ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales

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Qiu, Chunjing
Zhu, Dan
Ciais, Philippe
Guenet, Bertrand
Krinner, Gerhard
Peng, Shushi
Aurela, Mika
Bernhofer, Christian
Brümmer, Christian
Bret-Harte, M. Syndonia
Chu, Housen
Chen, Jiquan
Desai, Ankur R.
Dušek, Jiˇrí
Euskirchen, Eugenie
Fortuniak, Krzysztof
Flanagan, Lawrence B.
Friborg, Thomas
Grygoruk, Mateusz
Gogo, Sébastien
Grünwald, Thomas
Hansen, Birger U.
Holl, David
Humphreys, Elyn
Hurkuck, Miriam
Kiely, Gerard
Klatt, Janina
Kutzbach, Lars
Largeron, Chloé
Laggoun-Défarg, Fatima
Lund, Magnus
Lafleur, Peter M.
Li, Xuefei
Mammarella, Ivan
Merbold, Lutz
Nilsson, Mats B.
Olejnik, Janusz
Ottosson-Löfvenius, Mikaell
Oechel, Walter
Parmentier, Frans-Jan W.
Peichl, Matthias
Pirk, Norbert
Peltola, Olli
Pawlak, Włodzimierz
Rasse, Daniel
Rinne, Janne
Shaver, Gaius R.
Schmid, Hans Peter
Sottocornola, Matteo
Steinbrecher, Rainer
Sachs, Torsten
Urbaniak, Marek
Zona, Donatella
Ziemblinska, Klaudia
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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.
© 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.
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Geoscientific Model Development 11 (2018): 497-519
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