Pre-Initialize model xarray with timesteps

[sjordan29]

Closes #68

This PR adds a new required time_steps parameter for instantiation of the base model class. Writing to a pre-initialized array rather than continuously concatenating arrays has speed advantages, particularly for large model grids and a large number of model timesteps -- as shown in #68, for models with > 100 iterations and >10 model cells, we see performance gains which become substantial as the number of iterations/grid sizes grows (>14x improvement at best). Additional memory management improvements will help address minor slowdowns for single-cell models.

[aufdenkampe]

@sjordan29, Nice work! I looked over your code carefully, and I'm quite impressed (although I didn't run anything). I love the new examples/dev_sandbox/performance_profiling_tsm.py and its sister notebook. The plots are quite compelling, and it will be great to continue to add to it.

I'm also impressed with your work in src/clearwater_modules/base.py to properly set up the pre-initialized xarray datasets with all their coords. I imagine that sets us up nicely to tackle #69.

Thanks for updating and rerunning examples/model_architecture.ipynb.

Let's merge this!

[sjordan29]

@imscw95, @kewalak - FYI - merging this to main. Changes require models to have a time_steps input parameter during instantiation to initialize the xarray dataset we're running and improve performance.