Methane fluxes from arctic & boreal North America: Comparisons between process-based estimates and atmospheric observations
Hanyu Liu, Johns Hopkins University, hliu154@jh.edu (Presenter)
Scot Michael Miller, Johns Hopkins University, smill191@jhu.edu
Felix Vogel, Environment and Climate Change Canada, felix.vogel@canada.ca
Misa Ishizawa, Environment and Climate Change Canada, misa.ishizawa@ec.gc.ca
Zhen Zhang, University of Maryland, zhenzhang@itpcas.ac.cn
Doug Worthy, Environment Canada, doug.worthy@ec.gc.ca
Benjamin Poulter, NASA GSFC, benjamin.poulter@nasa.gov
Leyang Feng, Johns Hopkins University, lfeng13@jh.edu
Anna Gagné-Landmann, Northern Arizona University, ag4637@nau.edu
Ao Chen, Johns Hopkins University, achen152@jh.edu
Ziting Huang, Johns Hopkins University, zhuang51@jh.edu
Dylan Gaeta, Johns Hopkins University, dgaeta@jhu.edu
Joe Melton, Environment and Climate Change Canada, joe.melton@canada.ca
Vineet Yadav, JPL, vineet.yadav@jpl.nasa.gov
Deborah Nicole Huntzinger, Northern Arizona University, deborah.huntzinger@nau.edu
Methane (CH4) flux estimates from high-latitude North American wetlands remain highly uncertain in magnitude, seasonality, and spatial distribution. In this study, we evaluate a decade (2007 – 2017) of CH4 flux estimates by comparing 16 process-based models from a recent inter-comparison project with atmospheric CH4 observations collected from in-situ atmospheric observation towers across Canada and the US. We first compare the current Global Carbon Project (GCP) process-based models with a model inter-comparison from a decade earlier called WETCHIMP. Our analysis reveals that the current process-based models have a much smaller inter-model uncertainty and have an average magnitude that is a factor of two smaller across Canada and Alaska. With that said, the current GCP models likely overestimate wetland fluxes by a factor of two or more across Canada and Alaska based on our analysis using atmospheric CH4 observations. Furthermore, the differences in flux magnitudes among GCP models are more likely driven by spatial-temporal uncertainties in soil carbon or inundation uncertainties than in temperature relationships, such as Q10 factors. In addition, we find that models that agree best with atmospheric observations show peak CH4 fluxes in July and August, while models that exhibit a different seasonal timing or a flat seasonal cycle show seasonal discrepancies compared with atmospheric CH4 data. Furthermore, models that exhibit the best fit to atmospheric observation have a similar spatial distribution; these models concentrate fluxes near the Hudson Bay Lowlands (HBL). Overall, current, state-of-the-art process-based models are much more consistent with atmospheric observations than models from a decade ago, but our analysis shows that there are still numerous opportunities for improvement.
Poster: Poster_Liu_4_55_45.pdf
Associated Project(s):
Poster Location ID: 4
Presentation Type: Poster
Session: Wetlands
Session Date: Wednesday (5/14) 4:30-5:30 PM