Julia package to download and analyse ECMWF reanalysis data, with some calculations for other variables thrown in.
Author natgeo-wong
2 Stars
Updated Last
2 Years Ago
Started In
October 2019


Repo Status Travis CI Documentation Build
MIT License Latest Release Latest Documentation Latest Documentation

Created By: Nathanael Wong (

Developer To-Do for v1.0:

  • Testing of analysis functions
  • Comprehensive documentation and Jupyter notebook examples
  • eraquery function series development


ClimateERA.jl is a Julia package that aims to streamline the following processes:

  • downloading of ECMWF reanalysis data (ERA-Interim and ERA5)
  • basic analysis (mean, maximum, minimum, standard deviation, etc.) of downloaded data
  • extraction of data for a given GeoRegion (see GeoRegions.jl for more information)

ClimateERA.jl can be installed via

] add ClimateERA


There are some non-Julia functionalities required in order to download reanalysis data using ClimateERA.jl:

  • A working Python installation
  • For ERA-Interim, please follow the instructions here to install the ECMWF API
  • For ERA5, please follow the instructions here to install the CDS API

ECMWF Reanalysis

Both ERA-Interim and ERA5 are produced by the European Centre for Medium-Range Weather Forecasts. For more information regarding the ERA-Interim and ERA5 reanalysis models, please refer to the following:


Startup and Initialization



By default, ClimateERA.jl saves all data into a datadir repository that is user-specified, or else it will otherwise default to



ClimateERA.jl utlizes GeoRegions.jl to specify domains from which data is to be extracted. If the option is not specified, then ClimateERA.jl will assume that the user wishes to process global data (which may not be wise especially for GPM due to the large file sizes involved and memory required).

For more information, please see the repository for GeoRegions.jl here.


ClimateERA.jl does not directly download reanalysis data from ECMWF/CDS. Instead, it generates a Python script according to the user's choice of parameters that the user will run with Python to download the data required.

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