Title: Monthly Gridded Data Product of Northern Wetland Methane Emissions Based on Upscaling Eddy Covariance Observations
Citation: Peltola, O., Vesala, T., Gao, Y., Räty, O., Alekseychik, P., Aurela, M., Chojnicki, B., Desai, A., Dolman, H., Euskirchen, E., Friborg, T., Göckede, M., Helbig, M., Humphreys, E., Jackson, R., Jocher, G., Joos, F., Klatt, J., Knox, S., … Aalto, T. (2019). Dataset for "Monthly Gridded Data Product of Northern Wetland Methane Emissions Based on Upscaling Eddy Covariance Observations" [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.3247295
Study Site: Global
Purpose: Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process (“bottom-up”) or inversion (“top-down”) models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45◦ N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash–Sutcliffe model efficiency= 0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus,
three wetland distribution maps are utilized in the upscaling.
Abstract: This dataset provides wetland methane (CH4) emissions, their uncertainties and underlying CH4 flux densities north from 45 N using three different wetland maps. The data products are derived using data from several eddy covariance CH4 flux sites, random forest machine learning algorithms and three prescribed wetland maps. The data are at 0.5 by 0.5 deg or 1 by 1 deg resolution, depending on the wetland map used. The dataset covers years 2013 and 2014. CH4 flux densities are provided only for grid cells with > 5 % wetland coverage.
Supplemental Information Summary:
Responsible Parties:
Principal Investigator: Olli Peltola
Collaborator: Timo Vesala
Collaborator: Yao Gao
Collaborator: Olle Räty
Collaborator: Pavel Alekseychik
Collaborator: Mika Aurela
Collaborator: Bogdan Chojnicki
Collaborator: Ankur Desai
Collaborator: Han Dolman
Collaborator: Eugenie Euskirchen
Collaborator: Thomas Friborg
Collaborator: Mathias Göckede
Collaborator: Maniel Helbig
Collaborator: Elyn Humphreys
Collaborator: Rob Jackson
Collaborator: Georg Jocher
Collaborator: Fortunat Joos
Collaborator: Janina Klatt
Collaborator: Sara Knox
Collaborator: Natalia Kowalska
Collaborator: Lars Kutzbach
Collaborator: Sebastian Lienert
Collaborator: Annalea Lohila
Collaborator: Ivan Mammarella
Collaborator: Daniel Nadeau
Collaborator: Mats Nilsson
Collaborator: Walter Oechel
Collaborator: Matthias Peichl
Collaborator: Thomas Pypker
Collaborator: William Quinton
Collaborator: Janne Rinne
Collaborator: Torsten Sachs
Collaborator: Mateusz Samson
Collaborator: Hans Peter Schmid
Collaborator: Oliver Sonnentag
Collaborator: Christian Wille
Collaborator: Donatella Zona
Collaborator: Tuula Aalto
Research:
Further Info: Peltola, O., Vesala, T., Gao, Y., Räty, O., Alekseychik, P., Aurela, M., Chojnicki, B., Desai, A. R., Dolman, A. J., Euskirchen, E. S., Friborg, T., Göckede, M., Helbig, M., Humphreys, E., Jackson, R. B., Jocher, G., Joos, F., Klatt, J., Knox, S. H., Kowalska, N., Kutzbach, L., Lienert, S., Lohila, A., Mammarella, I., Nadeau, D. F., Nilsson, M. B., Oechel, W. C., Peichl, M., Pypker, T., Quinton, W., Rinne, J., Sachs, T., Samson, M., Schmid, H. P., Sonnentag, O., Wille, C., Zona, D., and Aalto, T.: Monthly Gridded Data Product of Northern Wetland Methane Emissions Based on Upscaling Eddy Covariance Observations, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2019-28, in review, 2019.
Status: Complete
Keywords:
methane,
mapping,
machine learning,
Geographical coordinates: North: 83.15, South: 41.909 East: -52.619 West: -141.010
Bounding Temporal Extent: Start Date: , End
Date:
