Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations

Peltola, Olli; Vesala, Timo; Gao, Yao; Räty, Olle; Alekseychik, Pavel; Aurela, Mika; Chojnicki, Bogdan; Desai, Ankur R.; Dolman, Albertus J.; Euskirchen, Eugenie S.; Friborg, Thomas; Göckede, Mathias; Helbig, Manuel; Humphreys, Elyn; Jackson, Robert B.; Jocher, Georg; Joos, Fortunat; Klatt, Janina; Knox, Sara H.; Kowalska, Natalia; ... (2019). Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations. Earth System Science Data, 11(3), pp. 1263-1289. Copernicus Publications 10.5194/essd-11-1263-2019

Preview

Text peltola19essd_essd-11-1263-2019.pdf - Published Version Available under License Creative Commons: Attribution (CC-BY). Download (9MB) | Preview

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. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3–41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4–39.9) or 38 (25.9–49.5) Tg(CH₄) yr⁻¹ . To further evaluate the uncertainties of the upscaled CH₄ flux data products we also compared them against output from two process models (LPX-Bernand WetCHARTs), and methodological issues related to CH₄ flux upscaling are discussed. The monthly upscaled CH₄ flux data products are available at https://doi.org/10.5281/zenodo.2560163 (Peltola et al., 2019).

Interest & Impact

Downloads

130 since deposited on 28 Nov 2019
31 in the past 12 months

Citations

5 Citations in Web of Science ®
6 Citations in Scopus

Search

in Google Scholar™

Services

Actions (login required)

Edit item

Actions (login required)

Edit item