Estimating the Observed Atmospheric Response to SST Anomalies: Maximum Covariance Analysis, Generalized Equilibrium Feedback Assessment, and Maximum Response Estimation

International audience Abstract Three multivariate statistical methods to estimate the influence of SST or boundary forcing on the atmosphere are discussed. Lagged maximum covariance analysis (MCA) maximizes the covariance between the atmosphere and prior SST, thus favoring large responses and domin...

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Published in:Journal of Climate
Main Authors: Frankignoul, Claude, Chouaib, Nadine, Liu, Zhengyu
Other Authors: Sorbonne Université (SU)
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2011
Subjects:
Online Access:https://hal.science/hal-03842683
https://doi.org/10.1175/2010JCLI3696.1
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spelling ftsorbonneuniv:oai:HAL:hal-03842683v1 2024-05-12T08:07:55+00:00 Estimating the Observed Atmospheric Response to SST Anomalies: Maximum Covariance Analysis, Generalized Equilibrium Feedback Assessment, and Maximum Response Estimation Frankignoul, Claude Chouaib, Nadine Liu, Zhengyu Sorbonne Université (SU) 2011-05-15 https://hal.science/hal-03842683 https://doi.org/10.1175/2010JCLI3696.1 en eng HAL CCSD American Meteorological Society info:eu-repo/semantics/altIdentifier/doi/10.1175/2010JCLI3696.1 hal-03842683 https://hal.science/hal-03842683 doi:10.1175/2010JCLI3696.1 ISSN: 0894-8755 EISSN: 1520-0442 Journal of Climate https://hal.science/hal-03842683 Journal of Climate, 2011, 24 (10), pp.2523-2539. ⟨10.1175/2010JCLI3696.1⟩ [SDE]Environmental Sciences info:eu-repo/semantics/article Journal articles 2011 ftsorbonneuniv https://doi.org/10.1175/2010JCLI3696.1 2024-04-18T03:30:12Z International audience Abstract Three multivariate statistical methods to estimate the influence of SST or boundary forcing on the atmosphere are discussed. Lagged maximum covariance analysis (MCA) maximizes the covariance between the atmosphere and prior SST, thus favoring large responses and dominant SST patterns. However, it does not take into account the possible SST evolution during the time lag. To correctly represent the relation between forcing and response, a new SST correction is introduced. The singular value decomposition (SVD) of generalized equilibrium feedback assessment (GEFA–SVD) identifies in a truncated SST space the optimal SST patterns for forcing the atmosphere, independently of the SST amplitude; hence it may not detect a large response. A new method based on GEFA, named maximum response estimation (MRE), is devised to estimate the largest boundary-forced atmospheric signal. The methods are compared using synthetic data with known properties and observed North Atlantic monthly anomaly data. The synthetic data shows that the MCA is generally robust and essentially unbiased. GEFA–SVD is less robust and sensitive to the truncation. MRE is less sensitive to truncation and nearly as robust as MCA, providing the closest approximation to the largest true response to the sample SST. To analyze the observations, a 2-month delay in the atmospheric response is assumed based on recent studies. The delay strongly affects GEFA–SVD and MRE, and it is key to obtaining consistent results between MCA and MRE. The MCA and MRE confirm that the dominant atmospheric signal is the NAO-like response to North Atlantic horseshoe SST anomalies. When the atmosphere is considered in early winter, the response is strongest and MCA most powerful. With all months of the year, MRE provides the most significant results. GEFA–SVD yields SST patterns and NAO-like atmospheric responses that depend on lag and truncation, thus lacking robustness. When SST leads by 1 month, a significant mode is found by the three methods, but ... Article in Journal/Newspaper North Atlantic HAL Sorbonne Université Journal of Climate 24 10 2523 2539
institution Open Polar
collection HAL Sorbonne Université
op_collection_id ftsorbonneuniv
language English
topic [SDE]Environmental Sciences
spellingShingle [SDE]Environmental Sciences
Frankignoul, Claude
Chouaib, Nadine
Liu, Zhengyu
