Correcting a Radiation Code Error in the NASA/Ames Legacy Mars Global Climate Model
Abstract
The goal of Haberle et al. (2019) was to document the status of the NASA/Ames Legacy Mars Global Climate Model (GCM) and to provide a reference for future investigations. Selected water cycle results were presented and interpreted to further our understanding of how clouds affect the current Mars climate. Since publishing that manuscript, we discovered a coding error that resulted in computed water ice cloud infrared opacities that were approximately a factor of 2 too small. Correcting the opacity computation resulted in clouds that were more effective in the infrared, and produced a water cycle that was too wet and too cloudy. Here we correct and document the error and demonstrate that we can recover many of the aspects of the Haberle et al. (2019) baseline simulation by implementing a small change to the contact parameter (the cosine of the contact angle), which is a microphysical parameter that controls the ease with which nucleation occurs (lower means harder) and therefore the number and size of cloud particles. We show that with a slightly lower contact parameter (0.965 instead of 0.975), the new baseline simulation produces a similar seasonal cycle of water vapor and atmospheric thermal response in the aphelion cloud belt as the Haberle et al. (2019) baseline simulation, but it also produces cloud optical depths that are about a factor of 2 lower in the aphelion cloud belt and local opacities that are ~20% higher in the polar hoods. Most importantly, however, we demonstrate that the clouds predicted by our new baseline simulation produce reasonable temperature responses that are consistent with the Haberle et al. (2019) baseline simulation. The fact that such a small change to the contact parameter can yield very different water cycles illustrates how sensitive the climate system is to cloud microphysical processes.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFM.P35F2189K