Annually resolved tree-ring records extending back to pre-industrial conditions have the potential to constrain the responses of global land surface models at interannual to centennial timescales. ...Here, we demonstrate a framework to simultaneously constrain the representation of tree growth and physiology in the ORCHIDEE global land surface model using the simulated variability of tree-ring width and carbon (Δ13C) and oxygen (δ18O) stable isotopes in six sites in boreal and temperate Europe. We exploit the resulting tree-ring triplet to derive integrative constraints for leaf physiology and growth from well-known mechanistic relationships among the variables. ORCHIDEE simulates Δ13C (r=0.31–0.80) and δ18O (r=0.36–0.74) better than tree-ring width (r<0.55), with an overall skill similar to that of a tree-ring model (MAIDENiso) and another isotope-enabled global vegetation model (LPX-Bern). The comparison with tree-ring data showed that growth variability is not well represented in ORCHIDEE and that the parameterization of leaf-level physiological responses (stomatal control) to drought stress in the temperate region can be constrained using the interannual variability of tree-ring stable isotopes. The representation of carbon storage and remobilization dynamics emerged as a critical process to improve the realism of simulated growth variability, temporal carryover, and recovery of forest ecosystems after climate extremes. Simulated forest gross primary productivity (GPP) correlates with simulated tree-ring Δ13C and δ18O variability, but the origin of the correlations with tree-ring δ18O is not entirely physiological. The integration of tree-ring data and land surface models as demonstrated here should guide model improvements and contribute towards reducing current uncertainties in forest carbon and water cycling.
The rate at which land surface soils dry following rain events is an important feature of terrestrial models. It determines, for example, the water availability for vegetation, the occurrences of ...droughts, and the surface heat exchanges. As such, surface soil moisture (SSM) “drydowns,” i.e., the SSM temporal dynamics following a significant rainfall event, are of particular interest when evaluating and calibrating land surface models (LSMs). By investigating drydowns, characterized by an exponential decay time scale τ, we aim to improve the representation of SSM in the ORCHIDEE global LSM. We consider τ calculated over 18 International Soil Moisture Network sites found within the footprint of FLUXNET towers, covering different vegetation types and climates. Using the ORCHIDEE LSM, we compare τ from the modeled SSM time series to values computed from in situ SSM measurements. We then assess the potential of using τ observations to constrain some water, carbon, and energy parameters of ORCHIDEE, selected using a sensitivity analysis, through a standard Bayesian optimization procedure. The impact of the SSM optimization is evaluated using FLUXNET evapotranspiration and gross primary production (GPP) data. We find that the relative drydowns of SSM can be well calibrated using observation-based τ estimates, when there is no need to match the absolute observed and modeled SSM values. When evaluated using independent data, τ-calibration parameters were able to improve drydowns for 73% of the sites. Furthermore, the fit of the model to independent fluxes was only minutely changed. We conclude by considering the potential of global satellite products to scale up the experiment to a global-scale optimization.
This study presents the global climate model IPSL‐CM6A‐LR developed at Institut Pierre‐Simon Laplace (IPSL) to study natural climate variability and climate response to natural and anthropogenic ...forcings as part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). This article describes the different model components, their coupling, and the simulated climate in comparison to previous model versions. We focus here on the representation of the physical climate along with the main characteristics of the global carbon cycle. The model's climatology, as assessed from a range of metrics (related in particular to radiation, temperature, precipitation, and wind), is strongly improved in comparison to previous model versions. Although they are reduced, a number of known biases and shortcomings (e.g., double Intertropical Convergence Zone ITCZ, frequency of midlatitude wintertime blockings, and El Niño–Southern Oscillation ENSO dynamics) persist. The equilibrium climate sensitivity and transient climate response have both increased from the previous climate model IPSL‐CM5A‐LR used in CMIP5. A large ensemble of more than 30 members for the historical period (1850–2018) and a smaller ensemble for a range of emissions scenarios (until 2100 and 2300) are also presented and discussed.
