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Paul Miller

Senior lecturer

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Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates

Author

  • Kuang Yu Chang
  • William J. Riley
  • Nathan Collier
  • Gavin McNicol
  • Etienne Fluet-Chouinard
  • Sara H. Knox
  • Kyle B. Delwiche
  • Robert B. Jackson
  • Benjamin Poulter
  • Marielle Saunois
  • Naveen Chandra
  • Nicola Gedney
  • Misa Ishizawa
  • Akihiko Ito
  • Fortunat Joos
  • Thomas Kleinen
  • Federico Maggi
  • Joe McNorton
  • Joe R. Melton
  • Paul Miller
  • Yosuke Niwa
  • Chiara Pasut
  • Prabir K. Patra
  • Changhui Peng
  • Sushi Peng
  • Arjo Segers
  • Hanqin Tian
  • Aki Tsuruta
  • Yuanzhi Yao
  • Yi Yin
  • Wenxin Zhang
  • Zhen Zhang
  • Qing Zhu
  • Qiuan Zhu
  • Qianlai Zhuang
Show all

Summary, in English

The recent rise in atmospheric methane (CH4) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH4 source, estimates of global wetland CH4 emissions vary widely among approaches taken by bottom-up (BU) process-based biogeochemical models and top-down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi-model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH4 emission estimates and model performance. We find that using better-performing models identified by observational constraints reduces the spread of wetland CH4 emission estimates by 62% and 39% for BU- and TD-based approaches, respectively. However, global BU and TD CH4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH4 year−1) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter-site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH4 models to move beyond static benchmarking and focus on evaluating site-specific and ecosystem-specific variabilities inferred from observations.

Department/s

  • LU Profile Area: Nature-based future solutions
  • LTH Profile Area: Aerosols
  • eSSENCE: The e-Science Collaboration
  • Centre for Environmental and Climate Science (CEC)
  • Dept of Physical Geography and Ecosystem Science
  • BECC: Biodiversity and Ecosystem services in a Changing Climate
  • MERGE: ModElling the Regional and Global Earth system

Publishing year

2023

Language

English

Pages

4298-4312

Publication/Series

Global Change Biology

Volume

29

Issue

15

Document type

Journal article

Publisher

Wiley-Blackwell

Topic

  • Climate Research

Keywords

  • benchmarking
  • bottom-up models
  • eddy covariance
  • methane emissions
  • observational constraints
  • top-down models
  • wetland modeling

Status

Published

ISBN/ISSN/Other

  • ISSN: 1354-1013