Methods for adding general DNS derived coagulation kernel

[Gorkowski]

Look at adding the DNS derived droplet coagulation kernel used in:
Riemer, N., & Wexler, A. S. (2005). Droplets to Drops by Turbulent Coagulation. Journal of the Atmospheric Sciences, 62(6), 1962–1975. https://doi.org/10.1175/JAS3431.1

See if there is a generalizable way to implement it, so that we can account for other DNS derived kernels.

[Gorkowski]

Grabowski, W. W., & Wang, L. P. (2013). Growth of cloud droplets in a turbulent environment. Annual Review of Fluid Mechanics, 45, 293–324. https://doi.org/10.1146/annurev-fluid-011212-140750

[Gorkowski]

Grabowski, W. W., & Wang, L.-P. (2009). Diffusional and accretional growth of water drops in a rising adiabatic parcel: effects of the turbulent collision kernel. Atmospheric Chemistry and Physics, 9(7), 2335–2353. https://doi.org/10.5194/acp-9-2335-2009

Third, the enhancement is more
uniform for droplets less than 60 µm than other unrealis-
tic turbulent kernels such as in Riemer and Wexler (2005)
for reasons discussed in Wang et al. (2006).

[Gorkowski]

@mahf708, I'm going start with

Ayala, O., Rosa, B., & Wang, L. P. (2008). Effects of turbulence on the geometric collision rate of sedimenting droplets. Part 2. Theory and parameterization. New Journal of Physics, 10. https://doi.org/10.1088/1367-2630/10/7/075016

As the first parameterization for the geometric coagulation kernel. It's the one used in subsequent Garbowski and Wang papers.
And I haven't seen more recent ones that clearly superseded this.

[Gorkowski]

[mahf708]

gpt, code this up for me pls 😸

[Gorkowski]

Hehehe, gpt is one reason I went with docs first. As gpt can handle those small functions pretty well and near perfect with an example to follow

[mahf708]

One thing I've been thinking a lot about is ... how to make these kernels "flowless"