scholarly journals ORCHIDEE-CROP (v0), a new process based Agro-Land Surface Model: model description and evaluation over Europe

2015 ◽  
Vol 8 (6) ◽  
pp. 4653-4696 ◽  
Author(s):  
X. Wu ◽  
N. Vuichard ◽  
P. Ciais ◽  
N. Viovy ◽  
N. de Noblet-Ducoudré ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Latent Heat ◽  
Aboveground Biomass ◽  
Land Surface ◽  
Land Surface Model ◽  
Heat Fluxes ◽  
Surface Model ◽  
Sensible Heat ◽  
Energy Fluxes ◽  
Crop Phenology

Abstract. The responses of crop functioning to changing climate and atmospheric CO2 concentration ([CO2]) could have large effects on food production, and impact carbon, water and energy fluxes, causing feedbacks to climate. To simulate the responses of temperate crops to changing climate and [CO2], accounting for the specific phenology of crops mediated by management practice, we present here the development of a process-oriented terrestrial biogeochemical model named ORCHIDEE-CROP (v0), which integrates a generic crop phenology and harvest module and a very simple parameterization of nitrogen fertilization, into the land surface model (LSM) ORCHIDEEv196, in order to simulate biophysical and biochemical interactions in croplands, as well as plant productivity and harvested yield. The model is applicable for a range of temperate crops, but it is tested here for maize and winter wheat, with the phenological parameterizations of two European varieties originating from the STICS agronomical model. We evaluate the ORCHIDEE-CROP (v0) model against eddy covariance and biometric measurements at 7 winter wheat and maize sites in Europe. The specific ecosystem variables used in the evaluation are CO2 fluxes (NEE), latent heat and sensible heat fluxes. Additional measurements of leaf area index (LAI), aboveground biomass and yield are used as well. Evaluation results reveal that ORCHIDEE-CROP (v0) reproduces the observed timing of crop development stages and the amplitude of pertaining LAI changes in contrast to ORCHIDEEv196 in which by default crops have the same phenology than grass. A near-halving of the root mean square error of LAI from 2.38 ± 0.77 to 1.08 ± 0.34 m2 m−2 is obtained between ORCHIDEEv196 and ORCHIDEE-CROP (v0) across the 7 study sites. Improved crop phenology and carbon allocation lead to a general good match between modelled and observed aboveground biomass (with a normalized root mean squared error (NRMSE) of 11.0–54.2 %), crop yield, as well as of the daily carbon and energy fluxes with NRMSE of ~9.0–20.1 and ~9.4–22.3 % for NEE, and sensible and latent heat fluxes, respectively. The model data mistfit for energy fluxes are within uncertainties of the measurements, which themselves show an incomplete energy balance closure within the range 80.6–86.3 %. The remaining discrepancies between modelled and observed LAI and other variables at specific sites are partly attributable to unrealistic representation of management events. In addition, ORCHIDEE-CROP (v0) is shown to have the ability to capture the spatial gradients of carbon and energy-related variables, such as gross primary productivity, NEE, sensible heat fluxes and latent heat fluxes, across the sites in Europe, an important requirement for future spatially explicit simulations. Further improvement of the model with an explicit parameterization of nutrition dynamics and of management, is expected to improve its predictive ability to simulate croplands in an Earth System Model.

scholarly journals ORCHIDEE-CROP (v0), a new process-based agro-land surface model: model description and evaluation over Europe

2016 ◽  
Vol 9 (2) ◽  
pp. 857-873 ◽  
Author(s):  
X. Wu ◽  
N. Vuichard ◽  
P. Ciais ◽  
N. Viovy ◽  
N. de Noblet-Ducoudré ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Latent Heat ◽  
Crop Yield ◽  
Land Surface ◽  
Land Surface Model ◽  
Heat Fluxes ◽  
Surface Model ◽  
Good Match ◽  
Energy Fluxes ◽  
Crop Phenology

