Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China
Chinese Academy of Sciences · Ghent University · +3 more institutions
Abstract
Abstract. Water resources are essential to the ecosystem and social economy in the desert and oasis of the arid Tarim River basin, northwestern China, and expected to be vulnerable to climate change. It has been demonstrated that regional climate models (RCMs) provide more reliable results for a regional impact study of climate change (e.g., on water resources) than general circulation models (GCMs). However, due to their considerable bias it is still necessary to apply bias correction before they are used for water resources research. In this paper, after a sensitivity analysis on input meteorological variables based on the Sobol' method, we compared five precipitation correction methods and three temperature…
Citation impact
- FWCI
- 15.20
- Percentile
- 100%
- References
- 49
Authors
4- GFGonghuan FangCorresponding
Chinese Academy of Sciences, Ghent University, Xinjiang Institute of Ecology and Geography, University of Chinese Academy of Sciences
- JYJing YangCorresponding
Chinese Academy of Sciences, Xinjiang Institute of Ecology and Geography, National Institute of Water and Atmospheric Research
- YCYaning ChenCorresponding
Chinese Academy of Sciences, Xinjiang Institute of Ecology and Geography
- CZChristian ZammitCorresponding
National Institute of Water and Atmospheric Research
Topics & keywords
- Downscaling
- Environmental science
- Precipitation
- Streamflow
- Climatology
- Climate change
- Quantile
- Water resources
- Clean water and sanitation