Exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than ...500 registered sites, and up to 250 of them share data (free fair-use data set). Many modelling groups use the FLUXNET data set for evaluating ecosystem models' performance, but this requires uninterrupted time series for the meteorological variables used as input. Because original in situ data often contain gaps, from very short (few hours) up to relatively long (some months) ones, we develop a new and robust method for filling the gaps in meteorological data measured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-Interim) and a high temporal resolution spanning from 1989 to today. These data are, however, not measured at site level, and for this reason a method to downscale and correct the ERA-Interim data is needed. We apply this method to the level 4 data (L4) from the La Thuile collection, freely available after registration under a fair-use policy. The performance of the developed method varies across sites and is also function of the meteorological variable. On average over all sites, applying the bias correction method to the ERA-Interim data reduced the mismatch with the in situ data by 10 to 36 %, depending on the meteorological variable considered. In comparison to the internal variability of the in situ data, the root mean square error (RMSE) between the in situ data and the unbiased ERA-I (ERA-Interim) data remains relatively large (on average over all sites, from 27 to 76 % of the standard deviation of in situ data, depending on the meteorological variable considered). The performance of the method remains poor for the wind speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations. The ERA-Interim reanalysis data de-biased at FLUXNET sites can be downloaded from the PANGAEA data centre (http://doi.pangaea.de/10.1594/PANGAEA.838234).
The Plumbing of Land Surface Models Best, M. J.; Abramowitz, G.; Johnson, H. R. ...
Journal of hydrometeorology,
06/2015, Letnik:
16, Številka:
3
Journal Article
Recenzirano
Odprti dostop
The Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) was designed to be a land surface model (LSM) benchmarking intercomparison. ...Unlike the traditional methods of LSM evaluation or comparison, benchmarking uses a fundamentally different approach in that it sets expectations of performance in a range of metrics a priori—before model simulations are performed. This can lead to very different conclusions about LSM performance. For this study, both simple physically basedmodels and empirical relationships were used as the benchmarks. Simulations were performed with 13 LSMs using atmospheric forcing for 20 sites, and then model performance relative to these benchmarks was examined. Results show that even for commonly used statistical metrics, the LSMs’ performance varies considerably when compared to the different benchmarks. All models outperform the simple physically based benchmarks, but for sensible heat flux the LSMs are themselves outperformed by an out-of-sample linear regression against downward shortwave radiation. While moisture information is clearly central to latent heat flux prediction, the LSMs are still outperformed by a three-variable nonlinear regression that uses instantaneous atmospheric humidity and temperature in addition to downward shortwave radiation. These results highlight the limitations of the prevailing paradigm of LSM evaluation that simply compares an LSM to observations and to other LSMs without a mechanism to objectively quantify the expectations of performance. The authors conclude that their results challenge the conceptual view of energy partitioning at the land surface.
The Cretaceous evolution of angiosperm leaves towards higher vein densities enables unprecedented leaf stomatal conductance. Still, simulating and quantifying the impact of such change on plant ...productivity and transpiration in the specific environmental conditions of the Cretaceous remain challenging. Here, we address this issue by combining a paleo proxy-based model with a full atmosphere–vegetation model that couples stomatal conductance to carbon assimilation. Based on the fossil record, we build and evaluate three consistent proto-angiosperm vegetation parameterizations under two end-member scenarios of pCO2 (280 and 1120 ppm) for the mid-Cretaceous: a reduction of leaf hydraulic or photosynthetic capacity and a combination of both, supported by a likely coevolution of stomatal conductance and photosynthetic biochemistry. Our results suggest that decreasing leaf hydraulic and/or photosynthetic capacities always generates a reduction of transpiration that is predominantly the result of plant productivity variations modulated by light, water availability in the soil, atmospheric evaporative demand and pCO2. The high pCO2 acts as a fertilizer on plant productivity that strengthens plant transpiration and water-use efficiency. However, we show that proto-angiosperm physiology does not allow vegetation to grow under low pCO2 because of a positive feedback between leaf stomatal conductance and leaf area index. Our modeling approach stresses the need to better represent paleovegetation physiological traits. It also confirms the hypothesis of a likely evolution of angiosperms from a state of low leaf hydraulic and photosynthetic capacities at high pCO2 to a state of high leaf hydraulic and photosynthetic capacities linked to leaves with more and more veins together with a more efficient biochemistry at low pCO2.