Abstract. The response of crops to changing climate and atmospheric CO2 concentration ([CO2]) could have large effects on food production, and impact carbon, water, and energy fluxes, causing feedbacks to the climate. To simulate the response of temperate crops to changing climate and [CO2], which accounts for the specific phenology of crops mediated by management practice, we describe here the development of a process-oriented terrestrial biogeochemical model named ORCHIDEE-CROP (v0), which integrates a generic crop phenology and harvest module, and a very simple parameterization of nitrogen fertilization, into the land surface model (LSM) ORCHIDEEv196, in order to simulate biophysical and biochemical interactions in croplands, as well as plant productivity and harvested yield. The model is applicable for a range of temperate crops, but is tested here using maize and winter wheat, with the phenological parameterizations of two European varieties originating from the STICS agronomical model. We evaluate the ORCHIDEE-CROP (v0) model against eddy covariance and biometric measurements at seven winter wheat and maize sites in Europe. The specific ecosystem variables used in the evaluation are CO2 fluxes (net ecosystem exchange, NEE), latent heat, and sensible heat fluxes. Additional measurements of leaf area index (LAI) and aboveground biomass and yield are used as well. Evaluation results revealed that ORCHIDEE-CROP (v0) reproduced the observed timing of crop development stages and the amplitude of the LAI changes. This is in contrast to ORCHIDEEv196 where, by default, crops have the same phenology as grass. A halving of the root mean square error for LAI from 2.38 ± 0.77 to 1.08 ± 0.34 m2 m−2 was obtained when ORCHIDEEv196 and ORCHIDEE-CROP (v0) were compared across the seven study sites. Improved crop phenology and carbon allocation led to a good match between modeled and observed aboveground biomass (with a normalized root mean squared error (NRMSE) of 11.0–54.2 %), crop yield, daily carbon and energy fluxes (with a NRMSE of  ∼  9.0–20.1 and  ∼  9.4–22.3 % for NEE), and sensible and latent heat fluxes. The simulated yields for winter wheat and maize from ORCHIDEE-CROP (v0) showed a good match with the simulated results from STICS for three sites with available crop yield observations, where the average NRMSE was  ∼  8.8 %. The model data misfit for energy fluxes were within the uncertainties of the measurements, which themselves showed an incomplete energy balance closure within the range 80.6–86.3 %. The remaining discrepancies between the modeled and observed LAI and other variables at specific sites were partly attributable to unrealistic representations of management events by the model. ORCHIDEE-CROP (v0) has the ability to capture the spatial gradients of carbon and energy-related variables, such as gross primary productivity, NEE, and sensible and latent heat fluxes across the sites in Europe, which is an important requirement for future spatially explicit simulations. Further improvement of the model, with an explicit parameterization of nutritional dynamics and management, is expected to improve its predictive ability to simulate croplands in an Earth system model.

scholarly journals Consistency between hydrological model, large aperture scintillometer and remote sensing based evapotranspiration estimates for a heterogeneous catchment

2012 ◽  
Vol 16 (7) ◽  
pp. 2095-2107 ◽  
Author(s):  
B. Samain ◽  
G. W. H. Simons ◽  
M. P. Voogt ◽  
W. Defloor ◽  
N.-J. Bink ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Latent Heat ◽  
Land Surface ◽  
Land Surface Model ◽  
Heat Fluxes ◽  
Surface Model ◽  
Sensible Heat ◽  
Catchment Scale ◽  
Large Aperture

Abstract. The catchment averaged actual evapotranspiration rate is a hydrologic model variable that is difficult to quantify. Evapotranspiration rates – up till present – cannot be continuously observed at the catchment scale. The objective of this paper is to estimate the evapotranspiration rates (or its energy equivalent, the latent heat fluxes LE) for a heterogeneous catchment of 102.3 km2 in Belgium using three fundamentally different algorithms. One possible manner to observe this variable could be the continuous measurement of sensible heat fluxes (H) across large distances (in the order of kilometers) using a large aperture scintillometer (LAS), and converting these observations into evapotranspiration rates. Latent heat fluxes are obtained through the energy balance equation using a series of sensible heat fluxes measured with a LAS over a distance of 9.5 km in the catchment, and point measurements of net radiation (Rn) and ground heat flux (G) upscaled to catchment average through the use of TOPLATS, a physically based land surface model. The resulting LE-values are then compared to results from the remote sensing based surface energy balance algorithm ETLook and the land surface model. Firstly, the performance of ETLook for the energy balance terms has been assessed at the point scale and at the catchment scale. Secondly, consistency between daily evapotranspiration rates from ETLook, TOPLATS and LAS is shown.

