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Modeled Surface‐Atmosphere Fluxes From Paired Sites in the Upper Great Lakes Region Using Neural Networks
Author(s) -
Reed David E.,
Poe Jeralyn,
Abraha Michael,
Dahlin Kyla M.,
Chen Jiquan
Publication year - 2021
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
eISSN - 2169-8961
pISSN - 2169-8953
DOI - 10.1029/2021jg006363
Subject(s) - eddy covariance , environmental science , land cover , ecosystem , atmosphere (unit) , atmospheric sciences , flux (metallurgy) , tower , ecosystem respiration , carbon flux , primary production , growing season , land use , meteorology , geography , ecology , geology , materials science , archaeology , metallurgy , biology
The eddy covariance (EC) method is one of the most widely used approaches to quantify surface‐atmosphere fluxes. However, scaling up from a single EC tower to the landscape remains an open challenge. To address this, we used 63 site years of data to examine simulated annual and growing season sums of carbon fluxes from three paired land‐cover type sites of corn, restored‐prairie, and switchgrass ecosystems. This was also done across the landscape by modeling fluxes using different land‐cover type input data. An artificial neural network (ANN) approach was used to model net ecosystem exchange (NEE), ecosystem respiration ( R eco ), and gross primary production (GPP) at one paired site using environmental observations from the second site only. With a mean spatial separation of 11 km between paired sites, we were able to model annual sums of NEE, R eco , and GPP with uncertainties of 20%, 22%, and 8%, respectively, relative to observation sums. When considering the growing season only, model uncertainties were 17%, 22%, and 9%, respectively for the three flux terms. We also show that ANN models can estimate sums of R eco and GPP fluxes without needing the constraint of similar land‐cover‐type, with annual uncertainties of 12% and 10%. These results provide new insights to scaling up observations from one EC site beyond the footprint of the EC tower to multiple land‐cover types across the landscape.