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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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Error estimates of Amazon catchment-balance evapotranspiration

Research datakeyboard_double_arrow_right Dataset 04 Mar 2021 English Publisher:Zenodo
Authors: Baker, Jessica C. A.;

doi: 10.5281/zenodo.4580292 , 10.5281/zenodo.4580291

Error estimates of Amazon catchment-balance evapotranspiration

Abstract

Monthly-scale estimates of error in Amazon-mean catchment-balance evapotranspiration (ET) from 2003 to 2013. The file includes absolute errors in precipitation (sigma_P), river runoff (sigma_R) and change in groundwater storage (sigma_dSdt), absolute errors in ET (sigma_ET), Amazon catchment-scale ET estimates (in mm), and the relative error in ET (in %). Errors were calculated by propagating errors in each term of the water budget equation. Catchment level estimates of climate variables used to estimate Amazon catchment-balance ET are provided here https://doi.org/10.5281/zenodo.4271331. Full details of all source datasets and methods are provided in 'Evapotranspiration in the Amazon: spatial patterns, seasonality and recent trends in observations, reanalysis and CMIP models' in Hydrology and Earth System Sciences, https://doi.org/10.5194/hess-2020-523.

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