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December 6, 2012 / Damien Irving

An observational data catalogue

When I started my previous job a few years ago now, I was set the task of validating global climate model output over the tropical Pacific. The obvious first step in this process was to obtain some observational data for the region, so that I would have something to compare the model output against. To make my life easier, I wanted the observational data to be:

  • Uniform in space and time (model output comes on a uniform temporal and spatial grid, with no missing data, so it’s much easier if the observational data do too)
  • Widely used (so that there is lots of information out there about the quality of the data)
  • The latest available (methods for producing observational datasets are improving all the time, so the most recent datasets usually represent the state-of-the-art)

I soon came to realise that this was not a unique task amongst people working in the weather and climate sciences. Most of us frequently use observational data in our daily work, which is why the National Centers for Atmospheric Research established the Climate Data Guide. This wonderful resource contains a wealth of information about pretty much all of the widely used observational datasets. For the uninitiated, however, opening up the Climate Data Guide homepage can be a little like taking your first swimming lesson in the deep end of the pool. With so much information, it’s a little difficult to know where to start. I flailed around in the deep end for many hours and eventually found the information (and datasets) that I needed, however looking back I would really have appreciated a simple overview of the observational datasets out there and the different methods used to construct them.

As such, I’ve compiled an observational data catalogue. It represents a simple, concise and up-to-date summary of the latest, widely used (i.e. predominantly temperature and rainfall) observational datasets. I’ve specifically focused on datasets with global coverage (noting that many ‘global’ datasets do not have complete coverage in the high latitudes) with no temporal or spatial gaps (i.e. no annoying missing data). There are of course many regional datasets that would be of use to some people, as well as many global datasets that have substantial data gaps, however it was impractical to try and cover all of those.

The observational data catalogue is supposed to be an ever-evolving work in progress, so if you have any thoughts on the content please feel free to post a comment on the page.

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