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The Paris Agreement of 2015 established an enhanced transparency framework, in which parties of the agreement compile and provide their national greenhouse gas (GHG) inventories based on annual statistics of [...]

The northern land biosphere is believed to be the main global sink of CO2, but the contribution of Europe is uncertain. While bottom‐up estimates and inverse atmospheric transport studies based on atmospheric CO2 observed in situ or from space by OCO‐2 point to a moderate rate of uptake, some other inversions based on remotely sensed atmospheric CO2 from GOSAT/SCIAMACHY and biomass estimates from passive microwave satellite data point to a large sink of around 1 Gt C/yr. We present results from combining both approaches in a data assimilation framework, inverting a biosphere model against in situ atmospheric CO2 and passive microwave measurements. When assimilating all observations, we estimate a European carbon sink of 0.303 ± 0.083 Gt C/yr for 2010–2015. The result agrees with other bottom‐up studies and atmospheric inversions using in situ CO2 or OCO‐2 observations pointing to potential data problems when using observations from GOSAT or SCIAMACHY to estimate the European CO2 sink. Key Points: European carbon sink estimated to be 0.303 ± 0.083 GtC/yrConsistent assimilation of three observational data products into a terrestrial biosphere modelSMOS soil moisture and vegetation optical depth reduce flux uncertainty by an additional 15–25% compared to assimilating CO2 only [ABSTRACT FROM AUTHOR]

Simulations of carbon fluxes with terrestrial biosphere models still exhibit significant uncertainties, in part due to the uncertainty in model parameter values. With the advent of satellite measurements of solar induced chlorophyll fluorescence (SIF), there exists a novel pathway for constraining simulated carbon fluxes and parameter values. We investigate the utility of SIF in constraining gross primary productivity (GPP). As a first test we assess whether SIF simulations are sensitive to important parameters in a biosphere model. SIF measurements at the wavelength of 755 nm are simulated by the Carbon-Cycle Data Assimilation System (CCDAS) which has been augmented by the fluorescence component of the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model. Idealized sensitivity tests of the SCOPE model stand-alone indicate strong sensitivity of GPP to the carboxylation capacity (Vcmax) and of SIF to the chlorophyll AB content (Cab) and incoming short wave radiation. Low sensitivity is found for SIF to Vcmax, however the relationship is subtle, with increased sensitivity under high radiation conditions and lower Vcmax ranges. CCDAS simulates well the patterns of satellite-measured SIF suggesting the combined model is capable of ingesting the data. CCDAS supports the idealized sensitivity tests of SCOPE, with SIF exhibiting sensitivity to Cab and incoming radiation, both of which are treated as perfectly known in previous CCDAS versions. These results demonstrate the need for careful consideration of Cab and incoming radiation when interpreting SIF and the limitations of utilizing SIF to constrain Vcmax in the present set-up in the CCDAS system. [ABSTRACT FROM AUTHOR]

We analyse global and regional changes in CO2 fluxes using two simple models, an airborne fraction of anthropogenic emissions and a linear relationship with CO2 concentrations. We show that both models are able to fit the non-anthropogenic (hereafter natural) flux over the length of the atmospheric concentration record. Analysis of the linear model (including its uncertainties) suggests no significant decrease in the response of the natural carbon cycle. Recent data points rather to an increase. We apply the same linear diagnostic to fluxes from atmospheric inversions. Flux responses show clear regional and seasonal patterns driven by terrestrial uptake in the northern summer. Ocean fluxes show little or no linear response. Terrestrial models show clear responses, agreeing globally with the inversion responses, however the spatial structure is quite different, with dominant responses in the tropics rather than the northern extratropics. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystem models are employed to calculate the sources and sinks of carbon dioxide between land and atmosphere. These models may be heavily parameterised. Where reliable estimates are unavailable for a parameter, it remains highly uncertain; uncertainty of parameters can substantially contribute to overall model output uncertainty. This paper builds on the work of the terrestrial Carbon Cycle Data Assimilation System (CCDAS), which, here, assimilates atmospheric CO2 concentrations to optimise 19 parameters of the underlying terrestrial ecosystem model (Biosphere Energy Transfer and Hydrology scheme, BETHY). Previous experiments have shown that the identified minimum may contain non-physical parameter values. One way to combat this problem is to use constrained optimisation and so avoid the optimiser searching non-physical regions. Another technique is to use penalty terms in the cost function, which are added when the optimisation searches outside of a specified region. The use of parameter transformations is a further method of avoiding this problem, where the optimisation is carried out in a transformed parameter space, thus ensuring that the optimal parameters at the minimum are in the physical domain. We compare these different methods of achieving meaningful parameter values, finding that the parameter transformation method shows consistent results and that the other two provide no useful results. [ABSTRACT FROM AUTHOR]

