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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.

This model presents an improvement of the original model by Verstraete et al., (1990) in order to account for the effects due to an underlying soil below the vegetation canopy. The unscattered and singly scattered by the leaves components are solved exactly using an analytical hot‐spot description. The multiply scattered component is approximated on the basis of a Discrete Ordinates Method reduced to a one‐angle problem and assuming isotropic scattering. This model is then compared to others existing reference models and it is also used in an inversion procedure to examine its performances for real remote sensing applications.

Dynamic Global Vegetation Models (DGVM) are an essential part of current state-of-the-art Earth System Models. In recent years, the complexity of DGVM has increased by incorporating new important processes, like e.g. nutrient cycling and land cover dynamics while biogeophysical processes, like surface radiation have been not much further developed. Canopy radiation models are however very important for the estimation of absorption and reflected fluxes and are essential for a proper estimation of surface carbon, energy and water fluxes. The present study provides an overview about current implementations of canopy radiation schemes in a couple of state-of-the-art DGVMs and evaluates their accuracy in simulating canopy absorption and reflection for a variety of different surface conditions. Systematic deviations in surface albedo and fraction of absorbed photosynthetic active radiation (faPAR) are identified and potential impacts are assessed. The results show clear deviations for both, absorbed and reflected, surface solar radiation fluxes. FaPAR is typically underestimated which results in an underestimation of Gross Primary Productivity (GPP) for the investigated cases. The deviation can be as large as 25% in extreme cases. Deviations in surface albedo range between −0.15 ≤ Δ α ≤ 0.36 with slight positive bias in the order of Δ α ≈ 0.04. Potential radiative forcing caused by albedo deviations is estimated as −1.25 ≤ RF ≤ −0.8 [W m−2] caused by a neglecting the diurnal cycle of surface albedo. The present study is the first one that provides an evaluation of canopy RT schemes in different currently used DGVMs together with an assessment of the potential impact of the identified deviations. The paper illustrates that there is a general need to improve the canopy radiation schemes in DGVMs and provides different perspectives for their improvement.

Despite an emerging body of literature linking canopy albedo to forest management, understanding of the process is still fragmented. We combined a stand-level forest gap model with a canopy radiation transfer model and satellite-derived model parameters to quantify the effects of forest thinning, that is removing trees at a certain time during the forest rotation, on summertime canopy albedo. The effects of different forest species (pine, beech, oak) and four thinning strategies (light to intense thinning regimes) were examined. During stand establishment, summertime canopy albedo is driven by tree species. In the later stages of stand development, the effect of tree species on summertime canopy albedo decreases in favour of an increasing influence of forest thinning on summertime canopy albedo. These trends continue until the end of the rotation where thinning explains up to 50% of the variance in near-infrared canopy albedo and up to 70% of the variance in visible canopy albedo. More intense thinning lowers the summertime shortwave albedo in the canopy by as much as 0.02 compared to unthinned forest. The structural changes associated with forest thinning can be described by the change in LAI in combination with crown volume. However, forests with identical canopy structure can have different summertime albedo values due to their location: the further north a forest is situated, the more the solar zenith angle increases and thus the higher is the summertime canopy albedo, independent of the wavelength. Despite the increase of absolute summertime canopy albedo values with latitude, the difference in canopy albedo between managed and unmanaged forest decreases with increasing latitude. Forest management thus strongly altered summertime forest albedo.

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. The use of observational information is required to reduce this uncertainty. Systematic model calibration through inversion procedures can infer parameter ranges that are consistent with the observations and exclude parameter ranges that are inconsistent with observations., JRC.H.7-Climate Risk Management

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.

Photosynthesis by terrestrial plants is the main driver of the global carbon cycle, and the presence of actively photosynthesizing vegetation can now be observed from space. However, challenges remain when translating remotely sensed data into carbon fluxes. One reason is that the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), which documents the presence of photosynthetically active vegetation, relates more directly to leaf development and leaf phenology than to photosynthetic rates. Here, we present a new approach for linking FAPAR and vegetation-to-atmosphere carbon fluxes through variational data assimilation. The scheme extends the Carbon Cycle Data Assimilation System (CCDAS) by a newly developed, globally applicable and generic leaf phenology model, which includes both temperature and water-driven leaf development. CCDAS is run for seven sites, six of them included in the FLUXNET network. Optimization is carried out simultaneously for all sites against 20 months of daily FAPAR from the Medium Resolution Imaging Spectrometer on board the European Space Agency's ENVISAT platform. Fourteen parameters related to phenology and 24 related to photosynthesis are optimized simultaneously, and their posterior uncertainties are computed. We find that with one parameter set for all sites, the model is able to reproduce the observed FAPAR spanning boreal, temperate, humid-tropical, and semiarid climates. Assimilation of FAPAR has led to reduced uncertainty (by >10%) of 10 of the 38 parameters, including one parameter related to photosynthesis, and a moderate reduction in net primary productivity uncertainty. The approach can easily be extended to regional or global studies and to the assimilation of further remotely sensed data. (Less)