scholarly journals Consistency between hydrological model, large aperture scintillometer and remote sensing based evapotranspiration estimates for a heterogeneous catchment

2011 ◽  
Vol 8 (6) ◽  
pp. 10863-10894 ◽  
Author(s):  
B. Samain ◽  
G. W. H. Simons ◽  
M. P. Voogt ◽  
W. Defloor ◽  
N.-J. Bink ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Latent Heat ◽  
Land Surface ◽  
Land Surface Model ◽  
Heat Fluxes ◽  
Surface Model ◽  
Sensible Heat ◽  
Catchment Scale ◽  
Daily Time

Abstract. The catchment averaged actual evapotranspiration rate is a hydrologic model variable that is difficult to quantify. Evapotranspiration rates can – up till present – not be continuously observed at the catchment scale. The objective of this paper is to estimate the evapotranspiration rates (or its energy equivalent, the latent heat fluxes LE) for a heterogeneous catchment of 102.3 km2 in Belgium using three fundamentally different algorithms. One possible manner to observe this variable could be the continuous measurement of sensible heat fluxes (H) across large distances (in the order of kilometers) using a Large Aperture Scintillometer (LAS), and inverting these observations into evapotranspiration rates. Latent heat fluxes are obtained through the energy balance equation using a series of sensible heat fluxes (H) measured with a LAS over a distance of 9.5 km in the catchment, and point measurements of net radiation (Rn) and ground heat flux (G) upscaled to catchment average through the use of TOPLATS, a physically based land surface model. The resulting LE-values are then validated by comparing them to results from the remote sensing based surface energy balance algorithm ETLook and the land surface model. Firstly, it is demonstrated that ETLook is able to estimate the energy balance terms for daily time steps at the point scale and at the catchment scale. Secondly, consistency between daily evapotranspiration rates from ETLook, TOPLATS and LAS is shown. As such, ETLook provides the opportunity to estimate continuous series of the energy balance terms of a large area for daily time steps and can thus e.g. be used as a validation tool for LAS-measurements, whereas LAS is able to estimate the latent heat fluxes (evapotranspiration rates) for a large and heterogeneous catchment at an hourly time step which can be used for the forcing or validation of hydrologic models.

Sensitivity of Latent Heat Fluxes to Initial Values and Parameters of a Land-Surface Model

2010 ◽  
Vol 9 (4) ◽  
pp. 984-1001 ◽  
Author(s):  
Jörg Schwinger ◽  
Stefan J. Kollet ◽  
Charlotte M. Hoppe ◽  
Hendrik Elbern
Keyword(s):  
Latent Heat ◽  
Land Surface ◽  
Land Surface Model ◽  
Heat Fluxes ◽  
Surface Model ◽  
Initial Values

scholarly journals Irrigated plantations and their effect on energy fluxes in a semi-arid region of Israel – a validated 3-D model simulation

2013 ◽  
Vol 10 (11) ◽  
pp. 13897-13953
Author(s):  
O. Branch ◽  
K. Warrach-Sagi ◽  
V. Wulfmeyer ◽  
S. Cohen
Keyword(s):  
Energy Balance ◽  
Latent Heat ◽  
Land Surface ◽  
Arid Region ◽  
Model Simulation ◽  
Vapour Pressure Deficit ◽  
Heat Fluxes ◽  
Surface Radiation ◽  
Surface Model ◽  
Energy Fluxes