The sensitivity of the process parameters of the Biosphere Energy Transfer HYdrology (BETHY) model to choices of atmospheric concentration network, high frequency terrestrial fluxes, and the choice of flux measurement network is investigated by using a carbon cycle data assimilation system. We use BETHY-generated fluxes as a proxy of flux measurements. Results show that monthly mean or low-frequency observations of CO2 concentration provide strong constraints on parameters relevant for net flux (NEP) but only weak constraints for parameters controlling gross fluxes. The use of high-frequency CO2 concentration observations, which has led to great refinement of spatial scales in inversions of net flux, adds little to the observing system in the Carbon Cycle Data Assimilation System (CCDAS) case. This unexpected result is explained by the fact that the stations of the CO2 concentration network we use are not well placed to measure such high frequency signals. Indeed, CO2 concentration sensitivities relevant for such high frequency fluxes are found to be largely confined in the vicinity of the corresponding fluxes, and are therefore not well observed by background monitoring stations. In contrast, our results clearly show the potential of flux measurements to better constrain the model parameters relevant for gross primary productivity (GPP) and net primary productivity (NPP). Given uncertainties in the spatial description of ecosystem functions, we recommend a combined observing strategy [ABSTRACT FROM AUTHOR]

Terrestrial productivity in semi-arid woodlands is strongly susceptible to changes in precipitation, and semi- arid woodlands constitute an important element of the global water and carbon cycles. Here, we use the Carbon Cycle Data Assimilation System (CCDAS) to investigate the key parameters controlling ecological and hydrological activities for a semi-arid savanna woodland site in Maun, Botswana. Twenty-four eco-hydrological process parameters of a terres-trial ecosystem model are optimized against two data streams separately and simultaneously: daily averaged latent heat flux (LHF) derived from eddy covariance measurements, and decadal fraction of absorbed photosynthetically active radiation (FAPAR) derived from the Sea-viewing Wide Field-of- view Sensor (SeaWiFS). Assimilation of both data streams LHF and FAPAR for the years 2000 and 2001 leads to improved agreement between measured and simulated quantities not only for LHF and FAPAR, but also for photosynthetic CO2 uptake. The mean uncertainty reduction (relative to the prior) over all parameters is 14.9% for the simultaneous assimilation of LHF and FAPAR, 8.5% for assimilating LHF only, and 6.1% for assimilating FAPAR only. The set of parameters with the highest uncertainty reduction is similar between assimilating only FAPAR or only LHF. The highest uncertainty reduction for all three cases is found for a parameter quantifying max- imum plant-available soil moisture. This indicates that not only LHF but also satellite-derived FAPAR data can be used to constrain and indirectly observe hydrological quantities. [ABSTRACT FROM AUTHOR]

