WORK PACKAGE 2

WP2: In-situ supersites & Remote Sensing integration

Lead: Helmholtz Geo-Research Center Potsdam (GFZ)

Participating partners: Natural Resources Institute Finland (LUKE), ETH Zurich (ETHZ), University of Zurich (UZH), Swedish University of Agricultural Sciences (SLU), University of Antwerp (UANT), Max Planck Institute for Biogeochemistry (MPI), Euro-Mediterranean Center on Climate Change (CMCC), Gamma Remote Sensing (GAMMA)

• Innovate and integrate novel in situ monitoring approaches for tracking C and hydro-logical dynamics.

• Improved in-situ and space-based data integration: combined site-level data streams with new space-based monitoring sensors from LiDAR, SAR, and hyperspectral sen-sors, and packaging of data streams for uptake in downstream WPs.

• Synthesis, uptake, and recommendations: a systematic analysis, comparison, and de-riving recommendations for future monitoring (i.e. ICOS, Copernicus).

WORK PACKAGE 3 

WP3: Large scale spatial analysis for monitoring key terrestrial ecosystems

Lead: University of Florence (UNIFI)

Participating partners: Karlsruhe Institute of Technology (KIT), Natural Resources Institute Finland (LUKE), Helmholtz Geo-Research Center Potsdam (GFZ), Wageningen University (WU), Swedish University of Agricultural Sciences (SLU), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Wageningen Environmental Research (WENR), Max Planck Institute for Biogeochemistry (MPI), Gamma Remote Sensing (GAMMA)

• To better understand LULC change dynamics and related land management at un-precedented spatial scale.

• Improve spatial and temporal understanding of disturbance and regrowth (D&R) dy-namics, to encompass the heterogeneous thematic parameters, to deliver key quanti-tative detail on GHG fluxes due to D&R.

• To produce annual maps of the CO2 fluxes exchanged between the land and the at-mosphere in response to lateral C transport processes

• To produce new pan-European spatial estimation of C stocks and fluxes-related varia-bles: above &below-ground biomass, including the soil carbon component and coarse woody debris; Net Biome Production (NBP) of forest attributed to gross C losses and gains from disturbances; SIF-based proxy of productivity.

• To produce enhanced pan-European data-driven upscaled NEE from FLUXCOM-X with integration of recent EO data and flux footprint.

WORK PACKAGE 4 

WP4: Vegetation demographics observations and modelling 

Lead: Centre for International Climate Research (CICERO)

Participating partners: Swedish University of Agricultural Sciences (SLU), Helmholtz Geo-Research Center Potsdam (GFZ), University of Exeter (UNEXE), Science Partners (SP), Wageningen Environmental Research (WENR), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)

• Integrate improved methods to monitor key European ecosystem states regarding terrestrial C by assessing size, age structure, and canopy structure using TLS

• Use demographic models and theory to interpret observed tree-size and tree-age dis-tribution

• Harness satellite-derived age class data to inform and constrain C dynamics in a di-verse set of demographic LSMs.

• Increase the accuracy of LSM C cycle representations of forest regrowth via DA and calibration of next-generation demographic schemes

WORK PACKAGE 5 

WP5: Enhanced model representation of anthropogenic & natural disturbances

Lead: Ludwig-Maximilians University Munich (LMU)

Participating partners: Karlsruhe Institute of Technology (KIT), Vrije Universiteit Amsterdam (VUA), Science Partners (SP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Centre for International Climate Research (CICERO), Wageningen Environmental Research (WENR), Natural Resources Institute Finland (LUKE)

• Harmonise land use DA for improved land surface and bookkeeping modelling

• Bridge the gap in spatial resolutions between RS and LSM.

• Improve handling of forest management and wood trade in terrestrial C modelling.

• Improve the representation of peatland GHG fluxes in LSM

• Improve the representation of key land-use processes in bookkeeping models to ob-tain better estimates ofCO2 fluxes from land-use change and land management.

