ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO$_2$ water, and energy fluxes on daily to annual scales

International audiencePeatlands 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 CO$_2$ 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 car-boxylation (V$_{cmax}$) being optimized at each site. Regarding short-term day-today variations, the model performance was good for gross primary production (GPP) ($r^2$ = 0.76; Nash– Sutcliffe modeling efficiency, MEF = 0.76) and ecosystem respiration (ER, $r^2$ = 0.78, MEF = 0.75), with lesser accuracy for latent heat fluxes (LE, $r^2$ = 0.42, MEF = 0.14) and and net ecosystem CO$_2$ exchange (NEE, $r^2$ = 0.38, MEF = 0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high $r^2$ values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, $r^2$ values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted ($r^2$ < 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 V$_{cmax}$ and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average V$_{cmax}$ value