A skewed perspective of the Indian rainfall–El Niño–Southern Oscillation (ENSO) relationship

<p>Wavelet coherence is a method that is commonly used in hydrology to extract scale-dependent, nonstationary relationships between time series. However, we show that the method cannot always determine why the time-domain correlation between two time series changes in time. We show that, even...

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Main Authors: J. Schulte, F. Policielli, B. Zaitchik
Format: Article
Language:English
Published: Copernicus Publications 2020-11-01
Series:Hydrology and Earth System Sciences
Online Access:https://hess.copernicus.org/articles/24/5473/2020/hess-24-5473-2020.pdf
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author J. Schulte
F. Policielli
B. Zaitchik
author_facet J. Schulte
F. Policielli
B. Zaitchik
author_sort J. Schulte
collection DOAJ
description <p>Wavelet coherence is a method that is commonly used in hydrology to extract scale-dependent, nonstationary relationships between time series. However, we show that the method cannot always determine why the time-domain correlation between two time series changes in time. We show that, even for stationary coherence, the time-domain correlation between two time series weakens if at least one of the time series has changing skewness. To overcome this drawback, a nonlinear coherence method is proposed to quantify the cross-correlation between nonlinear modes embedded in the time series. It is shown that nonlinear coherence and auto-bicoherence spectra can provide additional insight into changing time-domain correlations. The new method is applied to the El Niño–Southern Oscillation (ENSO) and all-India rainfall (AIR), which is intricately linked to hydrological processes across the Indian subcontinent. The nonlinear coherence analysis showed that the skewness of AIR is weakly correlated with that of two ENSO time series after the 1970s, indicating that increases in ENSO skewness after the 1970s at least partially contributed to the weakening ENSO–AIR relationship in recent decades. The implication of this result is that the intensity of skewed El Niño events is likely to overestimate India's drought severity, which was the case in the 1997 monsoon season, a time point when the nonlinear wavelet coherence between AIR and ENSO reached its lowest value in the 1871–2016 period. We determined that the association between the weakening ENSO–AIR relationship and ENSO nonlinearity could reflect the contribution of different nonlinear ENSO modes to ENSO diversity.</p>
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spelling doaj.art-d119131c4e54482eb0b9faaa7d4ab36a2022-12-22T01:21:03ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382020-11-01245473548910.5194/hess-24-5473-2020A skewed perspective of the Indian rainfall–El Niño–Southern Oscillation (ENSO) relationshipJ. Schulte0F. Policielli1B. Zaitchik2Science Systems and Applications, Inc., Lanham, Maryland, 20706, USANASA Goddard Space Flight Center, Greenbelt, Maryland, 20771, USADepartment of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, Maryland, 21218, USA<p>Wavelet coherence is a method that is commonly used in hydrology to extract scale-dependent, nonstationary relationships between time series. However, we show that the method cannot always determine why the time-domain correlation between two time series changes in time. We show that, even for stationary coherence, the time-domain correlation between two time series weakens if at least one of the time series has changing skewness. To overcome this drawback, a nonlinear coherence method is proposed to quantify the cross-correlation between nonlinear modes embedded in the time series. It is shown that nonlinear coherence and auto-bicoherence spectra can provide additional insight into changing time-domain correlations. The new method is applied to the El Niño–Southern Oscillation (ENSO) and all-India rainfall (AIR), which is intricately linked to hydrological processes across the Indian subcontinent. The nonlinear coherence analysis showed that the skewness of AIR is weakly correlated with that of two ENSO time series after the 1970s, indicating that increases in ENSO skewness after the 1970s at least partially contributed to the weakening ENSO–AIR relationship in recent decades. The implication of this result is that the intensity of skewed El Niño events is likely to overestimate India's drought severity, which was the case in the 1997 monsoon season, a time point when the nonlinear wavelet coherence between AIR and ENSO reached its lowest value in the 1871–2016 period. We determined that the association between the weakening ENSO–AIR relationship and ENSO nonlinearity could reflect the contribution of different nonlinear ENSO modes to ENSO diversity.</p>https://hess.copernicus.org/articles/24/5473/2020/hess-24-5473-2020.pdf
spellingShingle J. Schulte
F. Policielli
B. Zaitchik
A skewed perspective of the Indian rainfall–El Niño–Southern Oscillation (ENSO) relationship
Hydrology and Earth System Sciences
title A skewed perspective of the Indian rainfall–El Niño–Southern Oscillation (ENSO) relationship
title_full A skewed perspective of the Indian rainfall–El Niño–Southern Oscillation (ENSO) relationship
title_fullStr A skewed perspective of the Indian rainfall–El Niño–Southern Oscillation (ENSO) relationship
title_full_unstemmed A skewed perspective of the Indian rainfall–El Niño–Southern Oscillation (ENSO) relationship
title_short A skewed perspective of the Indian rainfall–El Niño–Southern Oscillation (ENSO) relationship
title_sort skewed perspective of the indian rainfall el nino southern oscillation enso relationship
url https://hess.copernicus.org/articles/24/5473/2020/hess-24-5473-2020.pdf
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