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Climate Dynamics

, Volume 38, Issue 1–2, pp 121–140 | Cite as

Large-scale circulation patterns and related rainfall in the Amazon Basin: a neuronal networks approach

  • Jhan Carlo Espinoza
  • Matthieu Lengaigne
  • Josyane Ronchail
  • Serge Janicot
Article

Abstract

This study describes the main circulation patterns (CP) in the Amazonian Basin over the 1975–2002 period and their relationship with rainfall variability. CPs in the Amazonian Basin have been computed for each season from the ERA-40 daily 850 hPa winds using an approach combining artificial neural network (Self Organizing Maps) and Hierarchical Ascendant Classification. A 6 to 8 cluster solutions (depending on the season considered) is shown to yield an integrated view of the complex regional circulation variability. For austral fall, winter and spring the temporal evolution between the different CPs shows a clear tendency to describe a cycle, with southern wind anomalies and their convergence with the trade winds progressing northward from the La Plata Basin to the Amazon Basin. This sequence is strongly related to eastward moving extra tropical perturbations and their incursion toward low latitude that modulate the geopotential and winds over South America and its adjoining oceans. During Austral summer, CPs are less spatially and temporally organized compared to other seasons, principally due to weaker extra tropical perturbations and more frequent shallow low situations. Each of these CPs is shown to be associated with coherent northward moving regional rainfall patterns (both in in situ data and ERA-40 reanalysis) and convective activity. However, our results reveals that precipitation variability is better reproduced by ERA-40 in the southern part of the Amazonian Basin than in the northern part, where rainfall variability is likely to be more constrained by local and subdaily processes (e.g. squall lines) that could be misrepresented in the reanalysis dataset. This analysis clearly illustrates the existing connections between the southern and northern part of the Amazonian Basin in terms of regional circulation/rainfall patterns. The identification of these CPs provide useful information to understand local rainfall variability and could hence be used to better understand the influence of these CPs on the hydrological variability in the Amazonian Basin.

Keywords

Circulation patterns South America Amazon Basin Rainfall Low level winds Self-organizing maps 

Notes

Acknowledgments

The authors would like to express their special thanks to the Institute of Research for the Development (IRD), the French National Center for Scientific Research (CNRS) through the REGYNA (Rainfall regionalisation and hydrological and agronomical impacts of climate change in vulnerable regions) program and the European CLARIS-LPB (European South American network for Climate Change Assessment and Impacts Studies) program for funding this research. ECMWF ERA-40 data used in this study has been provided by ECMWF from the ECMWF data server. We especially thank Gérard Cochonneau and Philippe Vauchel, the SENAMHI (Servicio Nacional de Meteorología e Hidrología—Bolivia) and ANA (Agência Nacional de Águas—Brazil), all members of the Observatory for Environmental Research HYBAM (Hydrogeodynamics of the Amazon Basin), for providing rainfall data. Our special thanks are for our colleagues from the LOCEAN, Benjamin Sultan, Pascal Terray, Abdou Gueye, and Mathieu Vrac from LSCE, for the productive discussions about circulation Patterns determination and downscalling. Also, we are appreciative to Henning Rust for the helpful proofreading of this manuscript. Finally, we are grateful to the reviewers whose comments and suggestions considerably helped to improve this paper.

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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Jhan Carlo Espinoza
    • 1
    • 2
  • Matthieu Lengaigne
    • 1
  • Josyane Ronchail
    • 1
    • 3
  • Serge Janicot
    • 1
  1. 1.LOCEAN—IPSL (IRD, CNRS, MNHN, UPMC)Paris Cedex 05France
  2. 2.Universidad Agraria La Molina UNALMLimaPeru
  3. 3.Université Paris 7ParisFrance

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