Post-processed data and graphical tools for a CONUS-wide eddy flux evapotranspiration dataset

Volk, John; Huntington, Justin L.; Melton, F. S.; Minor, Blake; Wang, Tianxin; Anapalli, Saseendran S.; Anderson, Ray G.; Evett, Steven R.; French, Andrew N.; Jasoni, Richard L.; Bambach, Nicolás; Kustas, W. P.; Alfieri, Joseph G.; Prueger, John H.; Hipps, Lawrence E.; McKee, L.; Castro, Sebastian J.; Alsina, María Mar; McElrone, Andrew J.; Reba, M. L.; Runkle, Benjamin R. K.; Saber, Meryem; Sánchez, C. A.; Tajfar, E.; Allen, Richard G.; Anderson, Mark

doi:10.1016/j.dib.2023.109274

Cited by 3 publications

(14 citation statements)

References 15 publications

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“…1) 19 . The SIMS model Mean monthly summary statistics for comparisons between OpenET 5 ensemble members ET and closed flux tower monthly ET 19,20 for agricultural sites grouped by Köppen-Geiger climate zones 34 . Slope is calculated as the linear regression slope forced through the origin.…”

Section: Performance In Natural Ecosystemsmentioning

confidence: 99%

Section: Flux Data Processing and Footprint Samplingmentioning

confidence: 99%

“…We used a curated benchmark eddy flux-based ET dataset 19,20 and tools for use in this and subsequent evaluations of OpenET RSET models 5 . The rationale and decision-making steps for the collection and post-processing of flux data, as well as analyses of footprint sampling techniques and energy balance closure error within the dataset, are described in Volk et al 19,20 . Data processing techniques for gap-filling and correction for energy balance closure error were conducted using open-source Python tools 56 that enhance data provenance and reproducibility.…”

Section: Flux Data Processing and Footprint Samplingmentioning

confidence: 99%

“…Flux footprints are twodimensional mappings of the areal extent of a station's source area, that is, the area on the ground that contributes to fluxes measured by the tower instrumentation. Refer to Methods and Volk et al 19,20 for details on flux data processing and footprint mapping methods used. Additional discussion of uncertainty in EC data and steps taken to limit that uncertainty are provided in Supplementary Discussion 1.…”

mentioning

confidence: 99%

“…In this Analysis, we present a large-scale benchmark assessment of the accuracy of OpenET data using a well-curated publicly archived dataset of in situ ET measurements from 152 stations (141 eddy covariance (EC) systems, 7 Bowen ratio systems and 4 lysimeters), over a variety of regions, climates and land cover types 19,20 , collectively comprising ~45 years of paired model-measurement ET data (Fig. 1).…”

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confidence: 99%

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Assessing the accuracy of OpenET satellite-based evapotranspiration data to support water resource and land management applications

Volk,

Huntington,

Melton

et al. 2024

Nat Water

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Remotely sensed evapotranspiration (ET) data offer strong potential to support data-driven approaches for sustainable water management. However, practitioners require robust and rigorous accuracy assessments of such data. The OpenET system, which includes an ensemble of six remote sensing models, was developed to increase access to field-scale (30 m) ET data for the contiguous United States. Here we compare OpenET outputs against data from 152 in situ stations, primarily eddy covariance flux towers, deployed across the contiguous United States. Mean absolute error at cropland sites for the OpenET ensemble value is 15.8 mm per month (17% of mean observed ET), mean bias error is −5.3 mm per month (6%) and r2 is 0.9. Results for shrublands and forested sites show higher inter-model variability and lower accuracy relative to croplands. High accuracy and multi-model convergence across croplands demonstrate the utility of a model ensemble approach, and enhance confidence among ET data practitioners, including the agricultural water resource management community.

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