Spatial and Temporal Distribution of Global Wetland Methane Emissions During 2019–2020 Estimated From Satellite Observations Journal Article uri icon

Overview

abstract

  • Abstract; Wetlands are the largest natural source of methane, yet bottom‐up models and top‐down models do not agree on global wetland methane emissions. In this study, we use TROPOMI methane data and inverse modeling to estimate the spatial and temporal distribution of global wetland methane emissions during the years 2019–2020 and compare inverse modeling results with an ensemble of 16 bottom‐up wetland models from the Global Carbon Project (GCP). We find that our inverse model increases wetland methane emissions near the equator (0–15) by 7% and decreases emissions in mid‐ and high‐latitude regions (31–90) by 26% compared to the mean of the GCP models. We also find that our inverse modeling estimate exhibits little seasonality in wetland methane emissions across most tropical wetland regions, even when emissions estimates within the prior include seasonality. This result is consistent with some bottom‐up models but not others. For mid‐ and high‐latitude wetland regions (e.g., the West Siberian lowland and Hudson Bay Great Lakes region), the seasonality of our inverse emissions estimate is consistent with most GCP models and suggests wetland methane emissions peak in July. Furthermore, we argue that an inundation map with accurate seasonality is a prerequisite for obtaining a bottom‐up methane emission estimate with appropriate seasonality. Overall, many of the bottom‐up models examined in this study agree with the magnitude and seasonality of the inverse model in major wetland regions, but there are nonetheless many opportunities to improve convergence between the bottom‐up and top‐down estimates.

publication date

  • December 28, 2025

Date in CU Experts

  • March 9, 2026 8:52 AM

Full Author List

  • Chen A; Zhang Z; Poulter B; Feng L; Liu H; Murray LT; Yu X; Huang Z; Gaeta DC; Morgan KL

author count

  • 12

Other Profiles

International Standard Serial Number (ISSN)

  • 2169-897X

Electronic International Standard Serial Number (EISSN)

  • 2169-8996

Additional Document Info

volume

  • 130

issue

  • 24

number

  • e2025JD044354