Correlation between paddy rice growth and satellite-observed methane column abundance does not imply causation
Abstract
In a recent study, Zhang et al. found paddy rice area and growth were strongly correlated with CH₄ column-averaged dry-air mole fractions (XCH₄) observed from satellites in Monsoon Asia. Based on these correlations, they argued that the spatial area and growth cycle of paddy rice drive the spatial distribution and seasonality of XCH₄ in the region of the rice paddies. Here, by reanalyzing satellite XCH₄ observations and running CH₄ simulations with a chemical transport model, we show that (1) local variation in XCH₄ is primarily driven by large scale CH₄ flux signals advected into the local area rather than from local emission, indicating that variations in XCH₄ do not simply translate to variations in the underlying rice paddy emissions. (2) Spatial correlations between rice paddy extent and XCH₄ are confounded by cross-correlation with other XCH₄ emission sources that have similar spatial structures. As a result, the spatial and temporal consistencies between rice paddies and XCH₄ reported in Zhang et al. do not imply a causal relationship. The inference of emissions based on the correlation may lead to incorrect conclusions on the annual variabilities of rice paddy CH₄ emissions in Monsoon Asia.
Additional Information
© The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Received 28 May 2020; Accepted 19 January 2021; Published 19 February 2021. Z.Z. would like to thank Yuk Yung at Caltech and Stan Sander at JPL for their strong supports and stimulating discussions on greenhouse gas remote sensing. BB's research was supported by an appointment to the NASA Postdoctoral Program at the Jet Propulsion Laboratory, administered by Universities Space Research Association under contract with NASA. BB's research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). Data availability: CarbonTracker-CH4 results are provided by NOAA ESRL, Boulder, Colorado, USA (http://www.esrl.noaa.gov/gmd/ccgg/carbontracker-ch4/); The IMAP v7.2 data product from SCIAMACHY from the ESA-CCI data portal (http://www.esa-ghg-cci.org/); the EDGAR methane emission bottom-up inventory data are provided by the European Commission (https://edgar.jrc.ec.europa.eu/overview.php?v=432_GHG). Results from model simulations are available via an open-access link at https://doi.org/10.5281/zenodo.4291324.Attached Files
Published - s41467-021-21434-7.pdf
Supplemental Material - 41467_2021_21434_MOESM1_ESM.pdf
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Additional details
- Eprint ID
- 108119
- Resolver ID
- CaltechAUTHORS:20210219-110037132
- NASA Postdoctoral Program
- 80NM0018D0004
- NASA
- Created
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2021-02-19Created from EPrint's datestamp field
- Updated
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2023-06-01Created from EPrint's last_modified field