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Pinty B.,European Commission - Joint Research Center Ispra | Pinty B.,Earth Observation Directorate | Widlowski J.-L.,European Commission - Joint Research Center Ispra | Verstraete M.M.,European Commission - Joint Research Center Ispra | And 5 more authors.
Geophysical Research Letters | Year: 2011

The fraction of radiation absorbed in the canopy depends on the amount and angular distribution of the solar irradiance reaching the top of the canopy as well as the fraction of this irradiance that is transmitted through the canopy gaps and reflected back to the vegetation by the background. This contribution shows that the presence of snow on forest floors enhances the fraction of absorbed Photosynthetically Active Radiation (PAR). A global analysis of satellite-derived products reveals that this enhancement affects evergreen and deciduous forests of the boreal zone. This snow-related effect may usefully contribute to the photosynthesis process in evergreen forests especially during spring time when radiation conditions are marginal but other physiological constraints (such as temperature) permit the necessary biochemical functions to take place. © 2011 by the American Geophysical Union.


Kato T.,University of Bristol | Kato T.,Japan Agency for Marine - Earth Science and Technology | Kato T.,CEA Saclay Nuclear Research Center | Knorr W.,University of Bristol | And 8 more authors.
Biogeosciences | Year: 2013

Terrestrial productivity in semi-arid woodlands is strongly susceptible to changes in precipitation, and semiarid 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 terrestrial 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-ofview 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 maximum 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. © Author(s) 2013.


Pinty B.,European Commission - Joint Research Center Ispra | Pinty B.,Earth Observation Directorate | Andredakis I.,European Commission - Joint Research Center Ispra | Clerici M.,European Commission - Joint Research Center Ispra | And 6 more authors.
Journal of Geophysical Research: Atmospheres | Year: 2011

The two-stream model parameters and associated uncertainties retrieved by inversion against MODIS broadband visible and near-infrared white sky surface albedos were discussed in a companion paper. The present paper concentrates on the partitioning of the solar radiation fluxes delivered by the Joint Research Centre Two-stream Inversion Package (JRC-TIP). The estimation of the various flux fractions related to the vegetation and the background layers separately capitalizes on the probability density functions of the model parameters discussed in the companion paper. The propagation of uncertainties from the observations to the model parameters is achieved via the Hessian of the cost function and yields a covariance matrix of posterior parameter uncertainties. This matrix is propagated to the radiation fluxes via the model's Jacobian matrix of first derivatives. Results exhibit a rather good spatiotemporal consistency given that the prior values on the model parameters are not specified as a function of land cover type and/or vegetation phenological states. A specific investigation based on a scenario imposing stringent conditions of leaf absorbing and scattering properties highlights the impact of such constraints that are, as a matter of fact, currently adopted in vegetation index approaches. Special attention is also given to snow-covered and snow-contaminated areas since these regions encompass significant reflectance changes that strongly affect land surface processes. A definite asset of the JRC-TIP lies in its capability to control and ultimately relax a number of assumptions that are often implicit in traditional approaches. These features greatly help us understand the discrepancies between the different data sets of land surface properties and fluxes that are currently available. Through a series of selected examples, the inverse procedure implemented in the JRC-TIP is shown to be robust, reliable, and compliant with large-scale processing requirements. Furthermore, this package ensures the physical consistency between the set of observations, the two-stream model parameters, and radiation fluxes. It also documents the retrieval of associated uncertainties. Copyright © 2011 by the American Geophysical Union.


Kaminski T.,FastOpt | Knorr W.,University of Bristol | Knorr W.,Aristotle University of Thessaloniki | Scholze M.,University of Bristol | And 5 more authors.
Biogeosciences | Year: 2012

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. © 2012 Author(s).


Schurmann G.J.,Max Planck Institute for Biogeochemistry | Kaminski T.,Inversion Laboratory | Kostler C.,Max Planck Institute for Biogeochemistry | Carvalhais N.,Max Planck Institute for Biogeochemistry | And 7 more authors.
Geoscientific Model Development | Year: 2016

We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS) built around the tangent-linear version of the JSBACH land-surface scheme, which is part of the MPI-Earth System Model v1. The simulated phenology and net land carbon balance were constrained by globally distributed observations of the fraction of absorbed photosynthetically active radiation (FAPAR, using the TIP-FAPAR product) and atmospheric CO2 at a global set of monitoring stations for the years 2005 to 2009. When constrained by FAPAR observations alone, the system successfully, and computationally efficiently, improved simulated growing-season average FAPAR, as well as its seasonality in the northern extra-tropics. When constrained by atmospheric CO2 observations alone, global net and gross carbon fluxes were improved, despite a tendency of the system to underestimate tropical productivity. Assimilating both data streams jointly allowed the MPI-CCDAS to match both observations (TIP-FAPAR and atmospheric CO2) equally well as the single data stream assimilation cases, thereby increasing the overall appropriateness of the simulated biosphere dynamics and underlying parameter values. Our study thus demonstrates the value of multiple-data-stream assimilation for the simulation of terrestrial biosphere dynamics. It further highlights the potential role of remote sensing data, here the TIP-FAPAR product, in stabilising the strongly underdetermined atmospheric inversion problem posed by atmospheric transport and CO2 observations alone. Notwithstanding these advances, the constraint of the observations on regional gross and net CO2 flux patterns on the MPI-CCDAS is limited through the coarse-scale parametrisation of the biosphere model. We expect improvement through a refined initialisation strategy and inclusion of further biosphere observations as constraints. © Author(s) 2016.