The sensitivity of the process parameters of the biosphere model BETHY (Biosphere Energy Transfer HYdrology) to choices of atmospheric concentration network, high frequency terrestrial fluxes, and the choice of flux measurement network is investigated by using a carbon cycle data assimilation system. Results show that monthly mean or low-frequency observations of CO2 concentration provide strong constraints on parameters relevant for net flux (NEP) but only weak constraints for parameters controlling gross fluxes. The use of high-frequency CO2 concentration observations, which has allowed a great refinement of spatial scales in direct inversions, adds little to the observing system in this case. This unexpected result is explained by the fact that the stations of the CO2 concentration network we are using are not well placed to measure such high frequency signals. Indeed, CO2 concentration sensitivities relevant for such high frequency fluxes are found to be largely confined in the vicinity of the corresponding fluxes, and are therefore not well observed by background monitoring stations. In contrast, our results clearly show the potential of flux measurements to better constrain the model parameters relevant for gross primary productivity (GPP) and net primary productivity (NPP). Given uncertainties in the spatial description of ecosystem functions we recommend a combined observing strategy. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystem models (TEMs) contain the coupling of many biogeochemical processes with a large number of parameters involved. In many cases those parameters are highly uncertain. In order to reduce those uncertainties, parameter estimation methods can be applied, which allow the model to be constrained against observations. We compare the performance and results of two such parameter estimation techniques - the Metropolis algorithm (MA) which is a Markov Chain Monte Carlo (MCMC) method and the adjoint approach as it is used in the Carbon Cycle Data Assimilation System (CCDAS). Both techniques are applied here to derive the posterior probability density function (PDF) for 19 parameters of the Biosphere Energy Transfer and Hydrology (BETHY) scheme. We also use the MA to sample the posterior parameter distribution from the adjoint inversion. This allows us to assess if the commonly made assumption in variational data assimilation, that everything is normally distributed, holds. The comparison of the posterior parameter PDF derived by both metfiods shows that in most cases an approximation of the PDF by a normal distribution as used by the adjoint approach is a valid assumption. The results also indicate that the global minimum has been identified by both methods for the given set up. However, the adjoint approach outperforms the MA by several orders of magnitude in terms of computational time. Both methods show good agreement in the PDF of estimated net carbon fluxes for the decades of the 1980s and 1990s [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between the heterogeneity of the terrestrial carbon cycle and the optimal design of observing networks to constrain it. We combine the methods of quantitative network design and carboncycle data assimilation to a hierarchy of increasingly heterogeneous descriptions of the European terrestrial biosphere as indicated by increasing diversity of plant functional types. We employ three types of observations, flask measurements of CO2 concentrations, continuous measurements of CO2 and pointwise measurements of CO2 flux. We show that flux measurements are extremely efficient for relatively homogeneous situations but not robust against increasing or unknown complexity. Here a hybrid approach is necessary, we recommend its use in the development of integrated carbon observing systems. [ABSTRACT FROM AUTHOR]

The terrestrial biosphere is currently a strong sink for anthropogenic CO2 emissions. Through the radiative properties of CO2, the strength of this sink has a direct influence on the radiative budget of the global climate system. The accurate assessment of this sink and its evolution under a changing climate is, hence, paramount for any efficient management strategies of the terrestrial carbon sink to avoid dangerous climate change. Unfortunately, simulations of carbon and water fluxes with terrestrial biosphere models exhibit large uncertainties. A considerable fraction of this uncertainty reflects uncertainty in the parameter values of the process formulations within the models. This paper describes the systematic calibration of the process parameters of a terrestrial biosphere model against two observational data streams: remotely sensed FAPAR (fraction of absorbed photosynthetically active radiation) provided by the MERIS (ESA's Medium Resolution Imaging Spectrometer) sensor and in situ measurements of atmospheric CO2 provided by the GLOBALVIEW flask sampling network. We use the Carbon Cycle Data Assimilation System (CCDAS) to systematically calibrate some 70 parameters of the terrestrial BETHY (Biosphere Energy Transfer Hydrology) model. The simultaneous assimilation of all observations provides parameter estimates and uncertainty ranges that are consistent with the observational information. In a subsequent step these parameter uncertainties are propagated through the model to uncertainty ranges for predicted carbon fluxes. We demonstrate the consistent assimilation at global scale, where the global MERIS FAPAR product and atmospheric CO2 are used simultaneously. The assimilation improves the match to independent observations. We quantify how MERIS data improve the accuracy of the current and future (net and gross) carbon flux estimates (within and beyond the assimilation period). We further demonstrate the use of an interactive mission benefit analysis tool built around CCDAS to support the design of future space missions. We find that, for long-term averages, the benefit of FAPAR data is most pronounced for hydrological quantities, and moderate for quantities related to carbon fluxes from ecosystems. The benefit for hydrological quantities is highest for semi-arid tropical or sub-tropical regions. Length of mission or sensor resolution is of minor importance. [ABSTRACT FROM AUTHOR]

