Bias Correction of CESM2 Output In a Modern Python Framework

This presentation will highlight progress and recent updates on a continuing project to convert legacy software to a modern Python framework to calculate a global bias-corrected climate dataset from the NCAR Community Earth System Model (CESM2) output. The existing legacy software, written in the NCAR Command Language (NCL) and Fortran, uses the bias correction technique described in Bruyère et al. (2015) and was applied to CESM output from simulations that participated in phase 5 of the Coupled Model Intercomparison Experiment (CMIP5). The updated software described in this presentation applies the same bias correction method and is written in a modern and open Python framework, and will be applied to CESM2 output from the CMIP6 initiative.

Building on work that was presented at the 2024 AMS Annual Meeting, recent work focuses on carrying out the full bias correction for a single, two-dimensional, near-surface variable. This subtask serves as an initial exercise to test and verify the feasibility of the Python frameworks used in the calculation (Xarray, Dask, GeoCAT, Numba). A longer term objective will then be to apply this calculation to the larger, 3-dimensional model output variables; progress on this task will be presented if appropriate.

Although the immediate goal is to bias correct the CESM2 output that participated in CMIP6, a long-term goal is to generalize the code to be used with any of the CF-formatted GCMs prevalent in the research community. It therefore will serve as an open, accessible, and valuable Python tool for the research community at large.