Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Geoscientific Model Development 11 (2018): 497-519, doi:10.5194/gmd-11-497-2018.

Description: Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 =  0.76; Nash–Sutcliffe modeling efficiency, MEF  =  0.76) and ecosystem respiration (ER, r2 =  0.78, MEF  =  0.75), with lesser accuracy for latent heat fluxes (LE, r2 =  0.42, MEF  =  0.14) and and net ecosystem CO2 exchange (NEE, r2 =  0.38, MEF  =  0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 〈 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.

Description: This study was supported by the European Research Council Synergy grant ERC-2013-SyG- 610028 IMBALANCE-P.

Description: Northern peatlands store 300–600 Pg C, of which approximately half are underlain by permafrost. Climate warming and, in some regions, soil drying from enhanced evaporation are progressively threatening this large carbon stock. Here, we assess future CO2 and CH4 fluxes from northern peatlands using five land surface models that explicitly include representation of peatland processes. Under Representative Concentration Pathways (RCP) 2.6, northern peatlands are projected to remain a net sink of CO2 and climate neutral for the next three centuries. A shift to a net CO2 source and a substantial increase in CH4 emissions are projected under RCP8.5, which could exacerbate global warming by 0.21°C (range, 0.09–0.49°C) by the year 2300. The true warming impact of peatlands might be higher owing to processes not simulated by the models and direct anthropogenic disturbance. Our study highlights the importance of understanding how future warming might trigger high carbon losses from northern peatlands.

Description: Modeling of global soil organic carbon (SOC) is accompanied by large uncertainties. The heavy computational requirement limits our flexibility in disentangling uncertainty sources especially in high latitudes. We build a structured sensitivity analyzing framework through reorganizing the ORCHIDEE-MICT model with vertically discretized SOC into one matrix equation, which brings flexibility in comprehensive sensitivity assessment. Through Sobol's method enabled by the matrix, we systematically rank 34 relevant parameters according to variance explained by each parameter and find a strong control of carbon input and turnover time on long-term SOC storages. From further analyses for each soil layer and regional assessment, we find that the active layer depth plays a critical role in the vertical distribution of SOC and SOC equilibrium stocks in northern high latitudes (〉50˚N). However, the impact of active layer depth on SOC is highly interactive and nonlinear, varying across soil layers and grid cells. SOC from regions with low active layer depth (e.g., the northernmost part of America, Asia and some Greenland regions) is most vulnerable to active layer depth in terms of relative changes. The model is sensitive to the parameter that controls vertical mixing (cryoturbation rate) but only when the vertical carbon input from vegetation is limited since the effect of vertical mixing is relatively small. And the current model structure may still lack mechanisms that effectively bury non-recalcitrant SOC. We envision a future with more comprehensive model inter-comparisons and assessments with an ensemble of land carbon models adopting the matrix-based sensitivity framework.