Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 17, issue 22
Articles | Volume 17, issue 22
https://doi.org/10.5194/gmd-17-8267-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-8267-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 22
Methods for assessment of models
 | 
25 Nov 2024
Methods for assessment of models |  | 25 Nov 2024

Observational operator for fair model evaluation with ground NO2 measurements

Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao

Viewed

Total article views: 1,210 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
892 263 55 1,210 113 62 100
  • HTML: 892
  • PDF: 263
  • XML: 55
  • Total: 1,210
  • Supplement: 113
  • BibTeX: 62
  • EndNote: 100
Views and downloads (calculated since 09 Feb 2024)
Cumulative views and downloads (calculated since 09 Feb 2024)

Viewed (geographical distribution)

Total article views: 1,210 (including HTML, PDF, and XML) Thereof 1,186 with geography defined and 24 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 14 Aug 2025
Download
Short summary
Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Read more
Share