Software Open Access

GWGEN v1.0.2: A global weather generator for daily data

Philipp S. Sommer; Jed O. Kaplan

This synthesis of FORTRAN and Python is a globally applicable
weather generator inspired by the original WGEN weather generator of
Richardson, 1981 and parameterized through a global dataset of GHCN (Menne et al., 2012) and
EECRA (Hahn and Warren, 1999) data.
The technical documentation can be seen under



  • The full source files for FORTRAN and Python including the data for unittests
  • The full source files without test data
  •  The documentation as static html
  • A bash installer for Linux with python 2.7
  • A bash installer for Linux with python 3.6
  • A bash installer for MacOSX with python 2.7
  • A bash installer for MacOSX with python 3.6


Installation from source

To install the source files in, you need python, numpy, matplotlib, sqlalchemy, statsmodels, scipy and pandas to be preinstalled. Then you can run

python install

to install the python files

Installation using the bash installer

The bash installers listed above contain a self-contained conda environment that includes all dependencies for GWGEN and GWGEN itself. You need to install a FORTRAN compiler, e.g. gfortran, by yourself.

Just run


and follow the instructions.



This work was supported by the European Research Council (COEVOLVE, 313797) and the Swiss National Science
Foundation (ACACIA, CR10I2_146314). We thank Shawn Koppenhoefer for assistance compiling and querying the weather databases and Alexis Berne and Grégoire Mariéthoz for helpful suggestions on the analyses. We are grateful to NOAA NCDC and the University of Washington for providing free of charge the GHCN-Daily and EECRA databases, respectively.

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  • Richardson, C. W.: Stochastic simulation of daily precipitation, temperature, and solar radiation, Water Resources Research, 17, 182–190, doi:10.1029/WR017i001p00182, 1981.

  • Menne, M. J., Durre, I., Vose, R. S., Gleason, B. E., and Houston, T. G.: An Overview of the Global Historical Climatology Network-Daily Database, J. Atmos. Oceanic Technol., 29, 897–910, doi:10.1175/jtech-d-11-00103.1,, 2012b.

  • Hahn, C. andWarren, S.: Extended Edited Synoptic Cloud Reports from Ships and Land Stations Over the Globe, 1952-1996 (with Ship data updated through 2008), doi:10.3334/CDIAC/cli.ndp026c,, 1999.

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