Agency: European Commission | Branch: FP7 | Program: CP-IP | Phase: Ocean.2010-1 | Award Amount: 14.85M | Year: 2011
The Arctic is engaged in a deep climatic evolution. This evolution is quite predictable at short (year) and longer scales (several decades), but it is the decadal intermediate scale that is the most difficult to predict. This is because the natural variability of the system is large and dominant at this scale, and the system is highly non linear due to positive and negative feedback between sea ice, the ocean and atmosphere. Already today, due to the increase of the GHG concentration in the atmosphere and the amplification of global warming in the Arctic, the impacts of climate change in the region are apparent, e.g. in the reduction in sea ice, in changes in weather patterns and cyclones or in the melting of glaciers and permafrost. It is therefore not surprising that models clearly predict that Artic sea ice will disappear in summer within 20 or 30 years, yielding new opportunities and risks for human activities in the Arctic. This climatic evolution is going to have strong impacts on both marine ecosystems and human activities in the Arctic. This in turn has large socio-economic implications for Europe. ACCESS will evaluate climatic impacts in the Arctic on marine transportation (including tourism), fisheries, marine mammals and the extraction of hydrocarbons for the next 20 years; with particular attention to environmental sensitivities and sustainability. These meso-economic issues will be extended to the macro-economic scale in order to highlight trans-sectoral implications and provide an integrated assessment of the socio-economic impact of climate change. An important aspect of ACCESS, given the geostrategic implication of Arctic state changes, will be the consideration of Arctic governance issues, including the framework UNCLOS (United Nations Convention for the Law of the Sea). ACCESS dedicates a full work package to integrate Arctic climate changes, socioeconomic impacts and Arctic governance issues.
Agency: European Commission | Branch: FP7 | Program: CP-IP-SICA | Phase: ENV.2011.4.1.1-1 | Award Amount: 8.67M | Year: 2011
Today, countries use a wide variety of methods to monitor the carbon cycle and it is difficult to compare data from country to country and to get a clear global picture. The current global observational and modelling capabilities allow us to produce estimates of carbon budget at different level (from local to global) but many uncertainties still remain. Decision makers need now more than ever systematic, consistent and transparent data, information and tools for an independent and reliable verification process of greenhouse gas emissions and sinks. Therefore higher quality and quantity of CO2 and CH4 data, from different domains and with an enhanced spatial and temporal resolution, need to be collected by a globally integrated observation and analysis system. This can be obtained by the coordinated Global Carbon Observation and Analysis System that this project aims at designing, addressing the climate targets of the Group on Earth Observations (GEO) toward building a Global Earth Observation System of Systems (GEOSS) for carbon. Specific objectives of the GEOCARBON project are: Provide an aggregated set of harmonized global carbon data information (integrating the land, ocean, atmosphere and human dimension) Develop improved Carbon Cycle Data Assimilation Systems (CCDAS) Define the specifications for an operational Global Carbon Observing System Provide improved regional carbon budgets of Amazon and Central Africa Provide comprehensive and synthetic information on the annual sources and sinks of CO2 for the globe and for large ocean and land regions Improve the assessment of global CH4 sources and sinks and develop the CH4 observing system component Provide an economic assessment of the value of an enhanced Global Carbon Observing System Strengthen the effectiveness of the European (and global) Carbon Community participation in the GEO system
Vossbeck M.,FastOpt GmbH |
Clerici M.,European Commission - Joint Research Center Ispra |
Kaminski T.,FastOpt GmbH |
Lavergne T.,Norwegian Meteorological Institute |
And 3 more authors.
Inverse Problems | Year: 2010
This paper presents an inverse model of radiation transfer processes occurring in the solar domain in vegetation plant canopies. It uses a gradient method to minimize the misfit between model simulation and observed radiant fluxes plus the deviation from prior information on the unknown model parameters. The second derivative of the misfit approximates uncertainty ranges for the estimated model parameters. In a second step, uncertainties are propagated from parameters to simulated radiant fluxes via the model's first derivative. AU derivative information is provided by a highly efficient code generated via automatic differentiation of the radiative transfer code. The paper further derives and evaluates an approach for avoiding secondary minima of the misfit. The approach exploits the smooth dependence of the solution on the observations, and relies on a database of solutions for a discretized version of the observation space. © 2010 IOP Publishing Ltd.
Knorr W.,University of Bristol |
Kaminski T.,FastOpt GmbH |
Scholze M.,University of Bristol |
Gobron N.,European Commission - Joint Research Center Ispra |
And 3 more authors.
Journal of Geophysical Research: Biogeosciences | Year: 2010
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. Copyright © 2010 by the American Geophysical Union.