As high strength aluminum alloys are generally hard to deform, the application of conventional severe plastic deformation methods, which in principle allow the generation of ultra fine grained microstructures and increasing strength, is limited. In this study, cryogenic ECAP deformation as an alternative approach to deform a 7075 alloy is explored. Here, a tool with an internal angle of 90° is used. We demonstrate that cryogenic ECAP (followed by suitable heat treatments) results in increases of the degree of deformation, strength and ductility. Moreover, we present first results on the effect of cryogenic ECAP on microstructural evolution and mechanical properties of the 7075 alloy that demonstrate the potential of cryogenic forming to produce improved properties of high-strength aluminum alloys. [ABSTRACT FROM AUTHOR]

Terrestrial productivity in semi-arid woodlands is strongly susceptible to changes in precipitation, and semi-arid woodlands constitute an important element of the global water and carbon cycles. Here, we use the Carbon Cycle Data Assimilation System (CC-DAS) to investigate the mechanisms controlling ecological and hydrogical activities for a semi-arid savanna woodland site in Maun, Botswana. Twenty-four eco-hydrological process parameters of a terrestrial ecosystem model are optimized against two data streams either separately or simultaneously: daily averaged latent heat flux (LHF) derived from eddy covariance measurement, and decadal fraction of absorbed photosynthetically active radiation (FAPAR) derived from Sea-viewingWide Field-of-view Sensor (SeaWiFS). Assimilation of both LHF and FAPAR for the years 2000 and 2001 leads to improved agreement between measured and simulated quantities not only for LHF and FAPAR, but also for photosynthetic CO2 uptake. The closest agreement is found for each observed data stream when only the same data stream is assimilated. The mean uncertainty reduction (relative to the prior) over all parameters is 16.1% for the simultaneous assimilation of LHF and FAPAR, 9.2% for assimilating LHF only, and 7.8% for assimilating FAPAR only. Furthermore, the set of parameters with the highest uncertainty reduction is similar between assimilating only FAPAR or only LHF. The highest uncertainty reduction is found for a parameter describing maximum plant-available soil moisture for all three cases. This indicates that not only LHF but also satellite-derived FAPAR data can be used to constrain and indirectly observe hydrological quantities. [ABSTRACT FROM AUTHOR]

This paper combines an atmospheric transport model and a terrestrial ecosystem model to estimate gross primary productivity (GPP) and net ecosystem productivity (NEP) of the land biosphere. Using atmospheric CO2 observations in a Carbon Cycle Data Assimilation System (CCDAS) we estimate a terrestrial global GPP of 146 ± 19 GtC/yr. However, the current observing network cannot distinguish this best estimate from a different assimilation experiment yielding a terrestrial global GPP of 117 GtC/yr. Spatial estimates of GPP agree with data-driven estimates in the extratropics but are overestimated in the poorly observed tropics. The uncertainty analysis of previous studies was extended by using two atmospheric transport models and different CO2 observing networks. We find that estimates of GPP and NEP are less sensitive to these choices than the form of the prior probability for model parameters. NEP is also found to be significantly sensitive to the transport model and this sensitivity is not greatly reduced compared to direct atmospheric transport inversions, which optimize NEP directly. [ABSTRACT FROM AUTHOR]

