ANALYSIS OF THE PRECIPITATION CLIMATE SIGNAL USING EMPIRICAL MODE DECOMPOSITION (EMD) OVER THE CASPIAN CATCHMENT AREA

<p>In this paper, we employ Empirical Mode Decomposition (EMD) together with Hilbert Transform to analyze precipitation time series over the Caspian Sea catchment. Several studies have shown that EMD can extract nonlinear and non-stationary signals better than Fast Fourier Transform (FFT) and...

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Main Authors: F. Sabzehee, V. Nafisi, S. Iran Pour, B. D. Vishwakarma
Format: Article
Language:English
Published: Copernicus Publications 2019-10-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W18/923/2019/isprs-archives-XLII-4-W18-923-2019.pdf
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author F. Sabzehee
V. Nafisi
S. Iran Pour
B. D. Vishwakarma
author_facet F. Sabzehee
V. Nafisi
S. Iran Pour
B. D. Vishwakarma
author_sort F. Sabzehee
collection DOAJ
description <p>In this paper, we employ Empirical Mode Decomposition (EMD) together with Hilbert Transform to analyze precipitation time series over the Caspian Sea catchment. Several studies have shown that EMD can extract nonlinear and non-stationary signals better than Fast Fourier Transform (FFT) and Wavelet Transform. EMD decomposes the time series into a finite number of Intrinsic Mode Functions (IMFs) in the time-frequency domain, while FFT helps us operate either in the time or the frequency domain, which fuels limitations such as the inability of nonstationary signal processing and the lack of time transparency. Although Wavelet Transform is shown to be better than FFT, it fails to detect the instantaneous frequencies and needs to have prior information about characteristics of the data. On the other hand, EMD has shown that it is almost able to determine the signal characteristics with no previous assumptions to estimate the instantaneous frequencies of the signal. In this work, EMD is applied to identify the main frequencies of precipitation time series. Thereafter, a statistical procedure is used to identify the prominent IMF of the original signal.</p><p>We use the correlation coefficient, Minkowski distance and variance test to extract the relevant and prominent IMFs. The results show that IMF 1–3 are the relevant components and are related to annual and biennial variations of precipitation time series over the Caspian catchment during 2003–2016, respectively.</p>
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spelling doaj.art-b3a9b20ad7c74a939866916798551abf2022-12-21T23:05:21ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342019-10-01XLII-4-W1892392910.5194/isprs-archives-XLII-4-W18-923-2019ANALYSIS OF THE PRECIPITATION CLIMATE SIGNAL USING EMPIRICAL MODE DECOMPOSITION (EMD) OVER THE CASPIAN CATCHMENT AREAF. Sabzehee0V. Nafisi1S. Iran Pour2B. D. Vishwakarma3Geomatics Engineering, Faculty of Civil Engineering and Transportation, University of Isfahan, Isfahan, IranGeomatics Engineering, Faculty of Civil Engineering and Transportation, University of Isfahan, Isfahan, IranInstitute of Geodesy, University of Stuttgart, Stuttgart, GermanySchool of Geographical Sciences, University of Bristol, University Road, Bristol BS8 1SS, UK<p>In this paper, we employ Empirical Mode Decomposition (EMD) together with Hilbert Transform to analyze precipitation time series over the Caspian Sea catchment. Several studies have shown that EMD can extract nonlinear and non-stationary signals better than Fast Fourier Transform (FFT) and Wavelet Transform. EMD decomposes the time series into a finite number of Intrinsic Mode Functions (IMFs) in the time-frequency domain, while FFT helps us operate either in the time or the frequency domain, which fuels limitations such as the inability of nonstationary signal processing and the lack of time transparency. Although Wavelet Transform is shown to be better than FFT, it fails to detect the instantaneous frequencies and needs to have prior information about characteristics of the data. On the other hand, EMD has shown that it is almost able to determine the signal characteristics with no previous assumptions to estimate the instantaneous frequencies of the signal. In this work, EMD is applied to identify the main frequencies of precipitation time series. Thereafter, a statistical procedure is used to identify the prominent IMF of the original signal.</p><p>We use the correlation coefficient, Minkowski distance and variance test to extract the relevant and prominent IMFs. The results show that IMF 1–3 are the relevant components and are related to annual and biennial variations of precipitation time series over the Caspian catchment during 2003–2016, respectively.</p>https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W18/923/2019/isprs-archives-XLII-4-W18-923-2019.pdf
spellingShingle F. Sabzehee
V. Nafisi
S. Iran Pour
B. D. Vishwakarma
ANALYSIS OF THE PRECIPITATION CLIMATE SIGNAL USING EMPIRICAL MODE DECOMPOSITION (EMD) OVER THE CASPIAN CATCHMENT AREA
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title ANALYSIS OF THE PRECIPITATION CLIMATE SIGNAL USING EMPIRICAL MODE DECOMPOSITION (EMD) OVER THE CASPIAN CATCHMENT AREA
title_full ANALYSIS OF THE PRECIPITATION CLIMATE SIGNAL USING EMPIRICAL MODE DECOMPOSITION (EMD) OVER THE CASPIAN CATCHMENT AREA
title_fullStr ANALYSIS OF THE PRECIPITATION CLIMATE SIGNAL USING EMPIRICAL MODE DECOMPOSITION (EMD) OVER THE CASPIAN CATCHMENT AREA
title_full_unstemmed ANALYSIS OF THE PRECIPITATION CLIMATE SIGNAL USING EMPIRICAL MODE DECOMPOSITION (EMD) OVER THE CASPIAN CATCHMENT AREA
title_short ANALYSIS OF THE PRECIPITATION CLIMATE SIGNAL USING EMPIRICAL MODE DECOMPOSITION (EMD) OVER THE CASPIAN CATCHMENT AREA
title_sort analysis of the precipitation climate signal using empirical mode decomposition emd over the caspian catchment area
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W18/923/2019/isprs-archives-XLII-4-W18-923-2019.pdf
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AT siranpour analysisoftheprecipitationclimatesignalusingempiricalmodedecompositionemdoverthecaspiancatchmentarea
AT bdvishwakarma analysisoftheprecipitationclimatesignalusingempiricalmodedecompositionemdoverthecaspiancatchmentarea