Pretty much what the title says. For my work I need historic (at least starting 2010), atmospheric weather data (mostly temperature at 2m, wind velocity and direction, humidity respectively dewpoint, nothing fancy) in hourly frequency and ERA5 delivers that globally and conveniently via free API access.

But I'd like to concentrate on areas with high population density (basically large cities) and I'm a bit afraid, that the ~30km grid of ERA5 is a bit too coarse to capture that accurately, especially for cities with a very high population density in a smaller area, as it is often the case for old European cities.

Does anyone know a data source that can offer this weather data on a higher resolution grid (10km, 5km, ...?) but with otherwise similar features as the ERA5 data (variables, frequency, access, ...)?

Degrees of Freedom: I'm fine if the coverage would be restricted to urban centers, I'm not interested in rural areas. Equally, if such data would only be available in parts of the world (e.g. only Europe or only North America), that would be acceptable if not ideal.

Restrictions: However, I'm not interested in just a collection of 'local' weather stations because I need to avoid any bias from any uncorrected measurements below blending height. I do not have the capability to do such corrections myself and due to the nature of my work I need a 'synoptic' base for my data. For example wind velocity at 10m should be provided in a similar fashion as by ERA5: with a roughness factor of grass, since I'd like to introduce my own surface parameters instead. (Ref: https://confluence.ecmwf.int/display/FUG/9.3+Surface+Wind)

Possible Workaround: Im not very well versed in ERA5 data (not meteorologist by training), so there might be a way to extract this data from the model by accessing sub-grid information in some way?

Currently I'm using code like this to grab my data:

        'product_type': 'reanalysis',
        'format': 'grib',
        'variable': climatevars,
        'area': bbox.bbox,
        'year': year,
        'month': month,
        'day': times.day,
        'time': times.time,

I hope this makes sense, if not please ask! I'm thankful for any tips!


1 Answer 1


I think the ERA5-Land dataset suits your purpose. See https://www.ecmwf.int/en/era5-land. As the website says, 'The data is a replay of the land component of the ERA5 climate reanalysis with a finer spatial resolution: ~9km grid spacing.'

  • $\begingroup$ Right what I was looking for :) Note to anyone using this: the retrieval via API is much slower with era5-land than with era5. $\endgroup$ Dec 19, 2022 at 10:44

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