Abstract. A large irrigated biomass plantation was simulated in an arid region of Israel within the WRF-NOAH coupled atmospheric/land surface model in order to assess land surface atmosphere feedbacks. Simulations were carried out for the 2012 summer season (JJA). The irrigated plantations were simulated by prescribing tailored land surface and soil/plant parameters, and by implementing a newly devised, controllable sub-surface irrigation scheme within NOAH. Two model cases studies were considered and compared – Impact and Control. Impact simulates a hypothetical 10 km × 10 km irrigated plantation. Control represents a baseline and uses the existing land surface data, where the predominant land surface type in the area is bare desert soil. Central to the study is model validation against observations collected for the study over the same period. Surface meteorological and soil observations were made at a desert site and from a 400 ha Simmondsia chinensis (Jojoba) plantation. Control was validated with data from the desert, and Impact from the Jojoba. Finally, estimations were made of the energy balance, applying two Penman–Monteith based methods along with observed meteorological data. These estimations were compared with simulated energy fluxes. Control simulates the daytime desert surface 2 m air temperatures (T2) with less than 0.2 °C deviation and the vapour pressure deficit (VPD) to within 0.25 hPa. Desert wind speed (U) is simulated to within 0.5 m s−1 and the net surface radiation (Rn) to 25 W m−2. Soil heat flux (G) is not so accurately simulated by Control (up to 30 W m−2 deviation) and 5 cm soil temperatures (ST5) are simulated to within 1.5 °C. Impact simulates daytime T2 over irrigated vegetation to within 1–1.5 °C, the VPD to 0.5 hPa, Rn to 50 W m−2 and ST5 to within 2 °C. Simulated Impact G deviates up to 40 W m−2, highlighting a need for re-parameterisation or better soil classification, but the overall contribution to the energy balance is small (5–6%). During the night, significant T2 and ST5 cold biases of 2–4 °C are present. Diurnal latent heat values from WRF Impact correspond closely with Penman–Monteith estimation curves, and latent heat magnitudes of 160 W m−2 over the plantation are usual. Simulated plantation sensible heat fluxes are high (450 W m−2) – around 100–110 W m−2 higher than over the surrounding desert. The high relative HFX over the vegetation, driven by high Rn and high surface resistances, indicate that low Bowen ratios should not necessarily be assumed when irrigated plantations are implemented in, and optimized for arid regions. Furthermore, the high plantation T2 magnitudes highlight the importance of considering diurnal dynamics, which drive the evolution of boundary layers, rather than only on daily mean statistics which often indicate an irrigation cooling effect.

scholarly journals Implementation of dynamic crop growth processes into a land surface model: evaluation of energy, water and carbon fluxes under corn and soybean rotation

2013 ◽  
Vol 10 (12) ◽  
pp. 8039-8066 ◽  
Author(s):  
Y. Song ◽  
A. K. Jain ◽  
G. F. McIsaac
Keyword(s):  
Latent Heat ◽  
Land Surface ◽  
Root Distribution ◽  
Carbon Allocation ◽  
Land Surface Model ◽  
Crop Growth ◽  
Surface Model ◽  
Energy Fluxes ◽  
Growth Processes ◽  
Dynamic Crop Growth

Abstract. Worldwide expansion of agriculture is impacting the earth's climate by altering carbon, water, and energy fluxes, but the climate in turn is impacting crop production. To study this two-way interaction and its impact on seasonal dynamics of carbon, water, and energy fluxes, we implemented dynamic crop growth processes into a land surface model, the Integrated Science Assessment Model (ISAM). In particular, we implemented crop-specific phenology schemes and dynamic carbon allocation schemes. These schemes account for light, water, and nutrient stresses while allocating the assimilated carbon to leaf, root, stem, and grain pools. The dynamic vegetation structure simulation better captured the seasonal variability in leaf area index (LAI), canopy height, and root depth. We further implemented dynamic root distribution processes in soil layers, which better simulated the root response of soil water uptake and transpiration. Observational data for LAI, above- and belowground biomass, and carbon, water, and energy fluxes were compiled from two AmeriFlux sites, Mead, NE, and Bondville, IL, USA, to calibrate and evaluate the model performance. For the purposes of calibration and evaluation, we use a corn–soybean (C4–C3) rotation system over the period 2001–2004. The calibrated model was able to capture the diurnal and seasonal patterns of carbon assimilation and water and energy fluxes for the corn–soybean rotation system at these two sites. Specifically, the calculated gross primary production (GPP), net radiation fluxes at the top of the canopy, and latent heat fluxes compared well with observations. The largest bias in model results was in sensible heat flux (SH) for corn and soybean at both sites. The dynamic crop growth simulation better captured the seasonal variability in carbon and energy fluxes relative to the static simulation implemented in the original version of ISAM. Especially, with dynamic carbon allocation and root distribution processes, the model's simulated GPP and latent heat flux (LH) were in much better agreement with observational data than for the static root distribution simulation. Modeled latent heat based on dynamic growth processes increased by 12–27% during the growing season at both sites, leading to an improvement in modeled GPP by 13–61% compared to the estimates based on the original version of the ISAM.

