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Table 2.

Statistical downscaling models from the RIWER2030 ANR project (Lafaysse et al. 2014; Hingray et al. 2013). Predictors used by the models are as follows: SLP: sea level pressure; Z: geopotential height for the pressure level; Ta: surface temperature; u and υ: zonal and meridian geostrophic wind; HU: relative humidity; and Fq: moisture flux, where subscripts refers to pressure level (hPa). The number of generation for each GCM–SDM chain is 100.

Statistical downscaling models from the RIWER2030 ANR project (Lafaysse et al. 2014; Hingray et al. 2013). Predictors used by the models are as follows: SLP: sea level pressure; Z: geopotential height for the pressure level; Ta: surface temperature; u and υ: zonal and meridian geostrophic wind; HU: relative humidity; and Fq: moisture flux, where subscripts refers to pressure level (hPa). The number of generation for each GCM–SDM chain is 100.
Statistical downscaling models from the RIWER2030 ANR project (Lafaysse et al. 2014; Hingray et al. 2013). Predictors used by the models are as follows: SLP: sea level pressure; Z: geopotential height for the pressure level; Ta: surface temperature; u and υ: zonal and meridian geostrophic wind; HU: relative humidity; and Fq: moisture flux, where subscripts refers to pressure level (hPa). The number of generation for each GCM–SDM chain is 100.
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