Fortnightly variability of Chl <i>a</i> in the Indonesian seas

Zaron, Edward D.; Capuano, Tonia Astrid; Koch-Larrouy, Ariane

doi:10.5194/os-19-43-2023

Cited by 3 publications

(3 citation statements)

References 52 publications

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“…They quantify errors using the (temperature) amplitudes of a few false tides in the vicinity of MSf and Mf lines. Recently, Zaron et al (2023) studied the fortnightly variability of Chl a in the Indonesian Seas using satellite sea surface color data. Their model errors are estimated using the (Chl a concentration) amplitudes at several fake tidal frequencies near the real constituents S a and MSf.…”

Section: Appendix A: Model Errorsmentioning

confidence: 99%

Seasonal West‐East Seesaw of M₂ Internal Tides From the Luzon Strait

Zhao

Qiu

2023

JGR Oceans

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Satellite altimetry sea surface height (SSH) measurements from 1993 to 2017 are used to investigate the seasonal variability of mode‐1 M2 internal tides from the Luzon Strait. The 25 years of SSH data are divided into four seasonal subsets, from which four seasonal internal tide models are constructed following the same mapping procedure. Climatological seasonal hydrography in the World Ocean Atlas 2013 is used to calculate two seasonally variable parameters required in the mapping procedure: Wavelength and the transfer function from the SSH amplitude to depth‐integrated energy flux. The M2 internal tides from the Luzon Strait are extracted using propagation direction determined in plane wave analysis. The satellite results show that the westward and eastward M2 internal tides both demonstrate significant seasonal variation. The westward and eastward internal tides seesaw seasonally: The westward internal tides strengthen (weaken) in summer and fall (winter and spring); while the eastward internal tides strengthen (weaken) in winter and spring (summer and fall). We suggest that the seasonal seesaw is mainly determined by ocean stratification and the Kuroshio Current; however, further studies are needed to quantify their relative contributions.

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Section: Appendix A: Model Errorsmentioning

confidence: 99%

Seasonal West‐East Seesaw of M₂ Internal Tides From the Luzon Strait

Zhao

Qiu

2023

JGR Oceans

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“…By this method, internal tides are determined by fitting horizontal plane waves in one given fitting window (160 km by 160 km in this study), in contrast to harmonic analysis at one single site. This method has been described in detail in our previous studies (Zhao and Alford, 2009;Zhao, 2014;Zhao et al, 2016). For each tidal constituent, there may be multiple internal tides of arbitrary propagation directions at each site, due to their multiple source regions and long-range propagation.…”

Section: Plane Wave Analysismentioning

confidence: 99%

“…For example, Ray and Susanto (2016) study the fortnightly tidal cycles (MS f and M f ) of tidal mixing using satellite sea surface temperature data. Zaron et al (2023) study the fortnightly variability in Chl a using satellite sea surface color data. In both studies, tidal errors are estimated using signals at fake or false tidal frequencies near the real tidal constituents.…”

Section: Model Errorsmentioning

confidence: 99%

Mode-1 N₂ internal tides observed by satellite altimetry

Zhao¹

2023

Ocean Sci.

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Abstract. Satellite altimetry provides a unique technique for observing the sea surface height (SSH) signature of internal tides from space. Previous studies have constructed empirical internal tide models for the four largest constituents M2, S2, K1, and O1 by satellite altimetry. Yet no empirical models have been constructed for minor tidal constituents. In this study, we observe mode-1 N2 internal tides (the fifth largest constituent) using about 100 satellite years of SSH data from 1993 to 2019. We employ a recently developed mapping procedure that includes two rounds of plane wave analysis and a two-dimensional bandpass filter in between. The results show that mode-1 N2 internal tides have millimeter-scale SSH amplitudes. Model errors are estimated from background internal tides that are mapped using the same altimetry data but with a tidal period of 12.6074 h (N2 minus 3 min). The global mean error variance is about 25 % that of N2, suggesting that the mode-1 N2 internal tides can overcome model errors in some regions. We find that the N2 and M2 internal tides have similar spatial patterns and that the N2 amplitudes are about 20 % of the M2 amplitudes. Both features are determined by the N2 and M2 barotropic tides. The mode-1 N2 internal tides are observed to propagate hundreds to thousands of kilometers in the open ocean. The globally integrated N2 and M2 internal tide energies are 1.8 and 30.9 PJ, respectively. Their ratio of 5.8 % is larger than the theoretical value of 4 % because the N2 internal tides contain relatively larger model errors. Our mode-1 N2 internal tide model is evaluated using independent satellite altimetry data in 2020 and 2021. The results suggest that the model can make internal tide correction in regions where the model variance is greater than twice the error variance. This work demonstrates that minor internal tidal constituents can be observed using multiyear multi-satellite altimetry data and dedicated mapping techniques.

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