Articles | Volume 19, issue 10
https://doi.org/10.5194/hess-19-4055-2015
https://doi.org/10.5194/hess-19-4055-2015
Research article
 | 
06 Oct 2015
Research article |  | 06 Oct 2015

The effect of empirical-statistical correction of intensity-dependent model errors on the temperature climate change signal

A. Gobiet, M. Suklitsch, and G. Heinrich

Viewed

Total article views: 3,571 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,081 1,245 245 3,571 493 104 106
  • HTML: 2,081
  • PDF: 1,245
  • XML: 245
  • Total: 3,571
  • Supplement: 493
  • BibTeX: 104
  • EndNote: 106
Views and downloads (calculated since 16 Jun 2015)
Cumulative views and downloads (calculated since 16 Jun 2015)

Cited

Saved (final revised paper)

Saved (final revised paper)

Saved (preprint)

Latest update: 07 Dec 2024
Download
Short summary
The effect of empirical-statistical bias correction methods, like quantile mapping (QM), on the simulated climate change signals (CCS) is currently strongly discussed and is often regarded as deficiency of bias correction methods. We demonstrate that, quite the contrary, QM can lead to an improved CCS and also has the potential to serve as an empirical constraint on model uncertainty in climate projections.