scholarly journals Multimodel Analysis of Energy and Water Fluxes: Intercomparisons between Operational Analyses, a Land Surface Model, and Remote Sensing

2012 ◽  
Vol 13 (1) ◽  
pp. 3-26 ◽  
Author(s):  
Raghuveer K. Vinukollu ◽  
Justin Sheffield ◽  
Eric F Wood ◽  
Michael G. Bosilovich ◽  
David Mocko
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Land Surface Model ◽  
Global Scale ◽  
Heat Fluxes ◽  
Surface Model ◽  
Water Fluxes ◽  
Net Radiation ◽  
Energy Fluxes ◽  
Ensemble Mean

Abstract Using data from seven global model operational analyses (OA), one land surface model, and various remote sensing retrievals, the energy and water fluxes over global land areas are intercompared for 2003/04. Remote sensing estimates of evapotranspiration (ET) are obtained from three process-based models that use input forcings from multisensor satellites. An ensemble mean (linear average) of the seven operational (mean-OA) models is used primarily to intercompare the fluxes with comparisons performed at both global and basin scales. At the global scale, it is found that all components of the energy budget represented by the ensemble mean of the OA models have a significant bias. Net radiation estimates had a positive bias (global mean) of 234 MJ m−2 yr−1 (7.4 W m−2) as compared to the remote sensing estimates, with the latent and sensible heat fluxes biased by 470 MJ m−2 yr−1 (13.3 W m−2) and −367 MJ m−2 yr−1 (11.7 W m−2), respectively. The bias in the latent heat flux is affected by the bias in the net radiation, which is primarily due to the biases in the incoming shortwave and outgoing longwave radiation and to the nudging process of the operational models. The OA models also suffer from improper partitioning of the surface heat fluxes. Comparison of precipitation (P) analyses from the various OA models, gauge analysis, and remote sensing retrievals showed better agreement than the energy fluxes. Basin-scale comparisons were consistent with the global-scale results, with the results for the Amazon in particular showing disparities between OA and remote sensing estimates of energy fluxes. The biases in the fluxes are attributable to a combination of errors in the forcing from the OA atmospheric models and the flux calculation methods in their land surface schemes. The atmospheric forcing errors are mainly attributable to high shortwave radiation likely due to the underestimation of clouds, but also precipitation errors, especially in water-limited regions.

scholarly journals Distinguishing between early- and late-covering crops in the land surface model Noah-MP: impact on simulated surface energy fluxes and temperature

2020 ◽  
Vol 17 (10) ◽  
pp. 2791-2805
Author(s):  
Kristina Bohm ◽  
Joachim Ingwersen ◽  
Josipa Milovac ◽  
Thilo Streck
Keyword(s):  
Land Use ◽  
Heat Flux ◽  
Surface Energy ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Energy Fluxes ◽  
Surface Energy Fluxes

