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

Bibliographische Detailangaben
Veröffentlicht in:	Global change biology. - 1999. - 29(2023), 15 vom: 16. Aug., Seite 4298-4312
1. Verfasser:	Chang, Kuang-Yu (VerfasserIn)
Weitere Verfasser:	Riley, William J, Collier, Nathan, McNicol, Gavin, Fluet-Chouinard, Etienne, Knox, Sara H, Delwiche, Kyle B, Jackson, Robert B, Poulter, Benjamin, Saunois, Marielle, Chandra, Naveen, Gedney, Nicola, Ishizawa, Misa, Ito, Akihiko, Joos, Fortunat, Kleinen, Thomas, Maggi, Federico, McNorton, Joe, Melton, Joe R, Miller, Paul, Niwa, Yosuke, Pasut, Chiara, Patra, Prabir K, Peng, Changhui, Peng, Sushi, Segers, Arjo, Tian, Hanqin, Tsuruta, Aki, Yao, Yuanzhi, Yin, Yi, Zhang, Wenxin, Zhang, Zhen, Zhu, Qing, Zhu, Qiuan, Zhuang, Qianlai
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2023
Zugriff auf das übergeordnete Werk:	Global change biology
Schlagworte:	Journal Article benchmarking bottom-up models eddy covariance methane emissions observational constraints top-down models wetland modeling Methane OP0UW79H66 mehr... Carbon Dioxide 142M471B3J

Beschreibung
Zusammenfassung:	© 2023 John Wiley & Sons Ltd. 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
Beschreibung:	Date Completed 06.07.2023 Date Revised 31.08.2023 published: Print-Electronic CommentIn: Glob Chang Biol. 2023 Aug;29(15):4175-4177. - PMID 37191537 Citation Status MEDLINE
ISSN:	1365-2486
DOI:	10.1111/gcb.16755