Abstract

Climate field reconstruction (CFR) refers to the estimation of spatiotemporal climate fields (such as surface temperature) from a collection of pointwise paleoclimate proxy datasets. The climate fields can provide rich information on climate dynamics and provide an out-of-sample validation of climate models. However, most CFR workflows are usually complex and time-consuming, as it involves:(i) preprocessing of the proxy records, climate model simulations, and instrumental observations,(ii) application of one or more statistical methods, and (iii) analysis and visualization of the reconstruction results. Historically, this process has lacked transparency and accessibility, limiting reproducibility and experimentation by non-specialists. This study presents an open-source and object-oriented Python package called cfr that aims to make CFR workflows easy to understand and conduct, saving climatologists from technical …

Date

January 1, 1970

Authors

Feng Zhu, Julien Emile-Geay, Gregory J Hakim, Dominique Guillot, Robert Tardif, Andre Perkins, Deborah Khider

Journal

AGU Fall Meeting Abstracts

Volume

2023

Issue

1249

Pages

PP13D-1249