Nemitz Eiko, Mammarella Ivan, Ibrom Andreas, Aurela Mika, Burba George G., Dengel Sigrid, Gielen Bert, Grelle Achim, Heinesch Bernard, Herbst Mathias, Hörtnagl Lukas, Klemedtsson Leif, Lindroth Anders, Lohila Annalea, McDermitt Dayle K., Meier Philip, Merbold Lutz, Nelson David, Nicolini Giacomo, Nilsson Mats B., Peltola Olli, Rinne Janne, Zahniser Mark (2018), Standardisation of eddy-covariance flux measurements of methane and nitrous oxide, in
International Agrophysics, 32(4), 517-549.
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Author |
Hoertnagl, Lukas; Merbold, Lutz; Fuchs, Kathrin |
Publication date |
01.04.2016 |
Persistent Identifier (PID) |
http://sites.fluxdata.org/CH-Cha |
Repository |
FLuxnet
|
Abstract |
This is the FLUXNET2015 version of the carbon flux data for the site CH-Cha Chamau. Site Description - intensively managed grassland in the lowlands of switzerland
Dataset from the Chamau Nitrous Oxide Mitigation Experiment 2015-2016
Models4Pastures will test, improve, and then use, simulation models to provide robust assessments of the impact of N2O mitigation options in grassland systems across a large geographic and climatic range. Our models and assessments will take into account the effects of the mitigation option, and its follow-on consequences (e.g. changes in grazing intensity) for other gases to understand the net ecosystem effect, food production and variability of production, and the effects on the ability of the soil to sustain production. This work will be done in the company of current and proposed FACCE-JPI projects and other international activities.We will use model inter-comparisons and development to provide improved tools for climatechange research. In our case we will concentrate on exploring N2O mitigation options for grassland systems and the flow-on impacts of those mitigations on the ability of the soil to sustain production and on the needs for changed inputs or management of the grasslands. The inclusion of New Zealand and European teams provides a wide range of datasets, including a new dataset collected at high temporal resolution and covering different climatic conditions and management practices, and a range of models that have different formulation (assumptions and parameters) and approaches. This is the ideal situation to explore the most effective model features and develop models that are robust across a range of situations that is as wide as possible.The suite of diverse models also forms an ideal ensemble with which to approach the study ofmitigation options. We expect that this combined approach (challenging/improving existing models and ensemble modelling) will result in modelling tools that can be used with confidence by scientists and mitigation assessments that policymakers can be assured are robust. Because many of the scientists in our project are also involved in other modelling inter-comparison initiatives we expect our findings will be rapidly and effectively disseminated to end users who will initially be other scientists wishing to explore potential mitigation options and their consequences.