rss
Coupled EBM Project Update 9/9
Code Location on GitHub
https://github.com/ethansavitch/coupled_ebm
Jacob's Answers To My Questions
- Purpose of the Stochastic Parameter?
The stochastic parameter in the EBM equation was used in my glacial-interglacial cycles paper (cited on your poster), which was done to explore the concept of "stochastic resonance" in a climate system. The idea is that the Earth system has multiple stable climate states (ice free, large ice cap, small ice cap, ice covered), and that variability in the Earth system itself might contribute to periodic transitions between states (which for small random variability would be between the large and small ice cap solutions). The stochastic parameter thus is a hand-wavy way of approximating the effect of sub-model-scale processes that would exert a random noise upon equilibrium climate. The net effect of this is that the hysteresis loop decreases in width, since it becomes slightly easier to access different states. There's no need to include the stochastic parameter for accuracy. I included a longer explanation here in case it is useful at a later stage in the project.
- What's the purpose of the soladj=solar forcing adjustment parameter?
The solar forcing adjustment is used to time step the model through a prescribed increase in stellar brightness as the star ages through the main sequence. If you look near line 265 of the code, you will see that when soladj is true, the model reads in the eccentricity, precession, obliquity, and solar constant from the file data/insolaout.dat. This data is from Laskar's astronomical solutions for Earth's past and future (http://vo.imcce.fr/insola/earth/online/earth/earth.html). If soladj is false, then these values are all treated as fixed with time. You only need the solar forcing adjustment feature if you are interested in long time integrations with realistic representation of solar brightening and orbital evolution.
- How best to incorporate weathering?
If you want CO2 weathering as described by Williams & Kasting (Icarus, 1997), then you could uncomment line 637, where I have added a comment "removed co2 adjusting.". However, the timescales we are talking about are on the order of thousands to tens of thousands of years, where shorter-term variation in atmospheric CO2 will dominate. The carbonate-silicate cycle operates with a residence time of about half a million years, and only matters for Earth climate when we consider timescales into the hundreds of thousands of years (see, e.g., Berner, Lasaga, & Garrels, Am. J. Sci., 1983). So I would say leave the code as-is, and don't worry about carbonate-silicate weathering. If you do want to experiment with the effects of weathering, then the solution in 3b of your blog post sounds like a good approach to me. (constant annual per-capita reduction in CO2, parameterized with )
ToDo Next
- Clean/Fix Jupyter Notebook. All parts are currently working except for the namelist functionality.
- Compare output of coupled EBM with global average temperatures.
- Increase accuracy of the growth rates temperature dependencies, which will hopefully make our output more in line with the global averages.
Comments
No comments.