GWGEN v1.0.2: A global weather generator for daily data
Creators
- 1. Institute of Earth Surface Dynamics, University of Lausanne
- 2. Institute of Earth Surface Dynamics, University of Lausanne; Max Planck Institute for the Science of Human History, Jena, Germany
Description
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 https://arve-research.github.io/gwgen/
Files
- gwgen-1.0.2.zip: The full source files for FORTRAN and Python including the data for unittests
- gwgen-1.0.2-no-test-data.zip: The full source files without test data
- gwgen_docs_v1.0.2.zip: The documentation as static html
- gwgen-conda-1.0.2-Linux-x86_64_2.7.sh: A bash installer for Linux with python 2.7
- gwgen-conda-1.0.2-Linux-x86_64_3.6.sh: A bash installer for Linux with python 3.6
- gwgen-conda-1.0.2-MacOSX-x86_64_2.7.sh: A bash installer for MacOSX with python 2.7
- gwgen-conda-1.0.2-MacOSX-x86_64_3.6.sh: A bash installer for MacOSX with python 3.6
Installation from source
To install the source files in gwgen-1.0.2.zip, you need python, numpy, matplotlib, sqlalchemy, statsmodels, scipy and pandas to be preinstalled. Then you can run
python setup.py 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
bash gwgen-conda-1.0.2-Linux-x86_64_2.7.sh
and follow the instructions.
Acknowledgements
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.
Files
gwgen-1.0.2-no-test-data.zip
Files
(1.1 GB)
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Additional details
Related works
- Is supplement to
- https://github.com/ARVE-Research/gwgen/tree/v1.0.2 (URL)
Funding
References
- 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, http://dx.doi.org/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, http://dx.doi.org/10.3334/CDIAC/cli.ndp026c, 1999.