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Volume 9, issue 1 | Copyright
Earth Syst. Dynam., 9, 153-165, 2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 21 Feb 2018

Research article | 21 Feb 2018

Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties

Jean-François Exbrayat1, A. Anthony Bloom2, Pete Falloon3, Akihiko Ito4, T. Luke Smallman1, and Mathew Williams1 Jean-François Exbrayat et al.
  • 1School of GeoSciences and National Centre for Earth Observation, University of Edinburgh, Edinburgh, EH9 3FF, UK
  • 2Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
  • 3Met Office Hadley Centre, Fitzroy Road, Exeter, EX1 3PB, UK
  • 4National Institute for Environmental Studies, Tsukuba, Japan

Abstract. Multi-model averaging techniques provide opportunities to extract additional information from large ensembles of simulations. In particular, present-day model skill can be used to evaluate their potential performance in future climate simulations. Multi-model averaging methods have been used extensively in climate and hydrological sciences, but they have not been used to constrain projected plant productivity responses to climate change, which is a major uncertainty in Earth system modelling. Here, we use three global observationally orientated estimates of current net primary productivity (NPP) to perform a reliability ensemble averaging (REA) method using 30 global simulations of the 21st century change in NPP based on the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) business as usual emissions scenario. We find that the three REA methods support an increase in global NPP by the end of the 21st century (2095–2099) compared to 2001–2005, which is 2–3% stronger than the ensemble ISIMIP mean value of 24.2Pg C y−1. Using REA also leads to a 45–68% reduction in the global uncertainty of 21st century NPP projection, which strengthens confidence in the resilience of the CO2 fertilization effect to climate change. This reduction in uncertainty is especially clear for boreal ecosystems although it may be an artefact due to the lack of representation of nutrient limitations on NPP in most models. Conversely, the large uncertainty that remains on the sign of the response of NPP in semi-arid regions points to the need for better observations and model development in these regions.

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Short summary
We use global observations of current terrestrial net primary productivity (NPP) to constrain the uncertainty in large ensemble 21st century projections of NPP under a "business as usual" scenario using a skill-based multi-model averaging technique. Our results show that this procedure helps greatly reduce the uncertainty in global projections of NPP. We also identify regions where uncertainties in models and observations remain too large to confidently conclude a sign of the change of NPP.
We use global observations of current terrestrial net primary productivity (NPP) to constrain...