Articles | Volume 23, issue 11
https://doi.org/10.5194/acp-23-6559-2023
https://doi.org/10.5194/acp-23-6559-2023
Research article
 | 
15 Jun 2023
Research article |  | 15 Jun 2023

Opposing trends of cloud coverage over land and ocean under global warming

Huan Liu, Ilan Koren, Orit Altaratz, and Mickaël D. Chekroun

Related authors

The Lightning Differential Space Framework: Multiscale Analysis of Stroke and Flash Behavior
Yuval Ben Ami, Ilan Koren, Orit Altaratz, and Yoav Yair
EGUsphere, https://doi.org/10.5194/egusphere-2025-4052,https://doi.org/10.5194/egusphere-2025-4052, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
The ENSO-driven bias in the assessment of long-term cloud feedback to global warming
Huan Liu, Ilan Koren, Orit Altaratz, and Shutian Mu
EGUsphere, https://doi.org/10.5194/egusphere-2025-2574,https://doi.org/10.5194/egusphere-2025-2574, 2025
Short summary
Dynamical regimes of CCN activation in adiabatic air parcels
Manuel Santos Gutiérrez, Mickaël David Chekroun, and Ilan Koren
EGUsphere, https://doi.org/10.48550/arXiv.2405.11545,https://doi.org/10.48550/arXiv.2405.11545, 2024
Preprint withdrawn
Short summary
Record-breaking statistics detect islands of cooling in a sea of warming
Elisa T. Sena, Ilan Koren, Orit Altaratz, and Alexander B. Kostinski
Atmos. Chem. Phys., 22, 16111–16122, https://doi.org/10.5194/acp-22-16111-2022,https://doi.org/10.5194/acp-22-16111-2022, 2022
Short summary
Revisiting adiabatic fraction estimations in cumulus clouds: high-resolution simulations with a passive tracer
Eshkol Eytan, Ilan Koren, Orit Altaratz, Mark Pinsky, and Alexander Khain
Atmos. Chem. Phys., 21, 16203–16217, https://doi.org/10.5194/acp-21-16203-2021,https://doi.org/10.5194/acp-21-16203-2021, 2021
Short summary

Cited articles

Aerenson, T., Marchand, R., Chepfer, H., and Medeiros, B.: When will MISR detect rising high clouds?, J. Geophys. Res.-Atmos., 127, 2021–035865, https://doi.org/10.1029/2021JD035865, 2022. 
ajdawson: eofs, GitHub [code], https://github.com/ajdawson/eofs (last access: 15 January 2022), 2019. 
Aleksandrova, M., Gulev, S. K., and Belyaev, K.: Probability distribution for the visually observed fractional cloud cover over the ocean, J. Climate, 31, 3207–3232, https://doi.org/10.1175/JCLI-D-17-0317.1, 2018 
Baldwin, M. P., Stephenson, D. B., and Jolliffe, I. T.: Spatial weighting and iterative projection methods for eofs, J. Climate, 22, 234–243, https://doi.org/10.1175/2008JCLI2147.1, 2009. 
Barker, H. W.: Representing cloud overlap with an effective decorrelation length: An assessment using CloudSat and CALIPSO data, J. Geophys. Res.-Atmos., 113, D24205, https://doi.org/10.1029/2008JD010391, 2008. 
Download
Short summary
Clouds' responses to global warming contribute the largest uncertainty in climate prediction. Here, we analyze 42 years of global cloud cover in reanalysis data and show a decreasing trend over most continents and an increasing trend over the tropical and subtropical oceans. A reduction in near-surface relative humidity can explain the decreasing trend in cloud cover over land. Our results suggest potential stress on the terrestrial water cycle, associated with global warming.
Share
Altmetrics
Final-revised paper
Preprint