Publications des scientifiques de l'IRD

Ruffault J., Martin-StPaul N.K., Duffet C., Goge F., Mouillot Florent. (2014). Projecting future drought in Mediterranean forests : bias correction of climate models matters !. Theoretical and Applied Climatology, 117 (1-2), p. 113-122. ISSN 0177-798X.

Titre du document
Projecting future drought in Mediterranean forests : bias correction of climate models matters !
Année de publication
2014
Type de document
Article référencé dans le Web of Science WOS:000338446500009
Auteurs
Ruffault J., Martin-StPaul N.K., Duffet C., Goge F., Mouillot Florent
Source
Theoretical and Applied Climatology, 2014, 117 (1-2), p. 113-122 ISSN 0177-798X
Global and regional climate models (GCM and RCM) are generally biased and cannot be used as forcing variables in ecological impact models without some form of prior bias correction. In this study, we investigated the influence of the bias correction method on drought projections in Mediterranean forests in southern France for the end of the twenty-first century (2071–2100). We used a water balance model with two different atmospheric climate forcings built from the same RCM simulations but using two different correction methods (quantile mapping or anomaly method). Drought, defined here as periods when vegetation functioning is affected by water deficit, was described in terms of intensity, duration and timing. Our results showed that the choice of the bias correction method had little effects on temperature and global radiation projections. However, although both methods led to similar predictions of precipitation amount, they induced strong differences in their temporal distribution, especially during summer. These differences were amplified when the climatic data were used to force the water balance model. On average, the choice of bias correction leads to 45 % uncertainty in the predicted anomalies in drought intensity along with discrepancies in the spatial pattern of the predicted changes and changes in the year-to-year variability in drought characteristics. We conclude that the choice of a bias correction method might have a significant impact on the projections of forest response to climate change.
Plan de classement
Analyse, évolution des climats [021CLIMAT01] ; Formations végétales [082VEGET02]
Descripteurs
FORET ; SECHERESSE ; PREVISION ; DEFICIT HYDRIQUE ; BILAN HYDRIQUE ; MODELE CLIMATIQUE ; PREVISION CLIMATIQUE ; METHODE ; TEMPERATURE ; PLUIE ; PRECIPITATION ; DISTRIBUTION SPATIALE ; ETUDE REGIONALE ; ETUDE COMPARATIVE ; CHANGEMENT CLIMATIQUE ; RADIATION
Description Géographique
FRANCE
Localisation
Fonds IRD [F B010063014]
Identifiant IRD
fdi:010063014
Contact