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Evaluating the Time-Invariance Hypothesis of Climate Model Bias Correction: Implications for Hydrological Impact Studies

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  • 1 Centre ESCER, Université du Québec à Montréal, Montréal, Québec, Canada
  • | 2 Centre ESCER, Université du Québec à Montréal, and Consortium Ouranos, Montréal, Québec, Canada
  • | 3 École de Technologie Supérieure, Montréal, Québec, Canada
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Abstract

The bias correction of climate model outputs is based on the main assumption of the time invariance of the bias, in which the statistical relationship between observations and climate model outputs in the historical period stays constant in the future period. The present study aims to assess statistical bias correction under nonstationary bias conditions and its implications on the simulated streamflow over two snowmelt-driven Canadian catchments. A pseudoreality approach is employed in order to derive a proxy of future observations. In this approach, CRCM–ECHAM5 ensemble simulations are used as pseudoreality observations to correct for bias in the CRCM–CGCM3 ensemble simulations in the reference (1971–2000) period. The climate model simulations are then bias corrected in the future (2041–70) period and compared with the future pseudoreality observations. This process demonstrates that biases (precipitation and temperature) remain after the bias correction. In a second step, the uncorrected and bias-corrected CRCM–CGCM3 simulations are used to drive the Soil and Water Assessment Tool (SWAT) hydrological model in both periods. The bias correction decreases the error on mean monthly streamflow over the reference period; such findings are more mixed over the future period. The results of various hydrological indicators show that the climate change signal on streamflow obtained with uncorrected and bias-corrected simulations is similar in both its magnitude and its direction for the mean monthly streamflow only. Regarding the indicators of extreme hydrological events, more mixed results are found with site dependence. All in all, bias correction under nonstationary bias is an additional source of uncertainty that cannot be neglected in hydrological climate change impact studies.

Corresponding author address: J. A. Velázquez, Centre ESCER, Université du Québec à Montréal, 550 Sherbrooke West, West Tower, 19th floor, Montréal, QC H3A 1B9, Canada. E-mail: jvelazquez@colsan.edu.mx

Abstract

The bias correction of climate model outputs is based on the main assumption of the time invariance of the bias, in which the statistical relationship between observations and climate model outputs in the historical period stays constant in the future period. The present study aims to assess statistical bias correction under nonstationary bias conditions and its implications on the simulated streamflow over two snowmelt-driven Canadian catchments. A pseudoreality approach is employed in order to derive a proxy of future observations. In this approach, CRCM–ECHAM5 ensemble simulations are used as pseudoreality observations to correct for bias in the CRCM–CGCM3 ensemble simulations in the reference (1971–2000) period. The climate model simulations are then bias corrected in the future (2041–70) period and compared with the future pseudoreality observations. This process demonstrates that biases (precipitation and temperature) remain after the bias correction. In a second step, the uncorrected and bias-corrected CRCM–CGCM3 simulations are used to drive the Soil and Water Assessment Tool (SWAT) hydrological model in both periods. The bias correction decreases the error on mean monthly streamflow over the reference period; such findings are more mixed over the future period. The results of various hydrological indicators show that the climate change signal on streamflow obtained with uncorrected and bias-corrected simulations is similar in both its magnitude and its direction for the mean monthly streamflow only. Regarding the indicators of extreme hydrological events, more mixed results are found with site dependence. All in all, bias correction under nonstationary bias is an additional source of uncertainty that cannot be neglected in hydrological climate change impact studies.

Corresponding author address: J. A. Velázquez, Centre ESCER, Université du Québec à Montréal, 550 Sherbrooke West, West Tower, 19th floor, Montréal, QC H3A 1B9, Canada. E-mail: jvelazquez@colsan.edu.mx
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