Canopy radiative transfer (RT) models simulate radiative transfer processes in the solar domain at or near the Earth’s terrestrial surface, i.e., within plant canopies and over bare soil surfaces. Such models are capable of simulating the transmitted, reflected and absorbed radiation fluxes, as well as, the angular distribution of the reflected light above vegetated surfaces in the optical domain of the solar spectrum. This directional aspect is important since the brightness with which a given canopy target appears in Earth Observation data (pixel) depends not only on the structural and spectral properties of the target area but also on the viewing and illumination geometry at the time of measurement. The quantitative interpretation of remote sensing data thus hinges more and more on the exploitation of RT models: In operational contexts they are used to pre-compute Look-Up-Tables of quantities required by the inversion algorithms, whereas, in off-line applications they may be directly inverted against the measurements to yield sets of state variables that describe the properties of the observed target. In both cases, the accuracy and reliability of the solutions to the inverse problems are determined by the performance of the RT model as well as the remote sensing instrument. Reducing the uncertainty of RT models will thus increase the quality of the information derived from remote sensing data (which is of interest to scientists and policy makers), and augment the reliability of RT model studies in forward mode (which is of interest to space agencies when testing new sensor concepts or mission strategies). This understanding has led to a series of model intercomparison projects (MIP) aiming either to document the spread of currently available simulation models, or, else to assess and benchmark the quality of their simulation results, e.g. (Bull. Am. Meteorol. Soc. 73:1962–1970, 1998; J. Geophys. Res. 106:11937–11956, 2001; J. Geophys. Res. 109:D06210, 2004; J. Geophys. Res. 110, 2005; Bull. Am. Meteorol. Soc. 86:1275–1293, 2005; J. Geophys. Res., 2007). Among these MIPs the RAdiation transfer Model Intercomparison (RAMI) activity focuses on the proper representation of the radiative processes occurring in vegetated environments in the optical domain of the solar spectrum.

Understanding the carbon dynamics of the terrestrial biosphere during climate fluctuations is a prerequisite for any reliable modeling of the climate-carbon cycle feedback. We drive a terrestrial vegetation model with observed climate data to show that most of the fluctuations in atmospheric CO2 are consistent with the modeled shift in the balance between carbon uptake by terrestrial plants and carbon loss through soil and plant respiration. Simulated anomalies of the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) during the last two El Nino events also agree well with satellite observations. Our model results suggest that changes in net primary productivity (NPP) are mainly responsible for the observed anomalies in the atmospheric CO2 growth rate. Changes in heterotrophic respiration (Rh) mostly happen in the same direction, but with smaller amplitude. We attribute the unusual acceleration of the atmospheric CO2 growth rate during 2002-2003 to a coincidence of moderate El Nino conditions in the tropics with a strong NPP decrease at northern mid latitudes, only partially compensated by decreased Rh. (Less)

International audience; The inference of surface reflectance from satellite observations requires the knowledge of the double-way transmittance through the atmosphere. Since the existing pyranometer networks routinely provide measurements of the incident transmittance over sensitive climatic regions, it would be useful for subsequent applications to relate this ground-based measurement to the corresponding double-way transmittance. A variety of satellite radiance simulations corresponding to clear sky conditions has been made in order to derive a suitable parameterized expression between the two quantities. The accuracy of this expression when making use of additional meteorological observations is shown and discussed. Finally, the derived expression is used to improve a method recently proposed by Pinty et al. for retrieving surface albedo over the African Sahel from METEOSAT radiances.

This note describes low-level observations obtained during WAMEX from an instrumented DC 7 aircraft. These data give a detailed description of the dynamical and thermodynamical structure of the layer 0.5–3 km over a zonal and a meridional cross section. The results indicate that a large and variable northerly wind occurs down to the Equator in the monsoon layer.

Surface albedo can be inferred from geostationary satellite measurements as long as the effects due to the atmosphere, the spectral response of the sensor, and the angular anisotropy of the reflected field are corrected. In this paper, we developed a method which includes ad hoc correction procedures for the three categories of effects. An application of the method is conducted over the Sahara and the African Sahel using METEOSAT radiances together with auxiliary data derived from other satellites (Tiros-N and Nimbus-7) and standard meteorological observations. The surface albedo maps are estimated over this region, at a spatial resolution compatible with one used in climate models, for 2 days representative of the dry and the wet seasons, respectively. The observed seasonal surface albedo change and the relationships between the surface and the planetary albedos are discussed in order to examine the validity of the method and the correction procedures.