Bias correcting regional scale Earth system model projections:  novel approach using empirical mode decomposition

Ganguli, Arkaprabha; Feinstein, Jeremy; Raji, Ibraheem; Akinsanola, Akintomide; Aghili, Connor; Jung, Chunyong; Branham, Jordan; Wall, Tom; Huang, Whitney; Kotamarthi, Rao

doi:https://doi.org/10.5194/gmd-18-8313-2025

Articles | Volume 18, issue 21

https://doi.org/10.5194/gmd-18-8313-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-18-8313-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 18, issue 21

Methods for assessment of models

|

06 Nov 2025

Methods for assessment of models |

| 06 Nov 2025

Bias correcting regional scale Earth system model projections: novel approach using empirical mode decomposition

Arkaprabha Ganguli, Jeremy Feinstein, Ibraheem Raji, Akintomide Akinsanola, Connor Aghili, Chunyong Jung, Jordan Branham, Tom Wall, Whitney Huang, and Rao Kotamarthi

Data sets

Full Simulation Data, Validation Indices, and Frozen Repository for the Empirical Mode Decomposition Based Bias Correction Approach Arkaprabha Gangul et al. https://doi.org/10.5281/zenodo.15244202

Model code and software

EMDBC: Empirical Mode Decomposition-based Bias Correction Arkaprabha Ganguli and Jeremy Feinstein https://github.com/jeremyfifty9/emdbc

Short summary

This study introduces a timescale-aware bias-correction framework to enhance Earth system model assessments, vital for the geoscience community. By decomposing model outputs into oscillatory components, we preserve critical information across various timescales, ensuring more reliable projections. This improved reliability supports strategic decisions in sectors such as agriculture, water resources, and disaster preparedness.