Work

BRIDGE-CH4: Code and Data for Global Soil Methane Uptake Prediction from Process-Based Simulations TEM and Chamber Observations from 1979 to 2025

Year: 2026

Type: article

Abstract: This repository contains the source code and datasets for BRIDGE-CH4, a neural-process-based framework that jointly learns from coarse-resolution TEM simulations and sparse chamber observations for global soil methane uptake prediction. It includes model implementations, training and evaluation scripts, environmental drivers, and raw/processed methane datasets. Please refer to readme.md for instructions on getting started. Thank you for using our work!

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.21603303

Author: Anonymity

Language: English

Topic: Atmospheric and Environmental Gas Dynamics

Subfield: Global and Planetary Change

Field: Environmental Science

Domain: Physical Sciences

SDG: Climate action

Open Access status: green

OpenAlex ID: W7171315905

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