Variability in the sensitivity among model simulations of permafrost and carbon dynamics in the permafrost region between 1960 and 2009

Abstract

A significant portion of the large amount of carbon (C) currently stored in soils of the permafrost region in the Northern Hemisphere has the potential to be emitted as the greenhouse gases CO 2 and CH 4 under a warmer climate. In this study we evaluated the variability in the sensitivity of permafrost and C in recent decades among land surface model simulations over the permafrost region between 1960 and 2009. The 15 model simulations all predict a loss of near-surface permafrost (within 3 m) area over the region, but there are large differences in the magnitude of the simulated rates of loss among the models (0.2 to 58.8 × 10 3 km 2 yr À1 ). Sensitivity simulations indicated that changes in air temperature largely explained changes in permafrost area, although interactions among changes in other environmental variables also played a role. All of the models indicate that both vegetation and soil C storage together have increased by 156 to 954 Tg C yr À1 between 1960 and 2009 over the permafrost region even though model analyses indicate that warming alone would decrease soil C storage. Increases in gross primary production (GPP) largely explain the simulated increases in vegetation and soil C. The sensitivity of GPP to increases in atmospheric CO 2 was the dominant cause of increases in GPP across the models, but comparison of simulated GPP trends across the 1982-2009 period with that of a global GPP data set indicates that all of the models overestimate the trend in GPP. Disturbance also appears to be an important factor affecting C storage, as models that consider disturbance had lower increases in C storage than models that did not consider disturbance. To improve the modeling of C in the permafrost region, there is the need for the MCGUIRE ET AL.MODELING PERMAFROST CARBON DYNAMICS 1015 PUBLICATIONS

A vertical representation of soil carbon in the JULES land surface scheme (vn4.3_permafrost) with a focus on permafrost regions

“…In the permafrost region and between 1960 and 2009 the soil carbon increases by 146-168 Tg C. This falls within the modelled spread found by McGuire et al (2016) who used a range of land surface models and showed the soil carbon increased over the permafrost region by 264 (42-637) Tg C year −1 for the period 1960-2009. The slightly faster increase (by ∼ 10 to 25 Tg C year −1 ) in the vertically discretized models are a consequence of the lower response of soil respiration to temperature change -possibly caused by a lag in the response of the deep soil temperatures to increasing air temperature.…”

“…In the standard model, the respiration only responds to the surface soil temperatures, which will respond much more quickly to changes in air temperature than the deeper soil. It should be noted that the difference in the soil carbon between the standard and vertically discretized model are small compared with differences between different models in, for example, McGuire et al (2016).…”

Deglacial permafrost carbon dynamics in MPI-ESM

“…also considering grid cells with active layers below 3 meters depth), a total of 194 PgC is stored in permafrost soils. Given a multitude of factors which impact simulated SOC storage, current process-based permafrost-carbon models underline that uncertainty in simulated present-day permafrost carbon stocks is very large (McGuire et al, 2016) and suggest that our estimate falls in the lower range of model 20 results.…”

A synthesis dataset of permafrost-affected soil thermal conditions for Alaska, USA

“…Modeling studies indicate that greenhouse gas emissions following thaw would amplify current rates of atmospheric warming (McGuire et al,5 2016). However, large uncertainties exist regarding the timing and magnitude of this permafrost-carbon feedback, in part due to challenges associated with representation of permafrost processes in the climate models and the lack of comprehensive permafrost datasets with which to test such models (Koven et al, 2015;McGuire et al, 2016), There is an immediate need for ready-to-use reliable near-surface permafrost datasets, including ground temperatures, soil moisture, and related climatic factors (such as air temperature and snow depth), which can serve as benchmarks for the modeling community and help to 10 evaluate potential physical, societal, and economic impacts.…”

“…The permafrost extent map by Brown et al (1998) is one of the most frequently and widely used metrics for comparing permafrost model results against real-world data (Koven et al, 2015;McGuire et al, 2016). Another widely used permafrost dataset is the Russian Soil Temperature dataset of daily ground temperature measurements at different depths ranging from 0 to 3.2 m for 51 years (Sherstiukov, 2012).…”