Abstract. Land surface models are essential parts of climate and weather models. The widely used Noah-MP land surface model requires information on the leaf area index (LAI) and green vegetation fraction (GVF) as key inputs of its evapotranspiration scheme. The model aggregates all agricultural areas into a land use class termed “cropland and pasture”. In a previous study we showed that, on a regional scale, the GVF has a bimodal distribution formed by two crop groups differing in phenology and growth dynamics: early-covering crops (ECC; e.g., winter wheat, winter rapeseed, winter barley) and late-covering crops (LCC; e.g., corn, silage maize, sugar beet). That result can be generalized for central Europe. The present study quantifies the effect of splitting the land use class cropland and pasture of Noah-MP into ECC and LCC on surface energy fluxes and temperature. We further studied the influence of increasing the LCC share, which in the study area (the Kraichgau region, southwest Germany) is mainly the result of heavily subsidized biomass production, on energy partitioning at the land surface. We used the GVF dynamics derived from high-resolution (5 m × 5 m) RapidEye satellite data and measured LAI data for the simulations. Our results confirm that the GVF and LAI strongly influence the partitioning of surface energy fluxes, resulting in pronounced differences between simulations of ECC and LCC. Splitting up the generic crop into ECC and LCC had the strongest effect on land surface exchange processes in July–August. During this period, ECC are at the senescence growth stage or already harvested, while LCC have a well-developed ground-covering canopy. The generic crop resulted in humid bias, i.e., an increase in evapotranspiration by +0.5 mm d−1 (latent heat flux is 1.3 MJ m−2 d−1), decrease in sensible heat flux (H) by 1.2 MJ m−2  d−1 and decrease in surface temperature by −1 ∘C. The bias increased as the shares of ECC and LCC became similar. The observed differences will impact the simulations of processes in the planetary boundary layer. Increasing the LCC share from 28 % to 38 % in the Kraichgau region led to a decrease in latent heat flux (LE) and a heating up of the land surface in the early growing season. Over the second part of the season, LE increased and the land surface cooled down by up to 1 ∘C.

scholarly journals Evaluation of the Soil, Vegetation, and Snow (SVS) Land Surface Model for the Simulation of Surface Energy Fluxes and Soil Moisture under Snow-Free Conditions

Atmosphere ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 278 ◽  
Author(s):  
Gonzalo Leonardini ◽  
François Anctil ◽  
Maria Abrahamowicz ◽  
Étienne Gaborit ◽  
Vincent Vionnet ◽  
...  
Keyword(s):  
Heat Flux ◽  
Soil Moisture ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Land Surface Model ◽  
Soil Heat Flux ◽  
Heat Fluxes ◽  
Surface Model ◽  
Point Scale ◽  
Energy Fluxes

The recently developed Soil, Vegetation, and Snow (SVS) land surface model is being progressively implemented at Environment and Climate Change Canada (ECCC) for operational numerical weather and hydrological predictions. The objective of this study is to evaluate the ability of SVS, in offline point-scale mode and under snow-free conditions, to simulate the surface heat fluxes and soil moisture when compared to flux tower observations and simulations from the Canadian Land Surface Scheme (CLASS), used here as a benchmark model. To do this, we performed point-scale simulations of between 4 and 12 years of data records at six selected sites of the FLUXNET network under arid, Mediterranean and tropical climates. At all sites, SVS shows realistic simulations of latent heat flux, sensible heat flux and net radiation. Soil heat flux is reasonably well simulated for the arid sites and one Mediterranean site and poorly simulated for the tropical sites. On the other hand, surface soil moisture was reasonably well simulated at the arid and Mediterranean sites and poorly simulated at the tropical sites. SVS performance was comparable to CLASS not only for energy fluxes and soil moisture, but also for more specific processes such as evapotranspiration and water balance.

scholarly journals ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO<sub>2</sub>, water and energy fluxes on daily to annual scales

2017 ◽  
Author(s):  
Chunjing Qiu ◽  
Dan Zhu ◽  
Philippe Ciais ◽  
Bertrand Guenet ◽  
Gerhard Krinner ◽  
...  
Keyword(s):  
Water Table ◽  
Land Surface ◽  
Peat Soil ◽  
Model Performance ◽  
Land Surface Model ◽  
Grid Cell ◽  
Co2 Exchange ◽  
Heat Fluxes ◽  
Surface Model ◽  
Energy Fluxes

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.

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