Note
If you use cfr in any way for your publications, please cite:
- Zhu, F., Emile-Geay, J., Hakim, G. J., Guillot, D., Khider, D., Tardif, R., & Perkins, W. A. (2024). cfr (v2024.1.26): a Python package for climate field reconstruction. Geoscientific Model Development, 17(8), 3409–3431. https://doi.org/10.5194/gmd-17-3409-2024
- Zhu, F., Emile-Geay, J., Anchukaitis, K.J., McKay, N.P., Stevenson, S., Meng, Z., 2023. A pseudoproxy emulation of the PAGES 2k database using a hierarchy of proxy system models. Sci Data 10, 624. https://doi.org/10.1038/s41597-023-02489-1
cfr aims to provide a universal framework for climate field reconstruction (CFR).
It provides a toolkit for
- the processing and visualization of the proxy records, climate model simulations, and instrumental observations,
- the calibration and running of the proxy system models (PSMs, Evans et al., 2013),
- the preparation and running of the multiple reconstruction frameworks/algorithms, such as LMR (Hakim et al., 2016; Tardif et al., 2019) and GraphEM (Guillot et al., 2015), and
- the validation of the reconstructions, etc.
For more details, please refer to the documentation linked below.
- Homepage: https://fzhu2e.github.io/cfr
- Installation: https://fzhu2e.github.io/cfr/ug-installation.html