Geostatistical SIMulation for the homogenisation and interpolation of CLImate data
gsimcli is a proposed method to homogenise climate data using geostatistical stochastic simulation methods.
It is presented here as a work in progress Python project. Some of its modules are intended to serve as useful libraries for other projects.
In a first stage, gsimcli will be implemented using Direct Sequential Simulation (DSS) [1]. The method description and its application have already been published [2].
It is planned to develop an implementation using Direct Sequential Simulation with local distributions.
This research project is hosted at ISEGI-NOVA (Lisbon, Portugal) and it is funded by the "Fundação para a Ciência e Tecnologia" (FCT), Portugal, through the research project PTDC/GEO-MET/4026/2012. See [approval and funding notice] (http://www.isegi.unl.pt/documentos/P_GSIMCLI_EN.pdf).
The documentation is hosted at readthedocs.org: http://gsimcli.readthedocs.org
Browse and post issues and contributions [here] (https://github.com/iled/gsimcli/issues).
- Python: 2.7
- NumPy: 1.8 or higher
- pandas 0.13.0 or higher
- DSS only the binary
- Wine only for *nix systems
GPLv3
[1]: Soares, Amílcar. Direct Sequential Simulation and Cosimulation. Mathematical Geology 33, no. 8 (2001): 911-926. http://link.springer.com/article/10.1023/A:1012246006212.
[2]: Costa, AC, and A Soares. Homogenization of Climate Data: Review and New Perspectives Using Geostatistics. Mathematical Geosciences 41, no. 3 (November 28, 2009): 291-305. doi:10.1007/s11004-008-9203-3.