The terrestrial biosphere is currently a strong sink for anthropogenic CO2 emissions. Through the radiative properties of CO2 the strength of this sink has a direct influence on the radiative budget of the global climate system. The accurate assessment of this sink and its evolution under a changing climate is, hence, paramount for any efficient management strategies of the terrestrial carbon sink to avoid dangerous climate change. Unfortunately, simulations of carbon and water fluxes with terrestrial biosphere models exhibit large uncertainties. A considerable fraction of this uncertainty is reflecting uncertainty in the parameter values of the process formulations within the models. This paper describes the systematic calibration of the process parameters of a terrestrial biosphere model against two observational data streams: remotely sensed FAPAR provided by the MERIS sensor and in situ measurements of atmospheric CO2 provided by the GLOBALVIEW flask sampling network. We use the Carbon Cycle Data Assimilation System (CCDAS) to systematically calibrate some 70 parameters of the terrestrial biosphere model BETHY. The simultaneous assimilation of all observations provides parameter estimates and uncertainty ranges that are consistent with the observational information. In a subsequent step these parameter uncertainties are propagated through the model to uncertainty ranges for predicted carbon fluxes. We demonstrate the consistent assimilation for two different set-ups: first at site scale, where MERIS FAPAR observations at a range of sites are used as simultaneous constraints, and second at global scale, where the global MERIS FAPAR product and atmospheric CO2 are used simultaneously. On both scales the assimilation improves the match to independent observations. We quantify how MERIS data improve the accuracy of the current and future (net and gross) carbon flux estimates (within and beyond the assimilation period). We further demonstrate the use of an interactive mission benefit analysis tool built around CCDAS to support the design of future space missions. We find that, for long-term averages, the benefit of FAPAR data is most pronounced for hydrological quantities, and moderate for quantities related to carbon fluxes from ecosystems. The benefit for hydrological quantities is highest for semi-arid tropical or sub-tropical regions. Length of mission or sensor resolution is of minor importance. [ABSTRACT FROM AUTHOR]

The article discusses the carbon cycle modelling using the Carbon Cycle Data Assimilation System (CCDAS) that evaluates the Biosphere Energy Transfer and Hydrology scheme (BETHY). It discusses the impact of terrestrial biosphere on global carbon cycle and the accumulation of carbon dioxide (CO2). It reports that the method serves as a parameter for carbon cycle-climate and for future climate change.

Better estimates of the net exchange of CO2 between the atmosphere and the terrestrial biosphere are urgently needed to improve predictions of future CO2 levels in the atmosphere. The carbon cycle data assimilation system (CCDAS) offers the capability of inversion, while it is at the same time based on a process model that can be used independent of observational data. CCDAS allows the assimilation of atmospheric CO2 concentrations into the terrestrial biosphere model BETHY, constraining its process parameters via an adjoint approach. Here, we investigate the effect of spatial differentiation of a universal carbon balance parameter of BETHY on posterior net CO2 fluxes and their uncertainties. The parameter, β, determines the characteristics of the slowly decomposing soil carbon pool and represents processes that are difficult to model explicitly. Two cases are studied with an assimilation period of 1979 to 2003. In the base case, there is a separate β for each plant functional type (PFT). In the regionalization case, β is differentiated not only by PFT, but also according to each of 11 large continental regions as used by the TransCom project. We find that the choice of spatial differentiation has a profound impact not only on the posterior (optimized) fluxes and their uncertainties, but even more so on the spatial covariance of the uncertainties. Differences are most pronounced in tropical regions, where observations are sparse. While regionalization leads to an improved fit to the observations by about 20% compared to the base case, we notice large spatial variations in the posterior net CO2 flux on a grid cell level. The results illustrate the need for universal process formulations in global-scale atmospheric CO2 inversion studies, at least as long as the observational network is too sparse to resolve spatial fluctuations at the regional scale. [ABSTRACT FROM AUTHOR]

ESA's Earth Explorer candidate mission A-SCOPE aims at observing CO from space with an active LIDAR instrument. This study employs quantitative network design techniques to investigate the benefit of A-SCOPE observations in a Carbon Cycle Data Assimilation System. The system links the observations to the terrestrial vegetation model BETHY via the fine resolution version of the atmospheric transport model TM3. In the modelling process chain the observations are used to reduce uncertainties in the values of BETHY's process parameters, and then the uncertainty in the process parameters is mapped forward to uncertainties in both in long-term net carbon flux and net primary productivity over three regions. A-SCOPE yields considerably better reductions in posterior uncertainties than the ground-based GLOBALVIEW station network. This is true for assimilating monthly mean values and instantaneous values, and it is true for two potential vertical weighting functions. The strength of the constraint through A-SCOPE observations is high over the range of observational uncertainties. [ABSTRACT FROM AUTHOR]

