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We use a carbon-cycle data assimilation system to estimate the terrestrial biospheric CO2 flux until 2090. The terrestrial sink increases rapidly and the increase is stronger in the presence of climate change. Using a linearized model, we calculate the uncertainty in the flux owing to uncertainty in model parameters. The uncertainty is large and is dominated by the impact of soil moisture on heter
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 a
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 transpo
Satellite remote sensing, with its unique synoptic coverage capabilities, can provide accurate and immediately valuable information on fire analysis and post-fire assessment, including estimation of burnt areas. In this study the potential for burnt area mapping of the combined use of Artificial Neural Network (ANN) and Spectral Angle Mapper (SAM) classifiers with Landsat TM satellite imagery was
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
This chapter provides a high-level summary of the state of knowledge regarding observations, processes and models of climate, terrestrial ecosystems and the global carbon cycle. We focus strongly on observations (at various timescales, including palaeo timescales as appropriate), and what can be learned from their interpretation in the light of the established principles of climate science and ter
Here, we discuss the feedback processes that determine the nature and rates of climatic changes in response to climate forcing. We explain the differences in the characteristic behaviour of biophysical and biogeochemical feedbacks, and describe the means by which feedbacks can be identified using models and observational data, and their strength quantified. Improved understanding of these kinds of
Sensitivity analysis consists of an integral and important validatory check of a computer simulation model before the code is used in performing any kind of analysis operation. The present paper demonstrates the use of a relatively new method and tool for conducting global sensitivity analysis (GSA) for environmental models, providing simultaneously the first GSA study of the widely used 1d soil-v
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 wi
The current and future strength of the terrestrial carbon sink has a crucial influence on the expected climate warming on Earth. Usually, Earth Observation (EO) by its very nature focusses on diagnosing the current state of the planet. However, it is possible to use EO products in data assimilation systems to improve not only the diagnosis of the current state, but also the accuracy of future pred
The paper presents a feasibility study for a Climate Prediction Data Assimilation System following the methodological approach of the Carbon Cycle Data Assimilation System (CCDAS). The usefulness of accurate gradient information for estimating process parameters of the spectral atmospheric circulation model PUMA on climate time-scales is investigated. Pseudo observations of the long-term mean surf
One of the major advantages of carbon cycle data assimilation is the possibility to estimate carbon fluxes with uncertainties in a prognostic mode, that is beyond the time period of carbon dioxide (CO2) observations. The carbon cycle data assimilation system is built around the Biosphere Energy Transfer Hydrology Scheme (BETHY) model, coupled to the atmospheric transport model TM2. It uses about 2
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 ca
We quantify the risks of climate-induced changes in key ecosystem processes during the 21st century by forcing a dynamic global vegetation model with multiple scenarios from 16 climate models and mapping the proportions of model runs showing forest/nonforest shifts or exceedance of natural variability in wildfire frequency and freshwater supply. Our analysis does not assign probabilities to scenar
This chapter uses the mass-conservation equations for CO2 and its isotopomers 13CO2 and CO18O that can be used to infer globally biospheric and oceanic net fluxes in the case of 18C, and gross terrestrial biospheric fluxes in the case of 18O. The quantitative use of atmospheric measurements of 13C and 18O in CO2 to better constrain those fluxes requires knowledge of various processes specific to e
We present a prototype of a Carbon Cycle Data Assimilation System (CCDAS), which is composed of a terrestrial biosphere model (BETHY) coupled to an atmospheric transport model (TM2), corresponding derivative codes and a derivative-based optimisation routine. In calibration mode, we use first and second derivatives to estimate model parameters and their uncertainties from atmospheric observations a
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 contr
The response of atmospheric CO2 and climate to the reconstructed variability in solar irradiance and radiative forcing by volcanoes over the last millennium is examined by applying a coupled physical-biogeochemical climate model that includes the Lund-Potsdam-Jena dynamic global vegetation model (LPJ-DGVM) and a simplified analogue of a coupled atmosphere-ocean general circulation model. The model
Abrupt climatic changes have occurred several times in the past, leading to large-scale modifications of vegetation patterns with important consequences for the global carbon cycle. Dynamic global vegetation models (DGVM) constitute an advanced tool for reconstructing past or predicting future shifts in vegetation distributions in response to climatic change on a global scale. The Lund-Potsdam-Jen
