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Statistical downscaling of sea-surface wind over the Peru–Chile upwelling region: diagnosing the impact of climate change from the IPSL-CM4 model

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Abstract

The key aspect of the ocean circulation off Peru–Chile is the wind-driven upwelling of deep, cold, nutrient-rich waters that promote a rich marine ecosystem. It has been suggested that global warming may be associated with an intensification of upwelling-favorable winds. However, the lack of high-resolution long-term observations has been a limitation for a quantitative analysis of this process. In this study, we use a statistical downscaling method to assess the regional impact of climate change on the sea-surface wind over the Peru–Chile upwelling region as simulated by the global coupled general circulation model IPSL-CM4. Taking advantage of the high-resolution QuikSCAT wind product and of the NCEP reanalysis data, a statistical model based on multiple linear regressions is built for the daily mean meridional and zonal wind at 10 m for the period 2000–2008. The large-scale 10 m wind components and sea level pressure are used as regional circulation predictors. The skill of the downscaling method is assessed by comparing with the surface wind derived from the ERS satellite measurements, with in situ wind observations collected by ICOADS and through cross-validation. It is then applied to the outputs of the IPSL-CM4 model over stabilized periods of the pre-industrial, 2 × CO2 and 4 × CO2 IPCC climate scenarios. The results indicate that surface along-shore winds off central Chile (off central Peru) experience a significant intensification (weakening) during Austral winter (summer) in warmer climates. This is associated with a general decrease in intra-seasonal variability.

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Notes

  1. Standard error of regression is defined as the standard deviation of regression error ε.

  2. The method consists in creating a surrogate data, namely a randomized data set of along-shore winds by scrambling the original data in the time domain. In the PI run, for the scrambled data set, we select 15 years over the 30-yr record. The seasonal cycle of the along-shore winds is then estimated. The same procedure of scrambling the data set and performing the analysis is repeated 1000 times, which allows deriving the PDF for each calendar month. The distribution is then used to assess the significance level for the change in along-shore winds for each calendar month. .

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Acknowledgments

This study was supported by the PCCC (Peru–Chile Climate Change) project funded by the ANR (Agence Nationale de la Recherche) and by the AXA research fund. We would like to thank Sébastien Denvil for providing the IPSL-CM4 data. Stimulating discussions with Sabrina Speich at the early stage of this project and with René Garreaud are also acknowledged. We are also grateful to Ali Belmadani for fruitful discussions.

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Authors and Affiliations

  1. Laboratoire d’Etudes en Géophysique et Océanographie Spatiale, CNES/CNRS/IRD/UPS, Toulouse, France

    K. Goubanova & B. Dewitte

  2. Laboratoire d’Océanographie et de Climatologie: Expérimentation et Approches Numériques, IPSL/UPMC/IRD, Paris, France

    V. Echevin & P. Terray

  3. Instituto del Mar del Peru, Callao, Peru

    K. Goubanova & B. Dewitte

  4. Laboratoire de Météorologie Dynamique, UPMC/CNRS, Paris, France

    F. Codron

  5. Instituto Geofisico del Peru, Lima, Peru

    B. Dewitte & K. Takahashi

  6. Laboratoire des Sciences du Climat et de l’Environnement, IPSL/CNRS/CEA/UVSQ, Gif-sur-Yvette, France

    M. Vrac

Authors
  1. K. Goubanova
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  2. V. Echevin
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  3. B. Dewitte
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  4. F. Codron
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  5. K. Takahashi
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  6. P. Terray
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  7. M. Vrac
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Correspondence to K. Goubanova.

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Goubanova, K., Echevin, V., Dewitte, B. et al. Statistical downscaling of sea-surface wind over the Peru–Chile upwelling region: diagnosing the impact of climate change from the IPSL-CM4 model. Clim Dyn 36, 1365–1378 (2011). https://doi.org/10.1007/s00382-010-0824-0

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  • DOI: https://doi.org/10.1007/s00382-010-0824-0

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