We present the global general circulation model IPSL-CM5 developed to study the long-term response of the climate system to natural and anthropogenic forcings as part of the 5th Phase of the Coupled ...Model Intercomparison Project (CMIP5). This model includes an interactive carbon cycle, a representation of tropospheric and stratospheric chemistry, and a comprehensive representation of aerosols. As it represents the principal dynamical, physical, and bio-geochemical processes relevant to the climate system, it may be referred to as an Earth System Model. However, the IPSL-CM5 model may be used in a multitude of configurations associated with different boundary conditions and with a range of complexities in terms of processes and interactions. This paper presents an overview of the different model components and explains how they were coupled and used to simulate historical climate changes over the past 150 years and different scenarios of future climate change. A single version of the IPSL-CM5 model (IPSL-CM5A-LR) was used to provide climate projections associated with different socio-economic scenarios, including the different Representative Concentration Pathways considered by CMIP5 and several scenarios from the Special Report on Emission Scenarios considered by CMIP3. Results suggest that the magnitude of global warming projections primarily depends on the socio-economic scenario considered, that there is potential for an aggressive mitigation policy to limit global warming to about two degrees, and that the behavior of some components of the climate system such as the Arctic sea ice and the Atlantic Meridional Overturning Circulation may change drastically by the end of the twenty-first century in the case of a no climate policy scenario. Although the magnitude of regional temperature and precipitation changes depends fairly linearly on the magnitude of the projected global warming (and thus on the scenario considered), the geographical pattern of these changes is strikingly similar for the different scenarios. The representation of atmospheric physical processes in the model is shown to strongly influence the simulated climate variability and both the magnitude and pattern of the projected climate changes.
Over the last few years, solar‐induced chlorophyll fluorescence (SIF) observations from space have emerged as a promising resource for evaluating the spatio‐temporal distribution of gross primary ...productivity (GPP) simulated by global terrestrial biosphere models. SIF can be used to improve GPP simulations by optimizing critical model parameters through statistical Bayesian data assimilation techniques. A prerequisite is the availability of a functional link between GPP and SIF in terrestrial biosphere models. Here we present the development of a mechanistic SIF observation operator in the ORCHIDEE (Organizing Carbon and Hydrology In Dynamic Ecosystems) terrestrial biosphere model. It simulates the regulation of photosystem II fluorescence quantum yield at the leaf level thanks to a novel parameterization of non‐photochemical quenching as a function of temperature, photosynthetically active radiation, and normalized quantum yield of photochemistry. It emulates the radiative transfer of chlorophyll fluorescence to the top of the canopy using a parametric simplification of the SCOPE (Soil Canopy Observation Photosynthesis Energy) model. We assimilate two years of monthly OCO‐2 (Orbiting Carbon Observatory‐2) SIF product at 0.5° (2015–2016) to optimize ORCHIDEE photosynthesis and phenological parameters over an ensemble of grid points for all plant functional types. The impact on the simulated GPP is considerable with a large decrease of the global scale budget by 28 GtC/year over the period 1990–2009. The optimized GPP budget (134/136 GtC/year over 1990–2009/2001–2009) remarkably agrees with independent GPP estimates, FLUXSAT (137 GtC/year over 2001–2009) in particular and FLUXCOM (121 GtC/year over 1990–2009). Our results also suggest a biome dependency of the SIF‐GPP relationship that needs to be improved for some plant functional types.
Key Points
We developed a process‐based SIF observation operator in a terrestrial biosphere model
We assimilated monthly OCO‐2 SIF products to optimize model photosynthesis and phenology‐related parameters
The optimized GPP is considerably reduced with spatio‐temporal patterns in closer agreement with independent products
Nitrogen is an essential element controlling ecosystem carbon (C) productivity and its response to climate change and atmospheric CO.sub.2 increase. This study presents the evaluation - focussing on ...gross primary production (GPP) - of a new version of the ORCHIDEE model that gathers the representation of the nitrogen cycle and of its interactions with the carbon cycle from the OCN model and the most recent developments from the ORCHIDEE trunk version.
