Wednesday, February 23, 2011

Pascal Oettli et al., Environ. Res. Lett. 6 (January-March 2011), Are regional climate models relevant for crop yield prediction in West Africa?

Environ. Res. Lett6 (January-March 2011) 014008; doi: 10.1088/1748-9326/6/1/014008

Are regional climate models relevant for crop yield 
prediction in West Africa?

Pascal Oettli1,2, Benjamin Sultan1,5, Christian Baron3 and Mathieu Vrac4

1 IPSL—LOCEAN, Paris, France
2 University of Tokyo, Tokyo, Japan
3 CIRAD UPR AIVA, Montpellier, France
4 IPSL—LSCE, Gif-sur-Yvette, France
5 Address for correspondence: LOCEAN, Boite 100, T45/55, 4 Place Jussieu, 75252 Paris 
cedex 05, France

Received 18 October 2010; Accepted 17 January 2011; Published 1 February 2011
Abstract. This study assesses the accuracy of state-of-the-art regional climate models
for agriculture applications in West Africa. A set of nine regional configurations with eight
regional models from the ENSEMBLES project is evaluated. Although they are all based
on similar large-scale conditions, the performances of regional models in reproducing the
most crucial variables for crop production are extremely variable. This therefore leads to
a large dispersion in crop yield prediction when using regional models in a climate/crop
modelling system. This dispersion comes from the different physics in each regional model
and also the choice of parametrizations for a single regional model. Indeed, two configurations of the same regional model are sometimes more distinct than two different regional models. Promising
results are obtained when applying a bias correction technique to climate model outputs.
Simulated yields with bias corrected climate variables show much more realistic means and
standard deviations. However, such a bias correction technique is not able to improve the
reproduction of the year-to-year variations of simulated yields.
This study confirms the importance of the multi-model approach for quantifying uncer-
tainties for impact studies and also stresses the benefits of combining both regional and 
statistical downscaling techniques. Finally, it indicates the urgent need to address the main 
uncertainties in atmospheric processes controlling the monsoon system and to contribute 
to the evaluation and improvement of climate and weather forecasting models in that respect.

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