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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/gmd-2017-155
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Model description paper
07 Sep 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).
ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water and energy fluxes on daily to annual scales
Chunjing Qiu1, Dan Zhu1, Philippe Ciais1, Bertrand Guenet1, Gerhard Krinner2, Shushi Peng3, Mika Aurela4, Christian Bernhofer5, Christian Brümmer6, Syndonia Bret-Harte7, Housen Chu8, Jiquan Chen9, Ankur R Desai10, Jiří Dušek11, Eugénie S. Euskirchen7, Krzysztof Fortuniak12, Lawrence B. Flanagan13, Thomas Friborg14, Mateusz Grygoruk15, Sébastien Gogo16,17,18, Thomas Grünwald5, Birger U. Hansen14, David Holl19, Elyn Humphreys20, Miriam Hurkuck6, Gerard Kiely21, Janina Klatt22, Lars Kutzbach19, Chloé Largeron1,23, Fatima Laggoun-Défarge16,17,18, Magnus Lund24, Peter M. Lafleur25, Xuefei Li26, Ivan Mammarella26, Lutz Merbold27, Mats B. Nilsson28, Janusz Olejnik29,30, Mikaell Ottosson-Löfvenius28, Walter Oechel31, Frans-Jan W. Parmentier32,33, Matthias Peichl28, Norbert Pirk34, Olli Peltola26, Włodzimierz Pawlak12, Corinna Rebmann35, Daniel Rasse36, Janne Rinne34, Gaius Shaver37, Hans Peter Schmid22, Matteo Sottocornola38, Rainer Steinbrecher22, Torsten Sachs39, Marek Urbaniak29, Donatella Zona30,40, and Klaudia Ziemblinska29 1Laboratoire des Sciences du Climat et de l’Environnement, UMR8212, CEA-CNRS-UVSQ 91191 Gif sur Yvette, France
2CNRS, Université Grenoble Alpes, Institut de Géosciences de l’Environnement (IGE), 38000 Grenoble, France
3Department of Ecology, College of Urban and Environmental Sciences, Peking University, 100871 Beijing, China
4Finnish Meteorological Institute, Climate Change Research, 00101 Helsinki, Finland
5Technische Universität (TU) Dresden, Institute of Hydrology and Meteorology, Chair of Meteorology, 01062 Dresden, Germany
6Thünen Institute of Climate-Smart Agriculture, Bundesallee 50, 38116 Braunschweig, Germany
7Institute of Arctic Biology, University of Alaska Fairbanks, AK 99775 Fairbanks, USA
8Department of Environmental Science, Policy, and Management, University of California, Berkeley, 94720, CA, USA
9Center for Global Change and Earth Observations, Michigan State University, East Lansing, MI 48823, USA
10Department of Atmospheric and Oceanic Sciences, University of Wisconsin–Madison, WI 53706 Madison, USA
11Department of Matters and Energy Fluxes, Global Change Research Institute, Czech Academy of Sciences, 603 00 Brno, Czech Republic
12Department of Meteorology and Climatology, University of Łódź, Narutowicza 88, 90-139 Łódź, Poland
13Department of Biological Sciences, University of Lethbridge, Lethbridge, T1K 3M4 Alberta, Canada
14Department of Geosciences and Natural Resource Management, University of Copenhagen, Oester Voldgade 10, 1350 Copenhagen K, Denmark
15Department of Hydraulic Engineering, Warsaw University of Life Sciences—SGGW, Nowoursynowska 159, 02-776 Warszawa, Poland
16Université d’Orléans, I STO, UMR 7327, 45071 Orléans, France
17CNRS, ISTO, UMR 7327, 45071 Orléans, France
18BRGM, ISTO, UMR 7327, BP 36009, 45060 Orléans, France
19Institute of Soil Science, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Germany
20Department of Geography and Environmental Studies, Carleton University, K1S5B6 Ottawa, Canada
21Department of Civil and Environmental Engineering, University College Cork, Cork, Ireland
22Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK–IFU), 82467 Garmisch-Partenkirchen, Germany
23CNRS and Univ. Grenoble Alpes, Institut de Géosciences de l’Environnement (IGE), 38000 Grenoble, France
24Department of Bioscience, Arctic Research Centre, Aarhus University, 4000 Roskilde, Denmark
25School of the Environment - Geography, Trent University, Peterborough, Ontario, K9J 7B8, Canada
26Department of Physics, University of Helsinki, 00014 Helsinki, Finland
27Mazingira Centre, International Livestock Research Institute (ILRI), 00100 Nairobi, Kenya
28Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, 90183 Umeå, Sweden
29Department of Meteorology, Poznań University of Life Sciences, 60-649 Poznań, Poland
30Department of Matter and Energy Fluxes, Global Change Research Center, AS CR, v.v.i. Belidla 986/4a, 603 00 Brno, Czech Republic
31Department of Biology, San Diego State University, CA 92182 San Diego,USA
