karhunen-Loeve and ARIMA methods." arXiv:physics/0701238 (2007). https://pith.science/paper/MBX2JWOH
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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 3,660 input tokens.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.16 · human participants 0.02 · controlled comparison 0.11 · randomized assignment 0.01 · states quantitative result 0.06 · compares with prior results 0.81 · mentions code or data availability 0.03.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

Measurements of optical turbulence time series data using unattended instruments over long time intervals inevitably lead to data drop-outs or degraded signals. We present a comparison of methods using both Principal Component Analysis, which is also known as the Karhunen--Loeve decomposition, and ARIMA that seek to correct for these event-induced and mechanically-induced signal drop-outs and degradations. We report on the quality of the correction by examining the Intrinsic Mode Functions generated by Empirical Mode Decomposition. The data studied are optical turbulence parameter time series from a commercial long path length optical anemometer/scintillometer, measured over several hundred metres in outdoor environments.

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What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 Measurements of optical turbulence time series data using unattended instruments over long time intervals inevitably lead to data drop-outs or degraded signals. background 1.00 0.22 0.02 asserted 0.98
s1 We present a comparison of methods using both Principal Component Analysis, which is also known as the Karhunen--Loeve decomposition, and ARIMA that seek to correct for these event-induced and mechanically-induced signal drop-outs and degradations. contribution 0.92 0.88 0.08 asserted 0.96
s2 We report on the quality of the correction by examining the Intrinsic Mode Functions generated by Empirical Mode Decomposition. method 0.85 0.91 0.11 asserted 0.94
s3 The data studied are optical turbulence parameter time series from a commercial long path length optical anemometer/scintillometer, measured over several hundred metres in outdoor environments. method 0.91 0.83 0.03 asserted 0.99

What kind of paper the classifier reports this is: method or tool 0.74 · evidence from analysis of existing data 0.74.

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Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

Measurements of optical turbulence time series data using unattended instruments over long time intervals inevitably lead to data drop-outs or degraded signals. We present a comparison of methods using both Principal Component Analysis, which is also known as the Karhunen--Loeve decomposition, and ARIMA that seek to correct for these event-induced and mechanically-induced signal drop-outs and degradations. We report on the quality of the correction by examining the Intrinsic Mode Functions generated by Empirical Mode Decomposition. The data studied are optical turbulence parameter time series from a commercial long path length optical anemometer/scintillometer, measured over several hundred metres in outdoor environments.

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