Apply Dask to parallelise acs_regional_stats

`acs_regional_stats` can be very memory intensive to run, particularly over many regions and many timesteps.
We should develop an example of running `acs_regional_stats` for many years of daily data to produce area averaged timeseries for regions. Currently, this is [possible](https://github.com/AusClimateService/plotting_maps/blob/main/example_notebooks/FAQ_example_timeseries_stats.ipynb), but will take several minutes to calculate.
Dask is likely to be able to achieve this by calculating area averages per file.
Previous development has focused on reducing memory usage through other clever means, such as implementing `chunks` to reduce the number of timesteps loaded into the memory to calculate stats over each time. This could be parallelised, but it is not currently.

Start with example_notebooks/FAQ_example_timeseries_stats.ipynb and the acs_regional_stats entry point, then run the current multi-year daily calculation to establish its memory use and runtime. Develop the requested Dask-based example that calculates area averages per file, and verify that it produces regional time series while reducing the current several-minute, memory-intensive workload.

索引モデルが issue の本文から書いたものです。