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South America Intraseasonal Precipitation: A Normal-Mode Approach
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  • Victor C. Mayta,
  • André Seiji Teruya,
  • Breno Raphaldini,
  • Pedro Leite da Silva Dias,
  • Camila Sapucci
Victor C. Mayta
University of Michigan

Corresponding Author:[email protected]

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André Seiji Teruya
Instituto de Astronomia, Geofísica e Ciências Atmosféricas
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Breno Raphaldini
Instituto de Astronomia, Geofísica e Ciências Atmosféricas
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Pedro Leite da Silva Dias
Instituto de Astronomia, Geofísica e Ciências Atmosféricas
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Camila Sapucci
Instituto de Astronomia, Geofísica e Ciências Atmosféricas
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Abstract

An alternative approach to assess the South America intraseasonal variability is presented. In this study, we use a normal-mode decomposition method to decompose the South American 30-90-day Low-Frequency Intraseasonal (LFI) and 10-30-day High-Frequency Intraseasonal (HFI) variability systematically into rotational (ROT) and inertio-gravity (IGW) components in the reanalysis data.
The seasonal cycle of the LFI and HFI convective and dynamical structure is well-described by the first leading pattern (EOF1). The LFI EOF1 spatial structure during the rainy season is the dipole-like between the South Atlantic Convergence Zone (SACZ) and southeastern South America (SESA), influenced by the large-scale Madden-Julian Oscillation (MJO). During the dry season, alternating periods of enhanced and suppressed convection over South America is primarily controlled by extratropical wave disturbances. The HFI spatial pattern also resembles the SESA–SACZ structure, in response to the Rossby wave trains. Results based on normal-mode decomposition of reanalysis data and the LFI and HFI indices show that the tropospheric circulation and SESA–SACZ convective structure observed over South America are dominated by ROT modes (Rossby). A considerable portion of the LFI variability is also associated with the inertio-gravity (IGW) modes (Kelvin mode), prevailing mainly during the wet season.
The proposed decomposition methodology provides insights into the dynamic of the South America intraseasonal variability, giving a powerful tool for diagnosing circulation model issues in order to improve the prediction of precipitation.