Snow reconciles observed and simulated phase partitioning and increases cloud feedback



Cesana, Gregory — Laboratoire de Meteorologie Dynamique
Silber, Israel — Pennsylvania State University

Area of research:

Cloud Processes

Journal Reference:

Cesana G, A Ackerman, A Fridlind, I Silber, and M Kelley. 2021. "Snow Reconciles Observed and Simulated Phase Partitioning and Increases Cloud Feedback." Geophysical Research Letters, 48(20), e2021GL094876, 10.1029/2021GL094876.


The strength of the response of extratropical clouds to climate change (cloud feedback) is partly driven by the amount of supercooled water in cloud phase partitioning. This amount may be affected by precipitation, which is often neglected in model radiative schemes and instrument simulators.

What is the effect of adding precipitation in model cloud feedback? How does it impact comparisons with observations?


Adding precipitation in model radiative schemes increases warming in future projections and improves consistency in comparisons with observations.


The surprising increase of Earth's climate sensitivity – a proxy for future global warming – in the most recent climate models (CMIP6) has been largely attributed to the response of extratropical low clouds to warming. This cloud-climate feedback is thought to be driven by greater supercooled water in present-day cloud phase partitioning. Here we report that accounting for precipitation in climate model radiation schemes –neglected in more than 60% of CMIP6 and 90% of CMIP5 models– profoundly changes their apparent cloud phase partitioning and substantially increases their cloud-climate feedbacks, which has not been reported before. Including precipitation in the comparison with observations and in model radiation schemes is essential to faithfully constrain cloud amount and phase partitioning and simulate cloud-climate feedbacks. Our novel findings suggest that making radiation schemes precipitation-aware, which is missing in most CMIP6 models, should strengthen their positive cloud feedback and further increase their already high mean climate sensitivity