Advances in Statistical Climatology, Meteorology and Oceanography
Advances in Statistical Climatology, Meteorology and Oceanography
ASCMO
Articles | Volume 6, issue 2
Articles | Volume 6, issue 2
https://doi.org/10.5194/ascmo-6-115-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ascmo-6-115-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 6, issue 2
06 Oct 2020
 | 06 Oct 2020

The effect of geographic sampling on evaluation of extreme precipitation in high-resolution climate models

Mark D. Risser and Michael F. Wehner

Viewed

Total article views: 3,512 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,168 276 68 3,512 60 52
  • HTML: 3,168
  • PDF: 276
  • XML: 68
  • Total: 3,512
  • BibTeX: 60
  • EndNote: 52
Views and downloads (calculated since 06 Oct 2020)
Cumulative views and downloads (calculated since 06 Oct 2020)

Viewed (geographical distribution)

Total article views: 3,334 (including HTML, PDF, and XML) Thereof 3,333 with geography defined and 1 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 20 Jan 2025
Download
Short summary
Evaluation of modern high-resolution global climate models often does not account for the geographic location of the underlying weather station data. In this paper, we quantify the impact of geographic sampling on the relative performance of climate model representations of precipitation extremes over the United States. We find that properly accounting for the geographic sampling of weather stations can significantly change the assessment of model performance.
Read more