Bias correction of dynamically downscaled precipitation to compute soil water deficit for explaining year-to-year variation of tree growth over northeastern France

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• 作者：Damien Boulard^a ; ^{damien.boulard@u-bourgogne.fr} ; Thierry Castel^a ; ^b ; Pierre Camberlin^a ; Anne-Sophie Sergent^c ; ^d ; Daphné ; Asse^e ; Nathalie Bré ; da^c ; Vincent Badeau^c ; Auré ; lien Rossi^a ; Benjamin Pohl^a
• 关键词：Regional climate modelling ; WRF ; Quantile mapping ; Water balance ; Soil water deficit ; Douglas-fir ; Common beech
• 刊名：Agricultural and Forest Meteorology
• 出版年：2017
• 出版时间：15 January 2017
• 年：2017
• 卷：232
• 期：Complete
• 页码：247-264
• 全文大小：4797 K
• 卷排序：232

文摘

The QM method succeeds at reducing the RCM’s wet biases in spring and summer. Post-correcting RCM precipitation does not improve the Soil Water Deficit Index. The QM method does not correct the timing errors produced by the climate model. Realistic temporality of precipitation is required for climate impact assessment.