Closed zxdawn closed 2 years ago
OK. I come up with this easier idea:
We can set the mask to the minimum value (>0) of previous masks https://github.com/zxdawn/S5P-LNO2/blob/26009d2caab0429d3a434c9a79eaa83a0e16dcf9/main/s5p_lnox_functions.py#L244-L256
The updated image is shown in https://github.com/zxdawn/S5P-LNO2/issues/2#issue-1088830325
Problem
The observed lightning flashes are clustered first and then classified into clean and polluted clusters. https://github.com/zxdawn/S5P-LNO2/blob/26009d2caab0429d3a434c9a79eaa83a0e16dcf9/main/s5p_lnox_main.py#L72-L85
However, that would split storms using the default 40 km https://github.com/zxdawn/S5P-LNO2/blob/26009d2caab0429d3a434c9a79eaa83a0e16dcf9/main/s5p_lnox_utils.py#L132-L136
This method works well for isolated storms like this: The LNO2 were produced and transported with wind:
However, there're some storms that occurred closely but were still far from 40 km. The LNO2 produced by them could mix together:
Solution
It's better to calculated the transported air containing LNO2 first, and then cluster and classify it.