Articles | Volume 22, issue 5
https://doi.org/10.5194/acp-22-3303-2022
https://doi.org/10.5194/acp-22-3303-2022
Research article
 | 
14 Mar 2022
Research article |  | 14 Mar 2022

Quantifying albedo susceptibility biases in shallow clouds

Graham Feingold, Tom Goren, and Takanobu Yamaguchi

Viewed

Total article views: 2,913 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,998 851 64 2,913 47 39
  • HTML: 1,998
  • PDF: 851
  • XML: 64
  • Total: 2,913
  • BibTeX: 47
  • EndNote: 39
Views and downloads (calculated since 08 Nov 2021)
Cumulative views and downloads (calculated since 08 Nov 2021)

Viewed (geographical distribution)

Total article views: 2,913 (including HTML, PDF, and XML) Thereof 2,876 with geography defined and 37 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 20 Nov 2024
Download
Short summary
The evaluation of radiative forcing associated with aerosol–cloud interactions remains a significant source of uncertainty in future climate projections. Using high-resolution numerical model output, we mimic typical satellite retrieval methodologies to show that data aggregation can introduce significant error (hundreds of percent) in the cloud albedo susceptibility metric. Spatial aggregation errors tend to be countered by temporal aggregation errors.
Altmetrics
Final-revised paper
Preprint