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Amazonian terrestrial water balance inferred from satellite-observed water vapor isotopes

Shi, Mingjie and Worden, John R. and Bailey, Adriana and Noone, David and Risi, Camille and Fu, Rong and Worden, Sarah and Herman, Robert and Payne, Vivienne and Pagano, Thomas and Bowman, Kevin and Bloom, A. Anthony and Saatchi, Sassan and Liu, Junjie and Fisher, Joshua B. (2022) Amazonian terrestrial water balance inferred from satellite-observed water vapor isotopes. Nature Communications, 13 . Art. No. 2686. ISSN 2041-1723. PMCID PMC9106687. doi:10.1038/s41467-022-30317-4.

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Atmospheric humidity and soil moisture in the Amazon forest are tightly coupled to the region’s water balance, or the difference between two moisture fluxes, evapotranspiration minus precipitation (ET-P). However, large and poorly characterized uncertainties in both fluxes, and in their difference, make it challenging to evaluate spatiotemporal variations of water balance and its dependence on ET or P. Here, we show that satellite observations of the HDO/H₂O ratio of water vapor are sensitive to spatiotemporal variations of ET-P over the Amazon. When calibrated by basin-scale and mass-balance estimates of ET-P derived from terrestrial water storage and river discharge measurements, the isotopic data demonstrate that rainfall controls wet Amazon water balance variability, but ET becomes important in regulating water balance and its variability in the dry Amazon. Changes in the drivers of ET, such as above ground biomass, could therefore have a larger impact on soil moisture and humidity in the dry (southern and eastern) Amazon relative to the wet Amazon.

Item Type:Article
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URLURL TypeDescription ItemData CentralArticle
Shi, Mingjie0000-0002-2469-4831
Worden, John R.0000-0003-0257-9549
Bailey, Adriana0000-0002-2614-1560
Herman, Robert0000-0001-7063-6424
Payne, Vivienne0000-0002-9204-9703
Bowman, Kevin0000-0002-8659-1117
Bloom, A. Anthony0000-0002-1486-1499
Saatchi, Sassan0000-0001-8524-4917
Liu, Junjie0000-0002-7184-6594
Additional Information:© The Author(s) 2022. 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 Received 12 February 2021; Accepted 26 April 2022; Published 13 May 2022. This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract (80NM0018D0004) with the National Aeronautics and Space Administration. We thank Adam J. Purdy for providing the PT-JPL data. We also thank Fernando Galvan and Lingcheng Li for map visualization. AIRS HDO/H2O data were processed as part of the NASA Tropospheric Ozone and its Precursors from Earth System Sounding (TROPESS). MS was partly supported by the U.S. Department of Energy Office of Science Biological and Environmental Research as part of the Terrestrial Ecosystem Science Program through the Next-Generation Ecosystem Experiments (NGEE) Tropics project. PNNL is operated by Battelle Memorial Institute for the U.S. DOE under contract DE-AC05-76RLO1830. JBF was supported in part by NASA programs: ECOSTRESS and SUSMAP. Part of this material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under Cooperative Agreement No. 1852977. The LES simulations to quantify the clear-sky sampling bias of AIRS used HPC resources of TGCC under the allocation 0292 made by GENCI. Data availability: The source data used to generate all plots and graphs and the plotting scripts are provided at Due to the large size of the raw data and iCAM output, these files were not deposited in a public repository, but are available from the corresponding authors on reasonable request. Contributions: J.W. led and designed the analysis approach. M.S. performed the analysis. A.B. provided an interpretation of the deuterium-based ET-P proxy. M.S., J.W., A.B., and J.F. wrote the paper. D.N., C.R., R.F., and S.W. supported the analysis through modeling studies and interpretation of re-analysis. R.H., V.P., and D.N. supported calibration and validation of the satellite deuterium data. T.P. supported the interpretation of the AIRS instrument calibration. K.B., A.B., S.S., J.L., and J.F. provided ET estimates and helped result interpretation. The authors declare no competing interests. Peer review information: Nature Communications thanks Rosane Cavalcante and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Funding AgencyGrant Number
Department of Energy (DOE)DE-AC05-76RLO1830
Subject Keywords:Atmospheric chemistry; Hydrology
PubMed Central ID:PMC9106687
Record Number:CaltechAUTHORS:20220531-508108500
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Official Citation:Shi, M., Worden, J.R., Bailey, A. et al. Amazonian terrestrial water balance inferred from satellite-observed water vapor isotopes. Nat Commun 13, 2686 (2022).
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:114965
Deposited By: Tony Diaz
Deposited On:31 May 2022 17:53
Last Modified:31 May 2022 17:53

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