Plain Language Summary
Climate models are unique tools to investigate the characteristics and behavior of the climate system. While climate models and their components are developed gradually over the years, the sixth phase of the Coupled Model Intercomparison Project (CMIP6) has been the opportunity for the Institut Pierre‐Simon Laplace to develop, test, and evaluate a new configuration of its climate model called IPSL‐CM6A‐LR. The characteristics and emerging properties of this new model are presented in this study. The model climatology, as assessed from a range of metrics, is strongly improved, although a number of biases common to many models do persist. The equilibrium climate sensitivity and transient climate response have both increased from the previous climate model IPSL‐CM5A‐LR used in CMIP5.
Key Points
The IPSL‐CM6A‐LR model climatology is much improved over the previous version, although some systematic biases and shortcomings persist
A long preindustrial control and a large number of historical and scenario simulations have been performed as part of CMIP6
The effective climate sensitivity of the IPSL model increases from 4.1 to 4.8 K between IPSL‐CM5A‐LR and IPSL‐CM6A‐LR
The purpose of this study was to evaluate 10 process‐based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity (GPP) is compared ...with flux‐tower‐based estimates by Jung et al. Journal of Geophysical Research 116 (2011) G00J07 (JU11). The net primary productivity (NPP) apparent sensitivity to climate variability and atmospheric CO2 trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO2 sensitivity of NPP is compared to the results from four Free‐Air CO2 Enrichment (FACE) experiments. The simulated global net biome productivity (NBP) is compared with the residual land sink (RLS) of the global carbon budget from Friedlingstein et al. Nature Geoscience 3 (2010) 811 (FR10). We found that models produce a higher GPP (133 ± 15 Pg C yr−1) than JU11 (118 ± 6 Pg C yr−1). In response to rising atmospheric CO2 concentration, modeled NPP increases on average by 16% (5–20%) per 100 ppm, a slightly larger apparent sensitivity of NPP to CO2 than that measured at the FACE experiment locations (13% per 100 ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 ± 0.8 Pg C yr−1 is remarkably close to the mean value of RLS (2.1 ± 1.2 Pg C yr−1). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980–2009. Both model‐to‐model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is −3.0 ± 1.5 Pg C yr−1 °C−1, within the uncertainty of what derived from RLS (−3.9 ± 1.1 Pg C yr−1 °C−1). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO2 and climate, the agreement between modeled and observation‐based GPP and NBP can be fortuitous. Carbon–nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO2 concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models.
The Southern Ocean (SO) carbon sink has strengthened substantially since the year 2000, following a decade of a weakening trend. However, the surface ocean pCO2 data underlying this trend reversal ...are sparse, requiring a substantial amount of extrapolation to map the data. Here we use nine different pCO2 mapping products to investigate the SO trends and their sensitivity to the mapping procedure. We find a robust temporal coherence for the entire SO, with eight of the nine products agreeing on the sign of the decadal trends, that is, a weakening CO2 sink trend in the 1990s (on average 0.22 ± 0.24 pg C yr−1 decade−1), and a strengthening sink trend during the 2000s (−0.35 ± 0.23 pg C yr−1 decade−1). Spatially, the multiproduct mean reveals rather uniform trends, but the confidence is limited, given the small number of statistically significant trends from the individual products, particularly during the data‐sparse 1990–1999 period.
Plain Language Summary
The Southern Ocean plays an important role in regulating Earth's climate as it takes up a substantial amount of carbon dioxide from the atmosphere, thereby limiting the effect of global warming. However, this part of the global ocean is also the least well observed and observational data are sparse. Therefore, to study Southern Ocean carbon uptake, data interpolation methods are used to estimate the variability of the carbon uptake from the few existing observations. This poses the question on how reliable these estimates are. The Surface Ocean CO2 Mapping intercomparison project aims to do exactly that, that is, test how reliable current estimates are by comparing results from different methods. Here we compare the results from nine data interpolation methods in the Southern Ocean from 1990 to 2010 and find a broad and encouraging agreement regarding decadal carbon uptake signals, whereas a spatially more refined analysis reveals much less agreement locally, illustrating the need to continue the measurement effort in the Southern Ocean.