Carbon cycling and C sequestration opportunities in temperate grasslands are addressed. A simple two-parameter exponential model is fitted to data from the literature to assess soil organic C fluxes ...stemming from land use change and from grassland management. C fluxes are also considered within the context of farming systems, including manure applications and crop-grass rotations. Simulations show that the greenhouse gas balance of pastures may differ by several tons of carbon dioxide-C equivalent/ha from the C balance. Restoration of grasslands and extensification of intensive herbivore breeding systems are likely to provide C sequestration opportunities.
Since 70 % of global forests are managed and forests impact the global carbon cycle and the energy exchange with the overlying atmosphere, forest management has the potential to mitigate climate ...change. Yet, none of the land-surface models used in Earth system models, and therefore none of today's predictions of future climate, accounts for the interactions between climate and forest management. We addressed this gap in modelling capability by developing and parametrising a version of the ORCHIDEE land-surface model to simulate the biogeochemical and biophysical effects of forest management. The most significant changes between the new branch called ORCHIDEE-CAN (SVN r2290) and the trunk version of ORCHIDEE (SVN r2243) are the allometric-based allocation of carbon to leaf, root, wood, fruit and reserve pools; the transmittance, absorbance and reflectance of radiation within the canopy; and the vertical discretisation of the energy budget calculations. In addition, conceptual changes were introduced towards a better process representation for the interaction of radiation with snow, the hydraulic architecture of plants, the representation of forest management and a numerical solution for the photosynthesis formalism of Farquhar, von Caemmerer and Berry. For consistency reasons, these changes were extensively linked throughout the code. Parametrisation was revisited after introducing 12 new parameter sets that represent specific tree species or genera rather than a group of often distantly related or even unrelated species, as is the case in widely used plant functional types. Performance of the new model was compared against the trunk and validated against independent spatially explicit data for basal area, tree height, canopy structure, gross primary production (GPP), albedo and evapotranspiration over Europe. For all tested variables, ORCHIDEE-CAN outperformed the trunk regarding its ability to reproduce large-scale spatial patterns as well as their inter-annual variability over Europe. Depending on the data stream, ORCHIDEE-CAN had a 67 to 92 % chance to reproduce the spatial and temporal variability of the validation data.
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.
We estimated the long-term carbon balance net biome production (NBP) of European (EU-25) croplands and its component fluxes, over the last two decades. Net primary production (NPP) estimates, from ...different data sources ranged between 490 and 846 gC m⁻² yr⁻¹, and mostly reflect uncertainties in allocation, and in cropland area when using yield statistics. Inventories of soil C change over arable lands may be the most reliable source of information on NBP, but inventories lack full and harmonized coverage of EU-25. From a compilation of inventories we infer a mean loss of soil C amounting to 17 g m⁻² yr⁻¹. In addition, three process-based models, driven by historical climate and evolving agricultural technology, estimate a small sink of 15 g C m⁻² yr⁻¹ or a small source of 7.6 g C m⁻² yr⁻¹. Neither the soil C inventory data, nor the process model results support the previous European-scale NBP estimate by Janssens and colleagues of a large soil C loss of 90 ± 50 gC m⁻² yr⁻¹. Discrepancy between measured and modeled NBP is caused by erosion which is not inventoried, and the burning of harvest residues which is not modeled. When correcting the inventory NBP for the erosion flux, and the modeled NBP for agricultural fire losses, the discrepancy is reduced, and cropland NBP ranges between -8.3 ± 13 and -13 ± 33 g C m⁻² yr⁻¹ from the mean of the models and inventories, respectively. The mean nitrous oxide (N₂O) flux estimates ranges between 32 and 37 g C Eq m⁻² yr⁻¹, which nearly doubles the CO₂ losses. European croplands act as small CH₄ sink of 3.3 g C Eq m⁻² yr⁻¹. Considering ecosystem CO₂, N₂O and CH₄ fluxes provides for the net greenhouse gas balance a net source of 42-47 g C Eq m⁻² yr⁻¹. Intensifying agriculture in Eastern Europe to the same level Western Europe amounts is expected to result in a near doubling of the N₂O emissions in Eastern Europe. N₂O emissions will then become the main source of concern for the impact of European agriculture on climate.
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