Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Curation Notes
• Data Files
• Supplemental Files
• Related Publications
• Related Datasets
• Parameters
• Project Information
• Funding

A global ocean methane cycle model was developed using the transport matrix method approach in the MATLAB programming language. In the model, the dissolved methane concentration distribution is controlled by the following processes: (i) equilibration with time-varying atmospheric methane partial pressure; (ii) loss due to first-order oxidation; (iii) in situ production in surface waters, linked to a prescribed phosphate distribution; (iv) transport and mixing by the large-scale circulation, as represented by the Ocean Circulation Inverse Model version 2. The model is first solved for a preindustrial (year 1700) steady-state methane distribution using Newton's method, and then time-stepped forwards to the year 2014.

For a full model description, including the data input and contraints, as well as the key parameterizations, see Wang et al., 2026 (DOI: 10.1073/pnas.2521235123) methods section. The model code is publicly available from the Zenodo archive (DOI: 10.5281/zenodo.15875413.). 

The output NetCDF data file accompanies Wang et al., 2026. It contains the global open-ocean distribution of methane as a function of time, predicted by a model in which methane equilibrates with atmosphere, oxidizes in the water column, and is produced in the surface ocean due to degradation of the organic compound methylphosphonate (modeled as a function of PO4 scarcity). Also included are the contributions of pre-industrial methane, anthropogenic methane, and biologically-produced methane to the distribution.

Grid structure
Grid information for the Ocean Circulation Inverse Model used in our simulations of the Methane Production Models. Contains the fields:

• x: Longitude of grid cell centers in degrees East of Prime meridian
• y: Latitude of grid cell centers in degrees North of Equator
• z: Depth of the grid cell center (m)
• M3d: Land/ocean masks (1 = ocean, 0 = land)
• VOL: Volume of each grid cell (m3)
• Year: Years from 1700 to 2014 at which the model results are recorded.

Model output

• CH4: Four-dimensional global ocean methane distribution in nM units (latitude x longitude x depth x time)
• CH4_production: Three-dimensional rate of aerobic methane production, modeled as a function of phosphate scarcity, in μmol m-3 yr-1 units (latitude x longitude x depth)
• PO4_corrected: The global distribution of phosphate (mmol m-3 units) that CH4 production is linked to – this is from World Ocean Atlas 2018 (WOA18) but adjusted using high precision data, to correct for the tendency of WOA18 to overestimate PO4 at low conentrations.
• CH4_pre: Three-dimensional distribution of CH4 (latitude x longitude x depth x time; nM units) that originated from equilibration with the pre-industrial atmosphere.
• CH4_anthro: Three-dimensional distribution of CH4 (latitude x longitude x depth x time; nM units) that accumulated in the ocean (as of 2014) due to equilibration with increasing atmospheric pCH4 (from anthropogenic sources).
• CH4_bio: Three-dimensional distribution of CH4 (latitude x longitude x depth x time; nM units) that originated from biological production in the oxic surface ocean.

The MATLAB output produced by the model ('final_result.mat') was converted into NetCDF format. See the Related Datasets for full MATLAB workflow (Wang & Weber, 2025).

- Header information was extracted from Wang_2026_model_output.nc and added to the file comment so parameters in the file are clearer in the metadata and are searchable
- Wang_2026_model_output.nc attached as the primary data file

NSF Award Abstract:
Methane is a potent greenhouse gas with a global warming potential thirty times larger than carbon dioxide. In addition to human emissions methane has many natural sources to the atmosphere, which could be amplified by future climate warming. Methane emissions from the vast open ocean are relatively small but their sensitivity to climate change is highly uncertain. This is because the processes that supply methane to surface ocean waters are not well understood. To improve our understanding of the open ocean methane cycle, this project will use a computer model to interpret a large database of methane concentration measurements. First, the model will be used to determine the dominant biological source of methane within surface waters. Candidates include production during algae growth, production in the guts of small animals, and bacterial decay of organic matter. Each of these processes would produce a different surface methane pattern, allowing the model to distinguish between them. Second, the model will quantify the supply of methane from the seafloor in low oxygen zones of the ocean, and determine whether this methane is consumed by bacteria before escaping to the atmosphere. This is important because low oxygen zones will likely grow as the climate warms. Leakage of methane from these regions could therefore act as a feedback on climate change.

The global model developed in this project will simulate the open ocean sources and sinks of methane, including in situ aerobic methanogenesis in surface waters, diffusion from anoxic sediments, oxidation in the water column, and exchange with the atmosphere. Data will be assimilated to optimize model parameters, and ultimately determine the balance of sources and sinks that is most consistent with the observed ocean methane distribution. Aerobic methane production will be formulated as function of phytoplankton growth, zooplankton abundance, and organic matter recycling, to determine which mechanisms best explains the pattern of surface methane supersaturation. The oxygen dependence of sedimentary methane sources and bacterial methane oxidation will be optimized to best match the observed plumes that spread laterally from suboxic waters and upwell towards the surface. The resulting optimized model will then be used to predict future perturbation of the open ocean methane source in response to ecosystem changes and ocean oxygen loss.