Key Points
We compare decadal trends of an ensemble of nine observation‐based Delta pCO2 products in the Southern Ocean
Eight out of nine products reveal a weakening sink trend calculated for the 1990s, and a strengthening sink in the 2000s
The spatial pattern of the multiproduct mean trends is rather uniform in both periods
This paper, developed under the framework of the RECCAP initiative, aims at providing improved estimates of the carbon and GHG (CO2, CH4 and N2O) balance of continental Africa. The various components ...and processes of the African carbon and GHG budget are considered, existing data reviewed, and new data from different methodologies (inventories, ecosystem flux measurements, models, and atmospheric inversions) presented. Uncertainties are quantified and current gaps and weaknesses in knowledge and monitoring systems described in order to guide future requirements. The majority of results agree that Africa is a small sink of carbon on an annual scale, with an average value of −0.61 ± 0.58 Pg C yr−1. Nevertheless, the emissions of CH4 and N2O may turn Africa into a net source of radiative forcing in CO2 equivalent terms. At sub-regional level, there is significant spatial variability in both sources and sinks, due to the diversity of biomes represented and differences in the degree of anthropic impacts. Southern Africa is the main source region; while central Africa, with its evergreen tropical forests, is the main sink. Emissions from land-use change in Africa are significant (around 0.32 ± 0.05 Pg C yr−1), even higher than the fossil fuel emissions: this is a unique feature among all the continents. There could be significant carbon losses from forest land even without deforestation, resulting from the impact of selective logging. Fires play a significant role in the African carbon cycle, with 1.03 ± 0.22 Pg C yr−1 of carbon emissions, and 90% originating in savannas and dry woodlands. A large portion of the wild fire emissions are compensated by CO2 uptake during the growing season, but an uncertain fraction of the emission from wood harvested for domestic use is not. Most of these fluxes have large interannual variability, on the order of ±0.5 Pg C yr−1 in standard deviation, accounting for around 25% of the year-to-year variation in the global carbon budget. Despite the high uncertainty, the estimates provided in this paper show the important role that Africa plays in the global carbon cycle, both in terms of absolute contribution, and as a key source of interannual variability.
Nitrogen is an essential element controlling ecosystem
carbon (C) productivity and its response to climate change and atmospheric
CO2 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. We quantify the model skills at 78 FLUXNET sites by simulating the observed
mean seasonal cycle, daily mean flux variations, and annual mean average GPP
flux for grasslands and forests. Accounting for carbon–nitrogen interactions
does not substantially change the main skills of ORCHIDEE, except for the
site-to-site annual mean GPP variations, for which the version with
carbon–nitrogen interactions is in better agreement with observations.
However, the simulated GPP response to idealised CO2 enrichment
simulations is highly sensitive to whether or not carbon–nitrogen
interactions are accounted for. Doubling of the atmospheric CO2
induces an increase in the GPP, but the site-averaged GPP response to
a CO2 increase projected by the model version with carbon–nitrogen
interactions is half of the increase projected by the version without
carbon–nitrogen interactions. This model's differentiated response has
important consequences for the transpiration rate, which is on average 50 mm yr−1 lower with the version with carbon–nitrogen interactions. Simulated annual GPP for northern, tropical and southern latitudes shows
good agreement with the observation-based MTE-GPP (model tree ensemble gross primary production) product for present-day
conditions. An attribution experiment making use of this new version of
ORCHIDEE for the time period 1860–2016 suggests that global GPP has
increased by 50 %, the main driver being the enrichment of land in
reactive nitrogen (through deposition and fertilisation), followed by the
CO2 increase. Based on our factorial experiment and sensitivity analysis, we conclude that
if carbon–nitrogen interactions are accounted for, the functional responses
of ORCHIDEE r4999 better agree with the current understanding of photosynthesis
than when the carbon–nitrogen interactions are not accounted for and that
carbon–nitrogen interactions are essential in understanding global
terrestrial ecosystem productivity.
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