Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 27, issue 4
Articles | Volume 27, issue 4
https://doi.org/10.5194/hess-27-861-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-27-861-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 27, issue 4
Research article
 | 
23 Feb 2023
Research article |  | 23 Feb 2023

Daytime-only mean data enhance understanding of land–atmosphere coupling

Zun Yin, Kirsten L. Findell, Paul Dirmeyer, Elena Shevliakova, Sergey Malyshev, Khaled Ghannam, Nina Raoult, and Zhihong Tan

Viewed

Total article views: 2,363 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,819 467 77 2,363 131 79 113
  • HTML: 1,819
  • PDF: 467
  • XML: 77
  • Total: 2,363
  • Supplement: 131
  • BibTeX: 79
  • EndNote: 113
Views and downloads (calculated since 07 Sep 2022)
Cumulative views and downloads (calculated since 07 Sep 2022)

Viewed (geographical distribution)

Total article views: 2,363 (including HTML, PDF, and XML) Thereof 2,340 with geography defined and 23 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 24 Oct 2025
Download
Short summary
Land–atmosphere (L–A) interactions typically focus on daytime processes connecting the land state with the overlying atmospheric boundary layer. However, much prior L–A work used monthly or daily means due to the lack of daytime-only data products. Here we show that monthly smoothing can significantly obscure the L–A coupling signal, and including nighttime information can mute or mask the daytime processes of interest. We propose diagnosing L–A coupling within models or archiving subdaily data.
Read more
Share