GWGEN: A global weather generator for daily data

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Welcome! This synthesis of FORTRAN and Python is a globally applicable weather generator inspired by the original WGEN weather generator of [Richardson1981]_ and parameterized through a global dataset of [GHCN]_ and [EECRA]_ data. A paper with the scientific documentation is in progress, the technical documentation_ with more information is hosted on github.io.

.. _technical documentation: https://arve-research.github.io/gwgen/

Authors

This package has been developped by Philipp S. Sommer_ and Jed O. Kaplan_.

Citing GWGEN

When using GWGEN, we kindly ask you to provide a reference to the corresponding paper published in Geoscientific Model Development:

Sommer, P. S. and Kaplan, J. O.: *A globally calibrated scheme for
generating daily meteorology from monthly statistics: Global-WGEN (GWGEN)
v1.0*, Geosci. Model Dev., 10, 3771-3791, DOI: `10.5194/gmd-10-3771-2017`_,
2017.

.. _10.5194/gmd-10-3771-2017: https://doi.org/10.5194/gmd-10-3771-2017

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 Washingtion for providing free of charge the GHCN-Daily and EECRA databases, respectively.

.. _Philipp S. Sommer: https://github.com/Chilipp .. _Jed O. Kaplan: https://github.com/jedokaplan .. _Shawn Koppenhoefer: http://arve.unil.ch/people/shawn-koppenhoefer/

References

.. [Richardson1981] Richardson, C. W.: Stochastic simulation of daily precipitation, temperature, and solar radiation, Water Resources Research, 17, 182–190, doi:10.1029/WR017i001p00182, 1981. .. [GHCN] T. G.: Global Historical Climatology Network - Daily (GHCN-Daily), Version 3.22, doi:10.7289/V5D21VHZ, doi:10.7289/V5D21VHZ, 2012 .. [EECRA] Hahn, C. and Warren, 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