Updating CLI and Acceptance Tests for non-default scale factors.

[mo-jbeaver]

Addresses #1151

This PR implements changes to the uv_index CLI and Acceptance Test.
This provides the option to use a non-default scale-factor via the CLI.

Testing:

• Ran tests and they passed OK
• Added new tests for the new feature(s)

[mo-kbogue]

I ran the acceptance test with no issues, though looking at the unit tests in improver_tests/uv_index/test_uv_index.py, I think that it may be worth adding some additional unit tests. There is already a unit test for non-default scale factor (in which 10 is used), but it might be worth taking other possibilities into account, such as including the case where a scale factor of 0 is received.

I would also like to have a better understanding and written record of where the 0.1 factor come from. From reading the previous tickets, it seems as is this possibly ported over from SPSS, but where did the 0.1 arise from in SPSS? If the justification is not clear, it may be worth revisiting if this is going to produce the best UV index for users. I do see that the jupyter notebook in the associated PR (#530) tests this 0.1 scaling and it does appear to give a reasonable answer, but is this enough of a scientific justification for its use? If we are confident in the 0.1 scaling factor, we should make sure that the reasons for this are clear and accessible.

[mo-kbogue]

Given that the user is now able to change the scale factor, that it has been empirically derived as 3.6 and it seems strongly encouraged to not change this, should we include a warning to the user if they put in a scale factor that is not the default?