Cross-spectral analysis of the SST/10-m wind speed coupling resolved by satellite products and climate model simulations

Laurindo, Lucas C.; Siqueira, Léo; Mariano, Arthur J.; Kirtman, Ben P.

doi:10.1007/s00382-018-4434-6

Cited by 20 publications

(29 citation statements)

References 129 publications

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“…By contrast, the SST‐ISV has a positive (negative) correlation with the wind speed (solar radiation) ISV in the equatorial cold tongues (Figure 2c, see the spatial pattern in Figure ). This positive relationship between the ISV of SST and wind speed over the cold tongue regions was previously seen from satellite observations (e.g., Laurindo et al., 2019; Small et al., 2008). The positive relationship occurs because the ocean forces the atmosphere at the oceanic mesoscale due to the presence of tropical instability wave (TIW) fronts, which has been widely studied (e.g., Chelton, 2005; Chelton & Xie, 2010; Hashizume et al., 2001; Laurindo et al., 2019; O'Neill, 2012; Small et al., 2008; Xie, 2004).…”

Section: Resultssupporting

confidence: 79%

“…The differing SST‐wind and SST‐radiation relationships arise from different atmosphere‐ocean interaction processes over the Indo‐Pacific warm pool and the equatorial cold tongue regions (Chelton, 2005; Laurindo et al., 2019; Small et al., 2008; Xie, 2004). Over the Indo‐Pacific warm pool region, the SST‐ISV is negatively correlated with the wind speed ISV and positively correlated with the solar radiation ISV (Figure 2c), indicating that the ocean is primarily driven by the atmospheric forcing on the intraseasonal timescales in this region (Hendon & Click, 1997; Small et al., 2008).…”

Section: Resultsmentioning

confidence: 99%

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Rectification of the Intraseasonal SST Variability by the Diurnal Cycle of SST Revealed by the Global Tropical Moored Buoy Array

Yan

Zhang

et al. 2021

Geophysical Research Letters

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The diurnal cycle of sea surface temperature (SST), which is driven by the diurnal variation of solar radiation, is a fundamental oscillation in the ocean (Soloviev & Lukas, 2006). The amplitude of the diurnal cycle of SST (dSST) is primarily determined by surface solar radiation and surface wind speed (Gentemann et al., 2003; Kawai & Wada, 2007; Price et al., 1986; Webster et al., 1996). Stronger solar radiation introduces more heat to the ocean inducing a larger dSST, while stronger wind forcing drives stronger oceanic turbulent mixing and draws more heat loss from the ocean surface to the atmosphere inducing a smaller dSST (Kawai & Wada, 2007). The dSST has been shown to have a significant impact on the intraseasonal variability (ISV) of SST (SST-ISV) (

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Section: Resultssupporting

confidence: 79%

Section: Resultsmentioning

confidence: 99%

Rectification of the Intraseasonal SST Variability by the Diurnal Cycle of SST Revealed by the Global Tropical Moored Buoy Array

Yan

Zhang

et al. 2021

Geophysical Research Letters

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“…IAP-LICOM is a global configuration of the LASG/IAP Climate system Ocean Model (LICOM) (Zhang and Liang, 1989;Liu et al, 2004Liu et al, , 2012Yu et al, 2018; e.g., Li et al, 2013;Bao et al, 2013) and of the CAS Earth System Model (CAS-ESM; Minghua Zhang, personal communication, 2019). Version 3 of LICOM (LICOM3) is coupled to CICE4 through the NCAR flux coupler 7 (Craig et al, 2012;Lin et al, 2016).…”

Section: Iap-licommentioning

confidence: 99%

Impact of horizontal resolution on global ocean–sea ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)

et al. 2020

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Abstract. This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations that are obtained following the OMIP-2 protocol (Griffies et al., 2016) and integrated for one cycle (1958–2018) of the JRA55-do atmospheric state and runoff dataset (Tsujino et al., 2018). Our goal is to assess the robustness of climate-relevant improvements in ocean simulations (mean and variability) associated with moving from coarse (∼ 1∘) to eddy-resolving (∼ 0.1∘) horizontal resolutions. The models are diverse in their numerics and parameterizations, but each low-resolution and high-resolution pair of models is matched so as to isolate, to the extent possible, the effects of horizontal resolution. A variety of observational datasets are used to assess the fidelity of simulated temperature and salinity, sea surface height, kinetic energy, heat and volume transports, and sea ice distribution. This paper provides a crucial benchmark for future studies comparing and improving different schemes in any of the models used in this study or similar ones. The biases in the low-resolution simulations are familiar, and their gross features – position, strength, and variability of western boundary currents, equatorial currents, and the Antarctic Circumpolar Current – are significantly improved in the high-resolution models. However, despite the fact that the high-resolution models “resolve” most of these features, the improvements in temperature and salinity are inconsistent among the different model families, and some regions show increased bias over their low-resolution counterparts. Greatly enhanced horizontal resolution does not deliver unambiguous bias improvement in all regions for all models.

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“…For example, decadal variability associated with ocean eddy activities and coupled air-sea feedbacks could be weak or even absent in low-resolution models, high-resolution CCSM4 with eddy-resolved ocean component model produces more realistic decadal variability (Chen & Kirtman, 2018;Laurindo et al, 2018;Siqueira & Kirtman, 2016). We speculate this underestimate (at least in CCSM4) could be possibly due to underresolved ocean mesoscale features and underestimated coupled feedbacks.…”

Section: Discussionmentioning

confidence: 89%

“…We speculate this underestimate (at least in CCSM4) could be possibly due to underresolved ocean mesoscale features and underestimated coupled feedbacks. For example, decadal variability associated with ocean eddy activities and coupled air-sea feedbacks could be weak or even absent in low-resolution models, high-resolution CCSM4 with eddy-resolved ocean component model produces more realistic decadal variability (Chen & Kirtman, 2018;Laurindo et al, 2018;Siqueira & Kirtman, 2016).…”

Section: Discussionmentioning

confidence: 99%

Estimates of Decadal Climate Predictability From an Interactive Ensemble Model

Zhang

Kirtman

2019

Geophysical Research Letters

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Decadal climate predictability has received considerable scientific interest in recent years, yet the limits and mechanisms for decadal predictability are currently not well known. It is widely accepted that noise due to internal atmospheric dynamics at the air‐sea interface influences predictability. The purpose of this paper is to use the interactive ensemble (IE) coupling strategy to quantify how internal atmospheric noise at the air‐sea interface impacts decadal predictability. The IE technique can significantly reduce internal atmospheric noise and has proven useful in assessing seasonal‐to‐interannual variability and predictability. Here we focus on decadal timescales and apply the nonlinear local Lyapunov exponent method to the Community Climate System Model comparing control simulations with IE simulations. This is the first time the nonlinear local Lyapunov exponent has been applied to the state‐of‐the‐art coupled models. The global patterns of decadal predictability are discussed from the perspective of internal atmospheric noise and ocean dynamics.

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Cross-spectral analysis of the SST/10-m wind speed coupling resolved by satellite products and climate model simulations

Cited by 20 publications

References 129 publications

Rectification of the Intraseasonal SST Variability by the Diurnal Cycle of SST Revealed by the Global Tropical Moored Buoy Array

Rectification of the Intraseasonal SST Variability by the Diurnal Cycle of SST Revealed by the Global Tropical Moored Buoy Array

Impact of horizontal resolution on global ocean–sea ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)

Estimates of Decadal Climate Predictability From an Interactive Ensemble Model

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