@article{fdi:010066060,
  title = {{E}rrors and uncertainties introduced by a regional climate model in climate impact assessments : example of crop yield simulations in {W}est {A}frica},
  author = {{R}amarohetra, {J}ohanna and {P}ohl, {B}. and {S}ultan, {B}enjamin},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he 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. {I}n this work, we analyze if and to what extent the bias in the simulated crop yield can be reduced by using the {W}eather {R}esearch and {F}orecasting ({WRF}) regional climate model to downscale {ERA}-{I}nterim ({E}uropean {C}entre for {M}edium-{R}ange {W}eather {F}orecasts ({ECMWF}) {R}e-{A}nalysis) rainfall and radiation data. {T}hen, we evaluate the uncertainties resulting from both the choice of the physical parameterizations of the {WRF} model and its internal variability. {I}mpact assessments were performed at two sites in {S}ub-{S}aharan {A}frica and by using two crop models to simulate {N}iger pearl millet and {B}enin maize yields. {W}e find that the use of the {WRF} model to downscale {ERA}-{I}nterim 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. {A}mong the physical parameterizations considered, we show that the choice of the land surface model ({LSM}) is of primary importance. {W}hen 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. {T}he convective scheme is the second most influential scheme for yield simulation, followed by the shortwave radiation scheme. {T}he uncertainties related to the internal variability of the {WRF} model are also significant and reach up to 30% of the simulated yields. {T}hese results suggest that regional models need to be used more carefully in order to improve the reliability of impact assessments.},
  keywords = {{WRF} ; crop model ; {W}est {A}frica ; regional climate model ; {EPIC} ; {SARRA}-{H} ; {BENIN} ; {NIGER} ; {ZONE} {SAHELIENNE} ; {ZONE} {SOUDANIENNE}},
  booktitle = {},
  journal = {{E}nvironmental {R}esearch {L}etters},
  volume = {12},
  numero = {12},
  pages = {art. 124014 [17 p.]},
  ISSN = {1748-9326},
  year = {2015},
  DOI = {10.1088/1748-9326/10/12/124014},
  URL = {https://www.documentation.ird.fr/hor/fdi:010066060},
}