Statistical downscaling of sea-surface wind over the Peru–Chile upwelling region: diagnosing the impact of climate change from the IPSL-CM4 model
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 crossvalidation. It is then applied to the outputs of the IPSLCM4 model over stabilized periods of the pre-industrial, 2 x CO₂ and 4 x 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.
Description
Date
2011-04
Keywords
Statistical downscaling , Coastal wind , Upwelling , Peru , Chile , Climate change
Citation
Goubanova, K., Echevin, V., Dewitte, B., Codron, F., Takahashi, K., Terray, P., & Vrac, M. (2011). Statistical downscaling of sea-surface wind over the Peru–Chile upwelling region: diagnosing the impact of climate change from the IPSL-CM4 model. Climate Dynamics, 36, 1365-1378. https://doi.org/10.1007/s00382-010-0824-0
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Publisher
Springer