According to a recent estimate (Tarnocai et al., 2009), the northern permafrost region contains approximately 1,700 Pg (1 Pg = 1 billion metric tons) of organic carbon, of which about 90% occurs in permafrost deposits. This represents approximately 50% of the estimated global below-ground organic carbon pool and more than twice as much as is contained in the current atmospheric carbon pool (Schuur et al., 2008).
The sheer size of this carbon pool, together with the large amplitude of predicted Arctic climate change (IPCC, 2007), implies that there is a high potential for global-scale feedbacks from Arctic climate change if these carbon reservoirs are destabilized. Moreover, the significant covariation of atmospheric CH4 and CO2 concentrations with global climate on "orbital" time scales (10,000 to 400,000 years; Petit et al., 1999) also hints at potential feedbacks between these high-latitude soil carbon reservoirs and global climate change, although other reservoirs such as those in the deep oceans will certainly have also played an important role.
A destabilization of 10% of these carbon pools and subsequent emission as CO2 would increase the atmospheric CO2 concentration by 0.1 ppm and, based on the Stern review (Stern et al., 2006), induce additional costs of 350 trillion Euros per year for the European Economy.
These major gaps in our knowledge are due, at least in part, to the fact that the Arctic permafrost regions are remote, subject to harsh climatic conditions, sparsely populated, difficult to access, and economically less relevant than the world's temperate and tropical zones. Data coverage is therefore poor and the attention of climate modellers has traditionally focused on the lower latitudes.
A good illustration of these modeling deficiencies was provided by Friedlingstein et al. (2006) who analysed the output from the WCRP C4MIP (Coupled-Carbon Cycle Climate Model Intercomparison Project) simulations designed to inform the 4th IPCC Assessment Report. The overwhelming majority of these coupled climate-carbon cycle models suggested that the continental high northern latitudes would turn into a carbon sink under the SRES A2 CO2 emission scenario. This result is in striking contradiction to our current understanding of the dynamics of the high-latitude carbon stocks, with the contradiction being certainly due to the incomplete representation of the permafrost carbon reservoir in current-generation carbon-cycle models (e.g., de Boer et al., 2010). With the specific properties of this soil carbon reservoir being ignored, the simulated carbon storage in the northern high latitudes increased as a result of the carbon content in the high latitude vegetation increasing due to climate warming and CO2 fertilisation.
Our current understanding suggests that, while the high-latitudes might indeed represent a transient carbon sink due to the growing above-ground carbon reservoir, the sign of the net flux is likely to reverse within a matter of decades because of the large size of the permafrost carbon reservoir (Oechel et al., 1993). This means that the "road to stabilization" (Friedlingstein, 2008), i.e. the rate of reduction in greenhouse gas emissions required to reduce climate change, may be greater than current observations and model-based evaluations tend to suggest.
The large knowledge gaps, the observed onset and projected acceleration of drastic climate and landscape changes in the Arctic, and the threat of potentially large positive feedbacks to global climate change, have encouraged the doomsday scenarios regarding permafrost feedbacks to global warming that have been popular in the media, and even in some serious scientific journals (e.g. Nisbet and Chappellaz, 2009). Clearly "more science, less hype" (Kerr, 2010) is needed to put these findings into perspective. This immediately leads to the following key questions that underlie this call and that will be addressed by this project:
The concept of PAGE21 is to directly address these questions through a close interaction between monitoring activities, process studies and modeling on the pertinent temporal and spatial scales.