Pinty B.,Center for Monitoring Research | Pinty B.,Earth Observation Directorate | Jung M.,Max Planck Institute for Biogeochemistry | Kaminski T.,FastOpt | And 5 more authors.
Remote Sensing of Environment | Year: 2011

The Joint Research Centre Two-stream Inversion Package (JRC-TIP) makes use of white sky albedo products-derived from MODIS and MISR observations in the visible and near-infrared domain-to deliver consistent sets of information about the terrestrial environments that gave rise to these data. The baseline version of the JRC-TIP operates at a spatial resolution of 0.01° and yields estimates of the Probability Distribution Functions (PDFs) of the effective canopy Leaf Area Index (LAI), the canopy background albedo, the vegetation scattering properties, as well as, the absorbed, reflected and transmitted fluxes of the vegetation canopy. In this contribution the evaluation efforts of the JRC-TIP products are extended to the deciduous forest site of Hainich (Germany) where multiannual datasets of in-situ estimates of canopy transmission-derived from LAI-2000 observations-are available. As a Fluxnet site, Hainich offers access to camera acquisitions from fixed locations in and above the canopy that are being used in phenological studies. These images qualitatively confirm the seasonal patterns of the effective LAI, canopy transmission and canopy absorption products (in the visible range of the solar spectrum) derived with the JRC-TIP. Making use of the LAI-2000 observations it is found that 3/4 of the JRC-TIP products lie within a ± 0.15 interval around the in-situ estimates of canopy transmission and absorption. The largest discrepancies occur at the end of the senescence phase when the scattering properties of the vegetation (evidenced by the pictures) and the images qualitatively confirm the seasonal patterns of the effective LAI, canopy transmission and canopy absorption products (in the visible range of the solar spectrum) derived with the JRC-TIP. Making use of the LAI-2000 observations it is found that 3/4 of the JRC-TIP products lie within a ± 0.15 interval around the in-situ estimates of canopy transmission and absorption. The largest discrepancies occur at the end of the senescence phase when the scattering properties of the vegetation (evidenced by the pictures) and the effective LAI (also derived from LAI-2000 measurements) are experiencing large simultaneous changes. It was also found that the seasonal pattern of vegetation scattering properties derived from MISR observations in the near-infrared varies together with the Excess Green index computed from the various channels of the camera data acquired at the top of the canopy. © 2011 Elsevier Inc.


Scholze M.,Lund University | Kaminski T.,The Inversion Laboratory | Knorr W.,Lund University | Blessing S.,FastOpt | And 3 more authors.
Remote Sensing of Environment | Year: 2016

Carbon dioxide (CO 2) is the most important anthropogenic greenhouse gas contributing to about half of the total anthropogenic change in the Earth's radiation budget. And about half of the anthropogenic CO2 emissions stay in the atmosphere, the remainder is taken up by the biosphere. It is of paramount importance to better understand CO2 sources and sinks and their spatio-temporal distribution. In the context of climate change this information is needed to improve the projections of future trends in carbon sinks and sources. Since the terrestrial carbon and water cycles are tightly coupled by biological plant processes, i.e. through the stomatal gas exchange with the atmosphere, it is expected that information on the soil moisture state will help to constrain terrestrial carbon fluxes. In the present feasibility study we employ the Carbon Cycle Data Assimilation System CCDAS to pioneer the assimilation of the SMOS L3 soil moisture product together with another biophysical data set - in this case atmospheric CO2 flask samples. The two data streams are assimilated into a process-based model of the terrestrial carbon cycle over two years. CCDAS aims to optimise model process parameters and subsequently land surface CO2 exchange fluxes. We find that the assimilation of SMOS data improves the agreement with independent soil moisture data from the active ASCAT instrument. In both cases the assimilation also improves the fit of modelled atmospheric CO2 to the observations at flask sampling sites which have not been used in the assimilation. Reduction of uncertainty relative to the prior is generally high for both regional net ecosystem productivity and net primary productivity and considerably higher than for assimilating CO2 only, which quantifies the added value of SMOS observations as a constraint on the terrestrial carbon cycle. The study demonstrates a high potential for a SMOS L4 carbon flux product. © 2016 Elsevier Inc.


Koffi E.N.,French Climate and Environment Sciences Laboratory | Rayner P.J.,University of Melbourne | Scholze M.,University of Bristol | Chevallier F.,French Climate and Environment Sciences Laboratory | Kaminski T.,FastOpt
Atmospheric Chemistry and Physics | Year: 2013

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. © Author(s) 2013. CC Attribution 3.0 License.


Kaminski T.,FastOpt | Rayner P.J.,University of Melbourne | Vobeck M.,FastOpt | Scholze M.,University of Bristol | Koffi E.,LSCE IPSL
Atmospheric Chemistry and Physics | Year: 2012

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 carbon-cycle 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 CO 2 and pointwise measurements of CO 2 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, and we recommend its use in the development of integrated carbon observing systems. © 2012 Author(s).


Kaminski T.,FastOpt | Scholze M.,University of Bristol | Houweling S.,SRON Netherlands Institute for Space Research
Tellus, Series B: Chemical and Physical Meteorology | Year: 2010

ESA's Earth Explorer candidate mission A-SCOPE aims at observing CO2 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. © 2010 The Authors Tellus B © 2010 International Meteorological Institute in Stockholm.

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