Estimating the Observed Atmospheric Response to SST Anomalies: Maximum Covariance Analysis, Generalized Equilibrium Feedback Assessment, and Maximum Response Estimation
topic_facet [SDE]Environmental Sciences
description International audience Abstract Three multivariate statistical methods to estimate the influence of SST or boundary forcing on the atmosphere are discussed. Lagged maximum covariance analysis (MCA) maximizes the covariance between the atmosphere and prior SST, thus favoring large responses and dominant SST patterns. However, it does not take into account the possible SST evolution during the time lag. To correctly represent the relation between forcing and response, a new SST correction is introduced. The singular value decomposition (SVD) of generalized equilibrium feedback assessment (GEFA–SVD) identifies in a truncated SST space the optimal SST patterns for forcing the atmosphere, independently of the SST amplitude; hence it may not detect a large response. A new method based on GEFA, named maximum response estimation (MRE), is devised to estimate the largest boundary-forced atmospheric signal. The methods are compared using synthetic data with known properties and observed North Atlantic monthly anomaly data. The synthetic data shows that the MCA is generally robust and essentially unbiased. GEFA–SVD is less robust and sensitive to the truncation. MRE is less sensitive to truncation and nearly as robust as MCA, providing the closest approximation to the largest true response to the sample SST. To analyze the observations, a 2-month delay in the atmospheric response is assumed based on recent studies. The delay strongly affects GEFA–SVD and MRE, and it is key to obtaining consistent results between MCA and MRE. The MCA and MRE confirm that the dominant atmospheric signal is the NAO-like response to North Atlantic horseshoe SST anomalies. When the atmosphere is considered in early winter, the response is strongest and MCA most powerful. With all months of the year, MRE provides the most significant results. GEFA–SVD yields SST patterns and NAO-like atmospheric responses that depend on lag and truncation, thus lacking robustness. When SST leads by 1 month, a significant mode is found by the three methods, but ...
author2 Sorbonne Université (SU)
format Article in Journal/Newspaper
author Frankignoul, Claude
Chouaib, Nadine
Liu, Zhengyu
author_facet Frankignoul, Claude
Chouaib, Nadine
Liu, Zhengyu
author_sort Frankignoul, Claude
title Estimating the Observed Atmospheric Response to SST Anomalies: Maximum Covariance Analysis, Generalized Equilibrium Feedback Assessment, and Maximum Response Estimation
title_short Estimating the Observed Atmospheric Response to SST Anomalies: Maximum Covariance Analysis, Generalized Equilibrium Feedback Assessment, and Maximum Response Estimation
title_full Estimating the Observed Atmospheric Response to SST Anomalies: Maximum Covariance Analysis, Generalized Equilibrium Feedback Assessment, and Maximum Response Estimation
title_fullStr Estimating the Observed Atmospheric Response to SST Anomalies: Maximum Covariance Analysis, Generalized Equilibrium Feedback Assessment, and Maximum Response Estimation
title_full_unstemmed Estimating the Observed Atmospheric Response to SST Anomalies: Maximum Covariance Analysis, Generalized Equilibrium Feedback Assessment, and Maximum Response Estimation
title_sort estimating the observed atmospheric response to sst anomalies: maximum covariance analysis, generalized equilibrium feedback assessment, and maximum response estimation
publisher HAL CCSD
publishDate 2011
url https://hal.science/hal-03842683
https://doi.org/10.1175/2010JCLI3696.1
genre North Atlantic
genre_facet North Atlantic
op_source ISSN: 0894-8755
EISSN: 1520-0442
Journal of Climate
https://hal.science/hal-03842683
Journal of Climate, 2011, 24 (10), pp.2523-2539. ⟨10.1175/2010JCLI3696.1⟩
op_relation info:eu-repo/semantics/altIdentifier/doi/10.1175/2010JCLI3696.1
hal-03842683
https://hal.science/hal-03842683
doi:10.1175/2010JCLI3696.1
op_doi https://doi.org/10.1175/2010JCLI3696.1
container_title Journal of Climate
container_volume 24
container_issue 10
container_start_page 2523
op_container_end_page 2539
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