Advances in Statistical Climatology, Meteorology and Oceanography
Advances in Statistical Climatology, Meteorology and Oceanography
ASCMO
Articles | Volume 6, issue 1
Articles | Volume 6, issue 1
https://doi.org/10.5194/ascmo-6-45-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ascmo-6-45-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 6, issue 1
11 May 2020
 | 11 May 2020

Postprocessing ensemble forecasts of vertical temperature profiles

David Schoenach, Thorsten Simon, and Georg Johann Mayr

Viewed

Total article views: 2,090 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,633 348 109 2,090 78 82
  • HTML: 1,633
  • PDF: 348
  • XML: 109
  • Total: 2,090
  • BibTeX: 78
  • EndNote: 82
Views and downloads (calculated since 11 May 2020)
Cumulative views and downloads (calculated since 11 May 2020)

Viewed (geographical distribution)

Total article views: 1,958 (including HTML, PDF, and XML) Thereof 1,880 with geography defined and 78 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 Apr 2025
Download
Short summary
State-of-the-art statistical methods are applied to postprocess an ensemble of numerical forecasts for vertical profiles of air temperature. These profiles are important tools in weather forecasting as they show the stratification and the static stability of the atmosphere. Flexible regression models combined with the multi-dimensionality of the data lead to better calibration and representation of uncertainty of the vertical profiles.
Read more
Share