Analysing large amounts (many petabytes and millions of files) of climate and weather data requires using specialised software and data indexes, as well as access to the datasets themselves.
Our Data Analysis environment includes a range of tools to make this easy - documented here.
These work in combination with a python API, called intake, to access a fast "database" of the file-level metadata. For climate and weather data, the most popular variant of this is called intake-esm; a more minimal set of metadata most relevant to the climate domain. The software for using intake-esm is described within our data analysis materials.
Below are some examples of probing some of the major datasets and how to manipulate this metadata.