Articles | Volume 17, issue 22
https://doi.org/10.5194/gmd-17-8267-2024
https://doi.org/10.5194/gmd-17-8267-2024
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: 548 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
410 98 40 548 54 32 30
  • HTML: 410
  • PDF: 98
  • XML: 40
  • Total: 548
  • Supplement: 54
  • BibTeX: 32
  • EndNote: 30
Views and downloads (calculated since 09 Feb 2024)
Cumulative views and downloads (calculated since 09 Feb 2024)

Viewed (geographical distribution)

Total article views: 548 (including HTML, PDF, and XML) Thereof 539 with geography defined and 9 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 25 Nov 2024
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.