Catalyzing carbon cycle science through synergies among research networks
A grand challenge in ecological forecasting is predicting the future trajectory of the terrestrial carbon cycle as simulated in coupled Earth System Models. However, simulations remain highly uncertain despite ever increasing availability of observations. Therefore, finding new ways to use data to evaluate, benchmark and constrain models, and improve forecasts through data assimilation, is critical to making progress in reducing these uncertainties.
This poster presents a summary of findings of a breakout session held at the North American Carbon Program meeting in Washington DC in January 2015 with the primary aim of identifying existing approaches and come up with new ways that observation networks such as AmeriFlux, ICOS and NEON, along with individual PIs can best enable scientific interoperability. This occurs through developing and sharing protocols, procedures, instrumentation, algorithms, metadata and models. Fostering efficiencies in these interactions is essential if the full capabilities of the observation systems are to be leveraged to their maximum potential to produce innovative solutions to major challenges in carbon cycle science.
We identified a number of “key topics” that could benefit from the use of this network interoperability and highlight these here. We also provide examples of how individuals have been working together finding synergies and finding solutions to challenging problems, the lessons learnt and common requirements.
We highlight on-going activities, new directions, and provide recommendations for how these synergistic activities can be best facilitated and generalized.