Remote sensing is increasingly being used as a cost-effective and practical solution for the rapid evaluation of impacts from wildland fires. The present study investigates the use of the support vector machine (SVM) classification method with multispectral data from the Advanced Spectral Emission and Reflection Radiometer (ASTER) for obtaining a rapid and cost effective post-fire assessment in a Mediterranean setting. A further objective is to perform a detailed intercomparison of available burnt area datasets for one of the most catastrophic forest fire events that occurred near the Greek capital during the summer of 2007. For this purpose, two ASTER scenes were acquired, one before and one closely after the fire episode. Cartography of the burnt area was obtained by classifying each multiband ASTER image into a number of discrete classes using the SVM classifier supported by land use/cover information from the CORINE 2000 land nomenclature. Overall verification of the derived thematic maps based on the classification statistics yielded results with a mean overall accuracy of 94.6% and a mean Kappa coefficient of 0.93. In addition, the burnt area estimate derived from the post-fire ASTER image was found to have an average difference of 9.63% from those reported by other operationally-offered burnt area datasets available for the test region. [ABSTRACT FROM AUTHOR]

The LPJ terrestrial carbon isotope model, which includes isotopic fractionation of 13C during assimilation and a full description of the isotopic terrestrial carbon cycle, has been used to calculate the atmosphere-biosphere exchange flux of CO2 and its δ13C for the years 1901 to 1998. A transient, spatially explicit data set of C4 crops and tropical C4 pastures has been compiled. In combination with a land use scheme this allows the analysis of the impact of land use conversion of C3 ecosystems to C4 cultivation, besides climate, fire disturbances, atmospheric CO2 and the isotope ratio of atmospheric CO2, on the terrestrial carbon stable isotope composition. Globally averaged values of modeled leaf discrimination vary between 17.9‰ and 17.0‰ depending on the chosen land use scheme and also the year of the simulation. Results from the simulation experiment prescribing the conversion of C3 ecosystems into C4 crops and C4 pastures show the lowest leaf discrimination. Modeled values of isotopic disequilibrium flux, caused by the δ13C difference between fixed CO2 and released CO2, similarly depend on the amount of prescribed C4 vegetation and vary between 37.9 Pg C‰ yr-1 and 23.9 Pg C‰ yr-1 averaged over the years 1985 to 1995. In addition, the effect of fire on the isotopic disequilibrium has been diagnosed; generally wildfires lead to a disequilibrium reduction of ≈10 Pg C‰ yr-1 because they shorten the turnover time of terrestrial carbon. If used in a global double deconvolution study, the differences in the results between the standard experiment without any C4 cultivation and the experiment including C4 crops and pastures could account for a shift of about 1 Pg C yr-1 from the inferred terrestrial sources to the ocean fluxes. [ABSTRACT FROM AUTHOR]

This paper presents the space-time distribution of terrestrial carbon fluxes for the period 1979-1999 generated by a terrestrial carbon cycle data assimilation system (CCDAS). CCDAS is based around the Biosphere Energy Transfer Hydrology model. We assimilate satellite observations of photosynthetically active radiation and atmospheric CO2 concentration observations in a two-step process. The control variables for the assimilation are the parameters of the carbon cycle model. The optimized model produces a moderate fit to the seasonal cycle of atmospheric CO2 concentration and a good fit to its interannual variability. Long-term mean fluxes show large uptakes over the northern midlatitudes and uptakes over tropical continents partly offsetting the prescribed efflux due to land use change. Interannual variability is dominated by the tropics. On interannual timescales the controlling process is net primary productivity (NPP) while for decadal changes the main driver is changes in soil respiration. An adjoint sensitivity analysis reveals that uncertainty in long-term storage efficiency of soil carbon is the largest contributor to uncertainty in net flux. [ABSTRACT FROM AUTHOR]

The response of a coupled atmosphere-ocean general circulation model to insolation representative of 6000 years ago has been studied with a set of 1000-year quasi-equilibrium simulations. Comparison with similar experiments with an uncoupled atmosphere general circulation model demonstrates the importance of an interactive ocean for the climate signal. The model simulates an intensification of the African and Asian monsoons and a warming at high northern latitudes with reduced sea ice. Data from the coupled climate model have been used to drive a dynamical vegetation model. The modelled response is a marked increase in vegetation cover in the Sahara and a poleward shift of vegetation zones in high northern latitudes. [ABSTRACT FROM AUTHOR]