Global research alliance on agricultural greenhouse gases - benchmark and ensemble crop and grassland model estimates — Renáta Sándor (2016) | RDL Network
Global research alliance on agricultural greenhouse gases - benchmark and ensemble crop and grassland model estimates
Preprint 2016 en
Authors
RS
Renáta Sándor
FE
Fiona Ehrhardt
BB
Bruno Basso
Abstract
1 min read
The Soil Carbon and Nitrogen Cycling Cross-cutting Group (Soil CN group) of the Global Research Alliance on Agricultural Greenhouse gases (GRA) promotes a coordinated activity across multiple international projects (e.g. CN MIP and Models4Pastures of the FACCE-JPI https://www.faccejpi.com) to benchmark and compare simulation models that simulate GHG emissions from arable crop and grassland systems. Ten long-term experimental sites are studied covering a variety of climatic and geographic conditions worldwide (Australia, Brazil, Canada, France, India, New Zealand, Switzerland, United Kingdom and United States). Twenty-four process-based models of different complexity have contributed to the modelling exercise in different stages, each with access to gradually more detailed data to run and evaluate models of a multi-stage protocol. We present a comparison of model estimates of production (e.g. grain yield, gross primary production, above-ground net primary production, grassland grazing or defoliation) and vegetation (e.g. leaf area index) outputs, as well as GHG emissions (e.g. ecosystem respiration, nitrous oxide, enteric methane) from individual models to the multi-model ensemble. We found substantial discrepancies across different models, indicating considerable uncertainties regarding the simulation of crop and grassland processes. We show that uncertainties are considerably reduced after calibration with detailed production and phenology data. The multi-model approach also allowed for improved performance, according to relative root mean square error and relative bias performance metrics. Calibrated models provide a reliable basis for testing mitigation options at the studied sites.
Fiona Ehrhardt, Jean‐François Soussana, Peter Grace, Sylvie Recous, Gianni Bellocchi, Josef Beautrais, Mark Easter, Mark A. Liebig, Pete Smith, A Celso, Arti Bhatia, Lorenzo Brilli, Richard T. Conant, Paola A. Deligios, Jordi Doltra, Roberta Farina, Nuala Fitton, Brian Grant, Matthew Tom Harrison, Miko U. F. Kirschbaum, Katja Klumpp, Jean-Pierre Léonard, Mark Lieffering, Ricardo I. Pérez‐Martín, S Massad Raia, Elizabeth A. Meier, Lutz Merbold, Andrew D. Moore, Laura Mula, P Newton, Elizabeth Pattey, Bob Rees, S Joanna, I Shcherback, Ward Smith, K. Topp, Lianhai Wu, Weien Zhang
Fiona Ehrhardt, Jean‐François Soussana, Gianni Bellocchi, Peter Grace, Russel McAuliffe, Sylvie Recous, Renáta Sándor, Pete Smith, Val Snow, Massimiliano De Antoni Migliorati, Bruno Basso, Arti Bhatia, Lorenzo Brilli, Jordi Doltra, Christopher D. Dorich, Luca Doro, Nuala Fitton, Sandro José Giacomini, Brian Grant, Matthew Tom Harrison, Stephanie Jones, Miko U. F. Kirschbaum, Katja Klumpp,
Mark Richards, Mark Pogson, Marta Dondini, Edward O. Jones, Astley Hastings, Dagmar N. Henner, Matthew J. Tallis, Eric Casella, Robert Matthews, Paul A. Henshall, Suzanne Milner, Gail Taylor, Niall P. McNamara, Jo Smith, Pete Smith
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