Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models
Material type:
ArticleLanguage: En Publication details: 2010Subject(s):
In:
Journal of Hydrology v. 395, no. 3-4, p. 199-215Summary: A statisticalbiascorrection methodology for global climate simulations is developed and applied to daily land precipitation and mean, minimum and maximum daily land temperatures. The biascorrection is based on a fitted histogram equalization function. This function is defined daily, as opposed to earlier published versions in which they were derived yearly or seasonally at best, while conserving properties of robustness and eliminating unrealistic jumps at seasonal or monthly transitions. The methodology is tested using the newly available global dataset of observed hydrological forcing data of the last 50 years from the EU project WATCH (WATer and global CHange) and an initial conditions ensemble of simulations performed with the ECHAM5 global climate model for the same period. Biascorrections are derived from 1960 to 1969 observed and simulated data and then applied to 1990?1999 simulations. Results confirm the effectiveness of the methodology for all tested variables. Biascorrections are also derived using three other non-overlapping decades from 1970 to 1999 and all members of the ECHAM5 initial conditions ensemble. A methodology is proposed to use the resulting ?ensemble of biascorrections? to quantify the error in simulated scenario projections of components of the hydrological cycle.
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
| Article | CIMMYT Knowledge Center: John Woolston Library | Reprints Collection | Available |
Peer-review: Yes - Open Access: Yes|http://science.thomsonreuters.com/cgi-bin/jrnlst/jlresults.cgi?PC=MASTER&ISSN=0022-1694
A statisticalbiascorrection methodology for global climate simulations is developed and applied to daily land precipitation and mean, minimum and maximum daily land temperatures. The biascorrection is based on a fitted histogram equalization function. This function is defined daily, as opposed to earlier published versions in which they were derived yearly or seasonally at best, while conserving properties of robustness and eliminating unrealistic jumps at seasonal or monthly transitions. The methodology is tested using the newly available global dataset of observed hydrological forcing data of the last 50 years from the EU project WATCH (WATer and global CHange) and an initial conditions ensemble of simulations performed with the ECHAM5 global climate model for the same period. Biascorrections are derived from 1960 to 1969 observed and simulated data and then applied to 1990?1999 simulations. Results confirm the effectiveness of the methodology for all tested variables. Biascorrections are also derived using three other non-overlapping decades from 1970 to 1999 and all members of the ECHAM5 initial conditions ensemble. A methodology is proposed to use the resulting ?ensemble of biascorrections? to quantify the error in simulated scenario projections of components of the hydrological cycle.
English
Elsevier
Carelia Juarez
Reprints Collection