Tropical Instability Waves in the Atlantic Ocean: Investigating the Relative Role of Sea Surface Salinity and Temperature From 2010 to 2018

Olivier, Léa; Reverdin, Gilles; Hasson, Audrey; Boutin, Jacqueline

doi:10.1029/2020jc016641

Cited by 11 publications

(17 citation statements)

References 83 publications

(156 reference statements)

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“…This indicates that σ ( v ′) and σ (SLA′) precede σ (SST′). Although the satellite SSS record is considerably shorter, there is also a clear signature of TIWs with peak σ (SSS′) variability north of the equator that is strongest in June (Figures S2a and S2b in Supporting Information ), consistent with previous findings (Lee et al., 2014; Olivier et al., 2020).…”

Section: Resultssupporting

confidence: 90%

“…To identify and quantify TIW activity, first all data are temporally band‐pass filtered (20–50 day Hamming window). In a second step, those data sets that exhibit spatial dimensions are zonally band‐pass filtered (4°–20°) following established Atlantic TIW methodology (Lee et al., 2014; Olivier et al., 2020; Perez et al., 2012). Then, for a filtered time series x ′, the monthly standard deviation σ ( x ′) is calculated and the resulting monthly standard deviation time series will be used as a proxy for TIW activity/variability in the subsequent statistical analysis.…”

Section: Methodsmentioning

confidence: 99%

“…Although the seasonality of Atlantic TIW activity is well documented (Grodsky et al., 2005; Heukamp et al., 2022; Olivier et al., 2020; Perez et al., 2012; Specht et al., 2021; Tuchen et al., 2018), considerably less is known about interannual to decadal variability and long‐term trends of TIWs and the associated variability of physical and biogeochemical properties. Previous studies identified significant year‐to‐year variability of TIWs (Athié & Marin, 2008; Caltabiano et al., 2005; Olivier et al., 2020; Perez et al., 2012; Wu & Bowman, 2007a) and suggested the coupled Atlantic zonal mode and changes in the barotropic energy conversion as possible sources for the observed interannual fluctuations (Perez et al., 2012; Wu & Bowman, 2007a). Jochum and Murtugudde (2004) showed that internal variability can be an important driver of interannual TIW variability.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multidecadal Intensification of Atlantic Tropical Instability Waves

Tuchen

Perez

Foltz

et al. 2022

Geophysical Research Letters

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Section: Resultssupporting

confidence: 90%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multidecadal Intensification of Atlantic Tropical Instability Waves

Tuchen

Perez

Foltz

et al. 2022

Geophysical Research Letters

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“…As this study started, individual satellite SSS is capable of resolving the upper register of the mesoscale spectrum (spatial scale of 50–500 km and temporal scale of 10–100 days) (e.g., Hasson et al., 2019; Huang et al., 2021; Kolodziejczyk et al., 2021; Lin et al., 2019; Melnichenko et al., 2021; Olivier et al., 2020). These scales play an important role in the mixing and exchanges of water masses close to fronts, as a result of ocean circulation and atmospheric fluxes.…”

Section: Introductionmentioning

confidence: 99%

Satellite‐Based Sea Surface Salinity Designed for Ocean and Climate Studies

et al. 2021

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Sea Surface Salinity (SSS) is an increasingly used Essential Ocean and Climate Variable. The Soil Moisture and Ocean Salinity (SMOS), Aquarius, and Soil Moisture Active Passive (SMAP) satellite missions all provide SSS measurements, with very different instrumental features leading to specific measurement characteristics. The Climate Change Initiative Salinity project (CCI + SSS) aims to produce a SSS Climate Data Record (CDR) that addresses well‐established user needs based on those satellite measurements. To generate a homogeneous CDR, instrumental differences are carefully adjusted based on in‐depth analysis of the measurements themselves, together with some limited use of independent reference data. An optimal interpolation in the time domain without temporal relaxation to reference data or spatial smoothing is applied. This allows preserving the original datasets variability. SSS CCI fields are well suited for monitoring weekly to interannual signals, at spatial scales ranging from 50 km to the basin scale. They display large year‐to‐year seasonal variations over the 2010–2019 decade, sometimes by more than ±0.4 over large regions. The robust standard deviation of the monthly CCI SSS minus in situ Argo salinities is 0.15 globally, while it is at least 0.20 with individual satellite SSS fields. r2 is 0.97, similar or better than with original datasets. The correlation with independent ship thermosalinographs SSS further highlights the CCI data set excellent performance, especially near land areas. During the SMOS‐Aquarius period, when the representativity uncertainties are the largest, r2 is 0.84 with CCI while it is 0.48 with the Aquarius original data set. SSS CCI data are freely available and will be updated and extended as more satellite data become available.

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“…As this study started, individual satellite SSS is capable of resolving the upper register of the mesoscale spectrum (spatial scale of 50-500 km and temporal scale of 10-100 days) (e.g., Hasson et al, 2019;Huang et al, 2021;Kolodziejczyk et al, 2021;Lin et al, 2019;Melnichenko et al, 2021;Olivier et al, 2020). These scales play an important role in the mixing and exchanges of water masses close to fronts, as a result of ocean circulation and atmospheric fluxes.…”

Section: Introductionmentioning

confidence: 99%

Satellite-based Sea Surface Salinity designed for Ocean and Climate Studies

Boutin

Reul

Kohler³

et al. 2021

Preprint

Self Cite

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Sea Surface Salinity (SSS) is an increasingly used Essential Ocean and Climate Variable. The Soil Moisture and Ocean Salinity (SMOS), Aquarius, and Soil Moisture Active Passive (SMAP) satellite missions all provide SSS measurements, with very different instrumental features leading to specific measurement characteristics. The Climate Change Initiative Salinity project (CCI + SSS) aims to produce a SSS Climate Data Record (CDR) that addresses well-established user needs based on those satellite measurements. To generate a homogeneous CDR, instrumental differences are carefully adjusted based on in-depth analysis of the measurements themselves, together with some limited use of independent reference data. An optimal interpolation in the time domain without temporal relaxation to reference data or spatial smoothing is applied. This allows preserving the original datasets variability. SSS CCI fields are well suited for monitoring weekly to interannual signals, at spatial scales ranging from 50 km to the basin scale. They display large year-to-year seasonal variations over the 2010-2019 decade, sometimes by more than ±0.4 over large regions. The robust standard deviation of the monthly CCI SSS minus in situ Argo salinities is 0.15 globally, while it is at least 0.20 with individual satellite SSS fields. r 2 is 0.97, similar or better than with original datasets. The correlation with independent ship thermosalinographs SSS further highlights the CCI data set excellent performance, especially near land areas. During the SMOS-Aquarius period, when the representativity uncertainties are the largest, r 2 is 0.84 with CCI while it is 0.48 with the Aquarius original data set. SSS CCI data are freely available and will be updated and extended as more satellite data become available.

show abstract

Tropical Instability Waves in the Atlantic Ocean: Investigating the Relative Role of Sea Surface Salinity and Temperature From 2010 to 2018

Cited by 11 publications

References 83 publications

Multidecadal Intensification of Atlantic Tropical Instability Waves

Multidecadal Intensification of Atlantic Tropical Instability Waves

Satellite‐Based Sea Surface Salinity Designed for Ocean and Climate Studies

Satellite-based Sea Surface Salinity designed for Ocean and Climate Studies

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