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Chu H, Christianson DS, Cheah YW, Pastorello G, O'Brien F, Geden J, Ngo ST, Hollowgrass R, Leibowitz K, Beekwilder NF, Sandesh M, Dengel S, Chan SW, Santos A, Delwiche K, Yi K, Buechner C, Baldocchi D, Papale D, Keenan TF, Biraud SC, Agarwal DA, Torn MS. AmeriFlux BASE data pipeline to support network growth and data sharing. Sci Data 2023; 10:614. [PMID: 37696825 PMCID: PMC10495345 DOI: 10.1038/s41597-023-02531-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 08/31/2023] [Indexed: 09/13/2023] Open
Abstract
AmeriFlux is a network of research sites that measure carbon, water, and energy fluxes between ecosystems and the atmosphere using the eddy covariance technique to study a variety of Earth science questions. AmeriFlux's diversity of ecosystems, instruments, and data-processing routines create challenges for data standardization, quality assurance, and sharing across the network. To address these challenges, the AmeriFlux Management Project (AMP) designed and implemented the BASE data-processing pipeline. The pipeline begins with data uploaded by the site teams, followed by the AMP team's quality assurance and quality control (QA/QC), ingestion of site metadata, and publication of the BASE data product. The semi-automated pipeline enables us to keep pace with the rapid growth of the network. As of 2022, the AmeriFlux BASE data product contains 3,130 site years of data from 444 sites, with standardized units and variable names of more than 60 common variables, representing the largest long-term data repository for flux-met data in the world. The standardized, quality-ensured data product facilitates multisite comparisons, model evaluations, and data syntheses.
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Affiliation(s)
- Housen Chu
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
| | | | - You-Wei Cheah
- Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Gilberto Pastorello
- Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Fianna O'Brien
- Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Joshua Geden
- Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Sy-Toan Ngo
- Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Rachel Hollowgrass
- Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA, 94720, USA
| | | | - Norman F Beekwilder
- Department of Computer Science, University of Virginia, Charlottesville, VA, 22903, USA
| | - Megha Sandesh
- Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Sigrid Dengel
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Stephen W Chan
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - André Santos
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Kyle Delwiche
- Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Koong Yi
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Christin Buechner
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Dennis Baldocchi
- Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Dario Papale
- DIBAF, University of Tuscia, Viterbo, 01100, Italy
- Euro-Mediterranean Center on Climate Change CMCC IAFES, Viterbo, 01100, Italy
| | - Trevor F Keenan
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
- Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Sébastien C Biraud
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Deborah A Agarwal
- Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Margaret S Torn
- Climate & Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
- Energy and Resources Group, University of California Berkeley, Berkeley, CA, 94720, USA
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Albedo-Induced Global Warming Impact at Multiple Temporal Scales within an Upper Midwest USA Watershed. LAND 2022. [DOI: 10.3390/land11020283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Land surface albedo is a significant regulator of climate. Changes in land use worldwide have greatly reshaped landscapes in the recent decades. Deforestation, agricultural development, and urban expansion alter land surface albedo, each with unique influences on shortwave radiative forcing and global warming impact (GWI). Here, we characterize the changes in landscape albedo-induced GWI (GWIΔα) at multiple temporal scales, with a special focus on the seasonal and monthly GWIΔα over a 19-year period for different land cover types in five ecoregions within a watershed in the upper Midwest USA. The results show that land cover changes from the original forest exhibited a net cooling effect, with contributions of annual GWIΔα varying by cover type and ecoregion. Seasonal and monthly variations of the GWIΔα showed unique trends over the 19-year period and contributed differently to the total GWIΔα. Cropland contributed most to cooling the local climate, with seasonal and monthly offsets of 18% and 83%, respectively, of the annual greenhouse gas emissions of maize fields in the same area. Urban areas exhibited both cooling and warming effects. Cropland and urban areas showed significantly different seasonal GWIΔα at some ecoregions. The landscape composition of the five ecoregions could cause different net landscape GWIΔα.
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