Towards Probabilistic Multivariate ENSO Monitoring

Zhang, Tao; Hoell, Andrew; Perlwitz, Judith; Eischeid, Jon; Murray, Donald; Hoerling, Martin; Hamill, Thomas M.

doi:10.1029/2019GL083946

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i

Towards Probabilistic Multivariate ENSO Monitoring

2019
By Zhang, Tao ; Hoell, Andrew ; Perlwitz, Judith ; ...
Source: Geophysical Research Letters, 46, 10532-10540.

[PDF-3.05 MB]

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Details:

Journal Title:

Geophysical Research Letters
Personal Author:

Zhang, Tao ; Hoell, Andrew ; Perlwitz, Judith ; Eischeid, Jon ; Murray, Donald ; ... More +

Zhang, Tao ; Hoell, Andrew ; Perlwitz, Judith ; Eischeid, Jon ; Murray, Donald ; Hoerling, Martin ; Hamill, Thomas M. Less -
NOAA Program & Office:

CIRES (Cooperative Institute for Research in Environmental Sciences) ; OAR (Oceanic and Atmospheric Research) ; ESRL (Earth System Research Laboratory) ; PSL (Physical Sciences Laboratory)

CIRES (Cooperative Institute for Research in Environmental Sciences) ; OAR (Oceanic and Atmospheric Research) ; ESRL (Earth System Research Laboratory) ; PSL (Physical Sciences Laboratory) Less -
Description:

A probabilistic approach to describing El Niño–Southern Oscillation (ENSO), based on consideration of the signal‐to‐noise ratio for the coupled ocean‐atmosphere ENSO state, is presented. The ENSO signal is estimated using an ensemble of historical atmospheric model simulations forced by observed sea surface temperatures and sea ice during 1980–2016. The noise is estimated from departures of individual model realizations from their ensemble average when subjected to identical forcing. It is found that this atmospheric noise effect is substantial and yields considerable uncertainty in detecting the true coupled ENSO mode. This uncertainty exceeds analysis errors by an order of magnitude. Greater atmospheric noise is found to prevail during El Niño than La Niña, suggesting that the intensity of the monitored ENSO state during El Niño is prone to greater misattribution. Our results demonstrate that a deterministic state estimate of ENSO conditions may not be representative of the true real‐time coupled ENSO mode.
Keywords:

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El Nino
Source:

Geophysical Research Letters, 46, 10532-10540.
DOI:

https://doi.org/10.1029/2019GL083946
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Journal Article
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urn:sha256:c643dd6be448deda49cffa7bf1f980015bb31950f86b881fe8386ce534647bf4
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https://repository.library.noaa.gov/view/noaa/25110/noaa_25110_DS1.pdf
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Dataset (GFSv2 model data)

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