Agency: European Commission | Branch: FP7 | Program: CP-FP | Phase: SPA.2013.1.1-03 | Award Amount: 7.00M | Year: 2013
Policy makers are increasingly relying on Earth Observation (EO) data to make decisions on mitigating and adapting to climate change. These decisions need to be evidence-based and this requires complete confidence in EO-derived products. Although EO data is plentiful, it is rare to have reliable, traceable and understandable quality information. The situation is often further confused because various versions of the same product exist from data providers using different retrieval algorithms. Users need an internationally acceptable Quality Assurance (QA) framework that establishes, and provides understandable traceable quality information for the data products used in Climate Services. This will ensure that long-term data sets are historically linked and, in the future, automatically harmonised in an efficient and interoperable manner. The Quality Assurance for ECVs (QA4ECV) project will address these issues by developing a robust generic system for the QA of satellite and in-situ algorithms and data records that can be applied to all ECVs in a prototype for future sustainable services in the frame of the GMES/Copernicus Climate Change Service. Multi-use tools and SI/community reference standards will be developed. The QA4ECV project will generate quality-assured multi-decadal Climate Data Records for 3 atmospheric ECV precursors (NO2, HCHO, and CO) and 3 land ECVs (albedo, LAI, and FAPAR), with full uncertainty metrics for every pixel ready for model ingestion. The generic QA framework will be applied to these ECVs. QA4ECV will engage with all stakeholders, including other ECV projects, governance bodies and end-users, developers of Climate Services and relevant projects. The QA4ECV project will show how trustable assessments of satellite data quality and reliable means of interoperability can facilitate users in judging the fitness-for-purpose of the ECV Climate Data Record. QA4ECV will be a major step forward in providing quality assured long-term Climate Data Records that are relevant for policy and climate change assessments.
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: EO-2-2014 | Award Amount: 5.50M | Year: 2015
FIDUCEO will create new climate datasets from Earth Observations with rigorous treatment of uncertainty informed by the discipline of metrology. This responds to the need for enhanced credibility for climate data, to support rigorous science, decision-making and climate services. Our approach is (1) to develop methodologies for generating Fundamental Climate Data Records (FCDRs) and [Thematic] Climate Data Records (CDRs) that are widely applicable and metrologically rigorous and (2) to build new FCDRs and CDRs, making them easily accessible, with complete and traceable estimates of stability and uncertainty. New tools for metrologically rigorous analysis will be created, including tools for stability analysis and ensemble creation. The chosen FCDRs have a length relevant to climate (>20 years) and can support numerous CDRs. Selected CDRs will be generated that illustrate new capabilities (e.g. equi-probable ensembles) as well as the benefits from use of the new FCDRs, such as improved stability and traceable uncertainties. Specifically, we will create: harmonised radiances (FCDRs) for the following sensors: AVHRR, HIRS, AMSU-B/MHS and MVIRI; and geophysical datasets, with uncertainties, for: ensemble sea and lake surface temperature, tropospheric humidity, aerosol optical depth and surface albedo. All data, software tools and methods will be freely and openly accessible and will be disseminated in a variety of forms including e-learning modules. All data will be available in both a common easy format (for general users) and community-standard formats. FIDUCEO will liaise explicitly with relevant programmes (Copernicus Climate Change Service, NOAA Climate Data Records programme, SCOPE-CM, re-analysis initiatives etc), and hold with two workshops for dialogue with the user community. By both creating valuable datasets and defining and applying rigorous new metrological methods, FIDUCEO aims for a broad and lasting impact in the field of climate data from space.
Rayner P.J.,CEA Saclay Nuclear Research Center |
Koffi E.,CEA Saclay Nuclear Research Center |
Scholze M.,University of Bristol |
Kaminski T.,Fastopt GmbH |
Dufresne J.-L.,University Pierre and Marie Curie
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences | Year: 2011
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 heterotrophic respiration. We show that this uncertainty can be greatly reduced by constraining the model parameters with two decades of atmospheric measurements. © 2011 The Royal Society.
Giering R.,FastOpt GmbH |
Vossbeck M.,FastOpt GmbH
Lecture Notes in Computational Science and Engineering | Year: 2012
We present a new source-to-source transformation which generates code to compute several model instances simultaneously. Due to the increased memory locality of memory accesses this speeds up the computation on processors using a cache hierarchy to overcome the relative slow memory access. The speedup depends on the model code, the processor, the compiler, and on the number of instances. © 2012 Springer-Verlag.
Knorr W.,Lund University |
Kaminski T.,FastOpt GmbH |
Arneth A.,KIT IMK IFU |
Weber U.,Max Planck Institute for Biogeochemistry
Biogeosciences | Year: 2014
Human impact on wildfires, a major earth system component, remains poorly understood. While local studies have found more fires close to settlements and roads, assimilated charcoal records and analyses of regional fire patterns from remote-sensing observations point to a decline in fire frequency with increasing human population. Here, we present a global analysis using three multi-year satellite-based burned-area products combined with a parameter estimation and uncertainty analysis with a non-linear model. We show that at the global scale, the impact of increasing population density is mainly to reduce fire frequency. Only for areas with up to 0.1 people per km2, we find that fire frequency increases by 10 to 20% relative to its value at no population. The results are robust against choice of burned-area data set, and indicate that at only very few places on earth, fire frequency is limited by human ignitions. Applying the results to historical population estimates results in a moderate but accelerating decline of global burned area by around 14% since 1800, with most of the decline since 1950. © Author(s) 2014.
Kemp S.,University of Bristol |
Scholze M.,Lund University |
Ziehn T.,CSIRO |
Kaminski T.,FastOpt GmbH
Geoscientific Model Development | Year: 2014
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. © Author(s) 2014.