The Arctic Carbon Monitoring and Forecasting System: a novel forecasting
framework to build new understanding and reduce model uncertainty of the
permafrost carbon-climate feedback.
Abstract
In light of the magnitude and pace of the environmental changes in the
northern permafrost zone (NPZ) and their feedbacks to climate,
contemporary, accurate and quantitative ecological forecasting has never
been so paramount to the development of climate change adaptation and
mitigation strategies. Yet, uncertainties associated with carbon (C)
projections in the NPZ remain the largest to projections of global C
budget and climate. While there are persisting lacks of data documenting
important and emerging soil and vegetation dynamics in the NPZ, the
volume, variety and accessibility of observational data in the NPZ has
grown exponentially over the past decades and significantly improved our
understanding of terrestrial C dynamic. Yet, a lag persists between
large availability of historical, new and iterative data collections and
the capacity of terrestrial biosphere models to fully incorporate this
information, limiting advances in reducing the uncertainty of ecological
forecasting in the NPZ. In this new project, we are developing the
Arctic Carbon Monitoring and Prediction System (ACMPS), a data
assimilation system that will use the information from field
observations from ecological networks, remote sensing data and
ecological modeling to reduce the uncertainty of the terrestrial carbon
balance in the NPZ. The ACMPS will be coupling model development and
testing, data-assimilation techniques and near-term forecasting capacity
to improve the accuracy of historical and future simulations of
ecosystem permafrost and C dynamics across the NPZ. We will present the
structure and workflow of the ACMPS, as well as preliminary assessment
of model sensitivity and uncertainty analysis of soil and vegetation
carbon fluxes, using a terrestrial biosphere model specifically
developed to represent permafrost, vegetation and carbon dynamics in
arctic and boreal ecosystems. Plain-language Summary We are presenting
the Arctic Carbon Monitoring and Prediction System, a data assimilation
system that uses field observation, remote sensing data and ecological
modeling to reduce the uncertainty of the terrestrial carbon balance in
the northern permafrost zone, and to better inform development of
climate change adaptation and mitigation strategies.