WORK PACKAGE 6 

WP6: Data assimilation developments & model-data fusion

Lead: University of Exeter (UNEXE)

Participating partners: Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Science Partners (SP), Max Planck Institute for Biogeochemistry (MPI), Centre for International Climate Research (CICERO), Swedish University of Agricultural Sciences (SLU), Natural Resources Institute Finland (LUKE), University of Florence (UNIFI), Joint Research Centre (JRC), Vrije Universiteit Amsterdam (VUA)

• Improve the current DA and model-data fusion schemes suitable for multiple data stream assimilation into process-based LSM.

• Develop empirical DA procedures for forest biomass assessment.

• Calibrate the main parameters of several LSMs to provide data-constrained C budgets (consistent short- and long-term fluxes and stocks) and associated parametric uncer-tainties

• Develop new hybrid modelling for maximal observation use in model DA approaches.

• Perform regional atmospheric inversion over Europe using a Community Inversion Framework (CIF).

WORK PACKAGE 7

WP7: GHG budgets, LULUCF reconciliation & synthesis

Lead: Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)

Participating partners: University of Exeter (UNEXE), Max Planck Institute for Biogeochemistry (MPI), Centre for International Climate Research (CICERO), Ludwig-Maximilians University Munich (LMU), Gamma Remote Sensing (GAMMA), Leipzig University (ULEI), Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Wageningen Environmental Research (WENR)

• Apply the enhanced LSMs and bookkeeping models for the GCB assessment and demonstrate a reduction in the global BIM.

• Derive biomass change estimates from EO at a global scale and over multiple decades and compare with LSMs over Europe and globally.

• Apply enhanced LSMs in Near-Real-Time (NRT) to estimate the impact of climate ex-tremes, using high-resolution simulations from WP6 and new coarse-resolution global simulations.

• Synthesise C budget estimates and reconcile C emissions for the LULUCF sector at the country-level over Europe between NGHGI estimates and those from this project.

WORK PACKAGE 8

WP8: Scenario modelling of the carbon cycle

Lead: Leipzig University (ULEI)

Participating partners: International Institute for Applied Systems Analysis (IIASA), Potsdam Institute for Climate Impact Research (PIK), Centre for International Climate Research (CICERO), Science Partners (SP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), University of Exeter (UNEXE), Vrije Universiteit Amsterdam (VUA), Ludwig-Maximilians University Munich (LMU)

• Develop empirically based scenarios extending TRENDY simulations connecting land use and land cover change to C emissions and sequestration potential.

• Quantify changing future likelihoods of extreme events (wind throw, drought, pest outbreaks, fire) and associated impacts on the C cycle

• Quantify dynamics and responses of vegetation to climate change and short- and long-term stress in a range of future scenarios.

WORK PACKAGE 9

WP9: Communication, impact & policy outreach

Lead: Swedish University of Agricultural Sciences (SLU)

Participating partners: All

• Appraise the performance of the NextGenCarbon consortium throughout the dura-tion of the project

• Conduct targeted, effective, high-impact communication, engagement, dissemina-tion and exploitation activities to raise awareness and understanding of multiple audi-ences around impacts of anthropogenic activities and management decisions on cli-mate change

• Support informed decision-making in climate change mitigation and adaptation poli-cies at EU and global levels, in line with the European Green Deal objectives, the EU Climate Law, and the LULUCF Regulation

• Set the pathway to the project’s sustainability through post-project sustainability plan development

WORK PACKAGE 10

WP10: Carbon Carrying Capacity (CCC) Prediction

Lead: Czech University of Life Sciences (CZU)

Participating partners: Swedish University of Agricultural Sciences (SLU), Helmholtz Geo-Research Center Potsdam (GFZ), Gamma Remote Sensing (GAMMA), University of Florence (UNIFI), Wageningen University (WU), Natural Resources Institute Finland (LUKE), Centre for International Climate Research (CICERO)

• To develop Pan-European CCC models by Ecological Zone & Forest Type.

• Generation of pan-European the relative C stocks and SF maps.

• Investigate the underlying environmental constrains that influence the ability of for-ests to reach their maximum CCC

• To create prediction scenarios for the relative C stock.