cfr: a Python package for Climate Field Reconstruction

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.

cfr: a Python package for Climate Field Reconstruction

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.

cfr: a Python package for Climate Field Reconstruction

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.