Global Monthly Wetland Methane Flux Simulated at 0.5 Degrees

LPJ-EOSIM L2 Global Simulated Monthly Wetland Methane Flux Low Latency V001 provides global estimates of methane emissions from wetlands at a 0.5-degree spatial resolution. The dataset is generated by the Lund-Potsdam-Jena Earth Observation SIMulator (LPJ-EOSIM) model, which uses simulated wetland extent, soil moisture, temperature, and carbon content. It is produced by LPCLOUD to support the United States Greenhouse Gas Center and related climate research.

Use Cases

• Analyzing global spatial patterns of wetland methane flux using the 0.5-degree resolution geospatial data.
• Comparing methane emission estimates derived from different meteorological forcing datasets (MERRA-2 and ERA5).
• Studying temporal variability in wetland methane emissions using the aggregated monthly mean and standard deviation values.
• Supporting detection and attribution of climate-carbon feedback mechanisms through modeled flux data.
• Informing policy and monitoring efforts for the United States Greenhouse Gas Center (GHGC).

Strengths

• Provides global coverage at a consistent 0.5-degree spatial resolution.
• Includes data aggregated from two major reanalysis forcing datasets (MERRA-2 and ERA5) for comparison.
• Offers both mean and standard deviation calculated from the monthly aggregate data.
• Cross-platform presence on NASA Earthdata and Data.gov signals its importance and curation for the scientific community.

Limitations

• Specific temporal coverage (start/end dates) and total row/file count are not provided in any source.
• Wetland definition excludes small ponds, lakes, and coastal wetlands, which may omit some emission sources.
• Sources conflict on license details, with one specifying 'other-license-specified' and another listing 'None'.

Provenance

Source

LPCLOUD, using the Lund-Potsdam-Jena Earth Observation SIMulator (LPJ-EOSIM) model.

Collection Method

Model simulation based on wetland extent and characteristics (soil moisture, temperature, carbon content), aggregated from daily data and forced by MERRA-2 and ERA5 reanalysis datasets.

Time Range

null

Freshness

2026-03-13 00:54:37.599499

Geography

Global