Articles | Volume 16, issue 7
https://doi.org/10.5194/gmd-16-2055-2023
https://doi.org/10.5194/gmd-16-2055-2023
Methods for assessment of models
 | 
17 Apr 2023
Methods for assessment of models |  | 17 Apr 2023

Evaluation of bias correction methods for a multivariate drought index: case study of the Upper Jhelum Basin

Rubina Ansari, Ana Casanueva, Muhammad Usman Liaqat, and Giovanna Grossi

Viewed

Total article views: 3,407 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,402 906 99 3,407 249 98 143
  • HTML: 2,402
  • PDF: 906
  • XML: 99
  • Total: 3,407
  • Supplement: 249
  • BibTeX: 98
  • EndNote: 143
Views and downloads (calculated since 05 Dec 2022)
Cumulative views and downloads (calculated since 05 Dec 2022)

Viewed (geographical distribution)

Total article views: 3,407 (including HTML, PDF, and XML) Thereof 3,290 with geography defined and 117 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 12 Feb 2026
Download
Short summary
Bias correction (BC) has become indispensable to climate model output as a post-processing step to render output more useful for impact assessment studies. The current work presents a comparison of different state-of-the-art BC methods (univariate and multivariate) and BC approaches (direct and component-wise) for climate model simulations from three initiatives (CMIP6, CORDEX, and CORDEX-CORE) for a multivariate drought index (i.e., standardized precipitation evapotranspiration index).
Share