32The Arctic University of Norway, Institute for Arctic and Marine Biology, Postboks 6050 Langnes, 9037 Tromsø, Norway
33Department of Geosciences, University of Oslo, Postboks 1022 Blindern, 0315, Oslo, Norway
34Department of Physical Geography and Ecosystem Science, Lund University, 22362 Lund, Sweden
35UFZ-Helmholtz Centre for Environmental Research, 04318 Leipzig, Germany
36Norwegian Institute of Bioeconomy Research, Oslo, Akershus, Norway
37Marine Biological Laboratory, The Ecosystems Center, Woods Hole, 02543 Massachusetts, USA
38Department of Science, Waterford Institute of Technology, Waterford, Ireland
39Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany
40Department of Animal and Plant Sciences, University of Sheffield, Western Bank, Sheffield S10 2TN, UK
Abstract. Peatlands store substantial amount of carbon, are vulnerable to climate change. To predict the fate of carbon stored in peatlands, the complex interactions between water, peat and vegetations need more attention. This study describes a modified version of the ORCHIDEE land surface model for simulating the hydrology, surface energy and CO2 fluxes of peatlands on daily to annual time scales. The model, referred to as ORCHIDEE-PEAT, 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 with 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 is evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site to match the peak of growing season gross primary productivity (GPP), derived from direct EC measurements. Regarding short-term variations from day to day, the model performance was good for the variations in GPP (r2 = 0.76, Nash-Sutcliff modeling efficiency, MEF = 0.76), with lesser accuracy for latent heat fluxes (LE, r2 = 0.42, MEF = 0.14) and Net ecosystem CO2 exchange (NEE, r2 = 0.38, MEF = 0.26). Seasonal variations in GPP, NEE and energy fluxes on monthly scales showed moderate to high r2 values ranging from 0.57 to 0.86. For spatial across-sites gradients of annual mean GPP, NEE and LE, r2 of 0.93, 0.27, and 0.71, respectively, were achieved. The water table variations are not well predicted (r2 < 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, when using the observed water table in the carbon module to define the fraction of oxic and anoxic decomposition instead of the modeled water table, ORCHIDEE-PEAT shows a small improvement in reproducing NEE. Moreover, we found a significant relationship between optimized Vcmax and the latitude (temperature), which can better reflect the spatial gradients of annual NEE than using an average Vcmax value. In a future version of ORCHIDEE-PEAT, the influences of water table on photosynthesis and depth-dependent influences of soil temperature on respiration may be included.

Citation: Qiu, C., Zhu, D., Ciais, P., Guenet, B., Krinner, G., Peng, S., Aurela, M., Bernhofer, C., Brümmer, C., Bret-Harte, S., Chu, H., Chen, J., Desai, A. R., Dušek, J., Euskirchen, E. S., Fortuniak, K., Flanagan, L. B., Friborg, T., Grygoruk, M., Gogo, S., Grünwald, T., Hansen, B. U., Holl, D., Humphreys, E., Hurkuck, M., Kiely, G., Klatt, J., Kutzbach, L., Largeron, C., Laggoun-Défarge, F., Lund, M., Lafleur, P. M., Li, X., Mammarella, I., Merbold, L., Nilsson, M. B., Olejnik, J., Ottosson-Löfvenius, M., Oechel, W., Parmentier, F.-J. W., Peichl, M., Pirk, N., Peltola, O., Pawlak, W., Rebmann, C., Rasse, D., Rinne, J., Shaver, G., Schmid, H. P., Sottocornola, M., Steinbrecher, R., Sachs, T., Urbaniak, M., Zona, D., and Ziemblinska, K.: ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water and energy fluxes on daily to annual scales, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-155, in review, 2017.
Chunjing Qiu et al.
Chunjing Qiu et al.
Chunjing Qiu et al.

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Short summary
Northern peatlands store large amount of soil carbon, are vulnerable to climate change. We implemented peatland hydrological and carbon accumulation processes into the ORCHIDEE land surface model. The model was evaluated against EC measurements from 30 northern peatland sites. The model generally well reproduced the spatial gradient and temporal variations in GPP and NEE at these sites. Water table depth were not well predicted, but have only small influence on simulated NEE.
Northern peatlands store large amount of soil carbon, are vulnerable to climate change. We...
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