Errors and uncertainties introduced by a regional climate model in climate impact assessments: example of crop yield simulations in West AfricaReport as inadecuate




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* Corresponding author 1 LOCEAN - Laboratoire d-Océanographie et du Climat : Expérimentations et Approches Numériques 2 Ecoclimasol 3 CRC - Centre de Recherches de Climatologie 4 PARVATI - Processus de la variabilité climatique tropicale et impacts LOCEAN - Laboratoire d-Océanographie et du Climat : Expérimentations et Approches Numériques

Abstract : The challenge of estimating the potential impacts of climate change has led to an increasing use of dynamical downscaling to produce fine spatial-scale climate projections for impact assessments. In this work, we analyze if and to what extent the bias in the simulated crop yield can be reduced by using the Weather Research and Forecasting WRF regional climate model to downscale ERA-Interim European Centre for Medium-Range Weather Forecasts ECMWF Re-Analysis rainfall and radiation data. Then, we evaluate the uncertainties resulting from both the choice of the physical parameterizations of the WRF model and its internal variability. Impact assessments were performed at two sites in Sub-Saharan Africa and by using two crop models to simulate Niger pearl millet and Benin maize yields. We find that the use of the WRF model to downscale ERA-Interim climate data generally reduces the bias in the simulated crop yield, yet this reduction in bias strongly depends on the choices in the model setup. Among the physical parameterizations considered, we show that the choice of the land surface model LSM is of primary importance. When there is no coupling with a LSM, or when the LSM is too simplistic, the simulated precipitation and then the simulated yield are null, or respectively very low; therefore, coupling with a LSM is necessary. The convective scheme is the second most influential scheme for yield simulation, followed by the shortwave radiation scheme. The uncertainties related to the internal variability of the WRF model are also significant and reach up to 30% of the simulated yields. These results suggest that regional models need to be used more carefully in order to improve the reliability of impact assessments.





Author: Johanna Ramarohetra - Benjamin Pohl - Benjamin Sultan -

Source: https://hal.archives-ouvertes.fr/



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