@article{9a38a430537a43c197c1b1254145d226,
title = "Cross-spectral analysis of the SST/10-m wind speed coupling resolved by satellite products and climate model simulations",
abstract = "This study aims to determine the spatial–temporal scales where the SST forcing of the near-surface winds takes places, and its relationship with the action of coherent ocean eddies. Here, cross-spectral statistics are used to examine the relationship between satellite-based SST and 10-m wind speed (w) fields at scales between 102–104 km and 101–103 days. It is shown that the transition from negative SST/w correlations at large-scales to positive at oceanic mesoscales occurs at wavelengths coinciding with the atmospheric first baroclinic Rossby radius of deformation; and that the dispersion of positively-correlated signals resembles tropical instability waves near the equator, and Rossby waves in the extratropics. Transfer functions are used to estimate the SST-driven w response in physical space (wc), a signal that explains 5–40% of the mesoscale w variance in the equatorial cold tongues, and 2–15% at extratropical SST fronts. The signature of ocean eddies is clearly visible in wc, accounting for 20–60% of its variability in eddy-rich regions. To provide further insight on the role of ocean eddies in the SST-driven coupling, the analysis is repeated for two climate model (CCSM) simulations using ocean grid resolutions of 1 ∘ (eddy-parameterized, LR) and 0. 1 ∘ (eddy-resolving, HR). The lack of resolved eddies in LR leads to a significantly underestimated mesoscale w variance relative to HR. Conversely, the wc variability in HR can exceed the satellite estimates by a factor of two at extratropical SST fronts and underestimate it by a factor of almost six near the equator, reflecting shortcomings of the CCSM to be addressed in its future developments.",
keywords = "Air–sea interaction, Climate modeling, Cross-spectral analysis, Mesoscale ocean eddies, Oceanic Rossby waves, Satellite observations",
author = "Laurindo, {Lucas C.} and Leo Siqueira and Mariano, {Arthur J.} and Kirtman, {Ben P.}",
note = "Funding Information: Acknowledgements The authors thank Drs. William Johns and Igor Kamenkovich for very helpful discussions throughout the development of this work. Constructive comments by Dr. Frank Bryan and one anonymous reviewer are also gratefully acknowledged. This research was supported by grants from The Gulf of Mexico Research Initiative, and from the National Science Foundation (OCE1419569). Model experiments were performed using computing resources provided by the University of Miami Center for Computational Science, and by the Climate Simulation Laboratory at NCAR{\textquoteright}s Computational and Information Systems Laboratory. Post-processed versions of the model outputs analyzed in this study, that can be used to replicate the presented results, are publicly available through the Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC) at https://data. gulfresearchinitiative.org (http://dx.doi.org/10.7266/N70R9N1Q). The source code for the CCSM4 model is available at http://www.cesm. ucar.edu/models/ccsm4.0/, where the full outputs of the model experiments described here, and the input data necessary to reproduce them, are available from the authors upon request (bkirtman@miami.edu). Finally, the software used in the spectral calculations based on the multitaper method are from the jLab data analysis package for Matlab (version 1.6.5) developed by Dr. Jonathan M. Lilly, available at http:// www.jmlilly.net/jmlsoft.html. Funding Information: The authors thank Drs. William Johns and Igor Kamenkovich for very helpful discussions throughout the development of this work. Constructive comments by Dr. Frank Bryan and one anonymous reviewer are also gratefully acknowledged. This research was supported by grants from The Gulf of Mexico Research Initiative, and from the National Science Foundation (OCE1419569). Model experiments were performed using computing resources provided by the University of Miami Center for Computational Science, and by the Climate Simulation Laboratory at NCAR?s Computational and Information Systems Laboratory. Post-processed versions of the model outputs analyzed in this study, that can be used to replicate the presented results, are publicly available through the Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC) at https://data.gulfresearchinitiative.org (http://dx.doi.org/10.7266/N70R9N1Q). The source code for the CCSM4 model is available at http://www.cesm.ucar.edu/models/ccsm4.0/ , where the full outputs of the model experiments described here, and the input data necessary to reproduce them, are available from the authors upon request (bkirtman@miami.edu). Finally, the software used in the spectral calculations based on the multitaper method are from the jLab data analysis package for Matlab (version 1.6.5) developed by Dr. Jonathan M. Lilly, available at http://www.jmlilly.net/jmlsoft.html. Publisher Copyright: {\textcopyright} 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.",
year = "2019",
month = may,
day = "1",
doi = "10.1007/s00382-018-4434-6",
language = "English (US)",
volume = "52",
pages = "5071--5098",
journal = "Climate Dynamics",
issn = "0930-7575",
publisher = "Springer Verlag",
number = "9-10",
}