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Preprints
https://doi.org/10.5194/egusphere-2023-1061
https://doi.org/10.5194/egusphere-2023-1061
05 Jun 2023
 | 05 Jun 2023

Equatorial wave diagnosis for the Atlantic Niño in 2019 with an ocean reanalysis

Qingyang Song and Hidenori Aiki

Abstract. The propagation of equatorial waves is essential for the onset of Atlantic Niño, but diagnosing waves using ocean reanalysis or in-situ data remains a challenge. This study uses an ocean reanalysis to diagnose the wave energy transfer route during the 2019 event. The climatological values and the anomaly in 2019 at each grid are decomposed into the first four baroclinic modes based on their local density profiles. The decomposed geopotential can well reproduce the displacement of the thermocline during the event. Wave energy flux is calculated by means of a group-velocity-based scheme. In addition to detecting wind-forced Kelvin waves and reflected Rossby waves, the wave energy flux reveals another possible energy transfer routes along the western boundary, where some off-equatorial wave energy can excite coastally-trapped Kelvin waves and transfer back to the equatorial Atlantic. Four transections are selected, and the passing wave energy fluxes for 2019 are integrated across them. The results suggest that the Kelvin waves in the third and fourth mode are local forced, while the wave energy in the second mode is more likely from the off-equatorial region. Therefore, in the fall of 2019, the second-mode Kelvin waves causes the thermocline to drop ahead of other modes from September, serving to precondition the Niño event.

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Journal article(s) based on this preprint

05 Dec 2023
Equatorial wave diagnosis for the Atlantic Niño in 2019 with an ocean reanalysis
Qingyang Song and Hidenori Aiki
Ocean Sci., 19, 1705–1717, https://doi.org/10.5194/os-19-1705-2023,https://doi.org/10.5194/os-19-1705-2023, 2023
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

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There has been a long-standing need for a rapid detection method for waves using simulation data...
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