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.
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.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Feb 2023
Research article |
| 23 Feb 2023
| 23 Feb 2023
Daytime-only mean data enhance understanding of land–atmosphere coupling
Program in Atmospheric and Oceanic Sciences, Princeton University, Princeton, 08540 New Jersey, USA
Kirsten L. Findell
Geophysical Fluid Dynamics Laboratory, NOAA, Princeton, 08540 New Jersey, USA
Paul Dirmeyer
Center for Ocean-Land-Atmosphere Studies, George Mason University, Fairfax, 22030 Virginia, USA
Elena Shevliakova
Geophysical Fluid Dynamics Laboratory, NOAA, Princeton, 08540 New Jersey, USA
Sergey Malyshev
Geophysical Fluid Dynamics Laboratory, NOAA, Princeton, 08540 New Jersey, USA
Khaled Ghannam
Program in Atmospheric and Oceanic Sciences, Princeton University, Princeton, 08540 New Jersey, USA
Nina Raoult
Laboratoire des Sciences du Climat et de l'Environnement, IPSL, CNRS-CEA-UVSQ, Gif-sur-Yvette 91191, Essonne, France
Zhihong Tan
Program in Atmospheric and Oceanic Sciences, Princeton University, Princeton, 08540 New Jersey, USA
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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.
Land–atmosphere (L–A) interactions typically focus on daytime processes connecting the land...
