Nonequilibrium Fractionation During Ice Cloud Formation in iCAM5: Evaluating the Common Parameterization of Supersaturation as a Linear Function of Temperature

• Published in: Journal of Advances in Modeling Earth Systems
• Main Authors: Marina Dütsch, Peter N. Blossey, Eric J. Steig, Jesse M. Nusbaumer
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Geophysical Union (AGU) 2019
• Subjects: stable water isotopes; deuterium excess; supersaturation; Antarctica; ice clouds; Physical geography; GB3-5030; Oceanography; GC1-1581; Antarctic; Antarc*
• Online Access: https://doi.org/10.1029/2019MS001764; https://doaj.org/article/b5bd45e3f0154396b8f3c0f3a97af4b8

Abstract Supersaturation with respect to ice determines the strength of nonequilibrium fractionation during vapor deposition onto ice or snow and therefore influences the water isotopic composition of vapor and precipitation in cold environments. Historically, most general circulation models formed clouds through saturation adjustment and therefore prevented supersaturation. To match the observed isotopic content, especially the deuterium excess, of snow in polar regions, the saturation ratio with respect to ice (Si) was parameterized, usually by assuming a linear dependence of Si on temperature. The Community Atmosphere Model Version 5 (CAM5) no longer applies saturation adjustment for the ice phase and thus allows ice supersaturation. Here, we adapt the isotope‐enabled version of CAM5 to compute nonequilibrium fractionation in ice and mixed‐phase clouds based on Si from the CAM5 microphysics and use it to evaluate the common parameterization of Si. Our results show a wide range of Si predicted by the CAM5 microphysics and reflected in the simulated deuterium excess of Antarctic precipitation; this is overly simplified by the linear parameterization. Nevertheless, a linear function, when properly tuned, can reproduce the average observed relationship between δD and deuterium excess reasonably well. However, only the model‐predicted Si can capture changes in microphysical conditions under different climate states that are not due to changes in temperature. Furthermore, parametric sensitivity tests show that with the model‐predicted Si, water isotopes are more closely tied to the model microphysics and can therefore constrain uncertain microphysical parameters.