Periodic Reporting for period 1 - CONFESS (Consistent representation of temporal variations of boundary forcings in reanalyses and seasonal forecasts)
Période du rapport: 2020-11-01 au 2021-10-31
The aim of CONFESS is to improve the reliability and usability of C3S information in the land-atmosphere coupled system by exploiting new and improved Earth Observations data records of land-use, vegetation states and surface-emitted aerosols delivered across different Copernicus Services. CONFESS developments will be integrated consistently for use in future C3S systems, enhancing the service’s accuracy by representing annual changes of land use, adding satellite-derived and prognostic vegetation states along with aerosols emissions due to hazardous/extreme events such as volcanic eruptions and large-scale biomass burning (e.g. wildfires). The added capacity to represent temporal variations and trends of these variables and the occurrence of hazardous/ extreme events will be supported by a rapid uptake of new Earth Observations. The impact on the Earth system will be evaluated on the quality of global reanalysis as well as seasonal forecasts using state-of-the-art modelling systems. The infrastructure and knowledge developed within CONFESS will contribute to improve the C3S capabilities for reliable monitoring and forecasting with particular focus on extremes.
By exploitation of improved observational records delivered across different Copernicus Services, CONFESS will improve the C3S capabilities for monitoring and predicting extreme events and produce reliable climate trends, it will increase the relevance of the services to represent hazardous events and their impact, and it will prepare the ground for rapid uptake of new observations. This will be achieved by enabling a consistent representation of the temporal variability of chemical and biological elements of land surface state and atmospheric composition in future C3S reanalyses and seasonal forecasting systems, by taking stock of the latest harmonized data sets and further inclusion of prognostic models for these new earth system components.
CONFESS strategic objectives are:
1. Representation, for the first time, of temporal variations of land cover and vegetation in C3S systems by exploiting state of the art Copernicus observational datasets
2. Improved temporal representation of tropospheric aerosols by harmonization of CMIP6 and CAMS datasets.
3. Increased prognostic capabilities by inclusion of prognostic vegetation and new capabilities for response to volcanic and biomass burning emissions.
By exploitation of improved observational records delivered across different Copernicus Services, CONFESS will improve the C3S capabilities for monitoring and predicting extreme events and produce reliable climate trends, it will increase the relevance of the services to represent hazardous events and their impact, and it will prepare the ground for rapid uptake of new observations. This will be achieved by enabling a consistent representation of the temporal variability of chemical and biological elements of land surface state and atmospheric composition in future C3S reanalyses and seasonal forecasting systems, by taking stock of the latest harmonized data sets and further inclusion of prognostic models for these new earth system components.
CONFESS strategic objectives are:
1. Representation, for the first time, of temporal variations of land cover and vegetation in C3S systems by exploiting state of the art Copernicus observational datasets
2. Improved temporal representation of tropospheric aerosols by harmonization of CMIP6 and CAMS datasets.
3. Increased prognostic capabilities by inclusion of prognostic vegetation and new capabilities for response to volcanic and biomass burning emissions.
The following presents an overview of main results in the first period.
WP1
• A harmonized observational Leaf Area Index (LAI) dataset covering the 1993-2019 period has been finalized and disseminated to CONFESS partners.
• The Land Use / Land Cover (LULC) dataset has been adapted to IFS Vegetation Types and shared with partners
• The FCover dataset has been retrieved and finalized to support modelling in task 1.2 and 1.3.
• Annual maps of LULC derived from LUH2 have been produced consistently with SURFEX plant functional types
• Vegetation and atmospheric input (ERA5 hourly forcing) have been prepared separately for each partner.
• A list of land model output (variables, frequency) has been agreed and shared between partners.
• Performed a historical land-only simulation with interactive vegetation.
WP2
• A new approach has been developed to derive a new version of the CAMS aerosol climatology, using the latest IFS version with full chemistry and aerosol, and including 14 aerosol types.
• A new climatology will be derived over a multi-decadal period to allow the creation of a time-varying climatology, to obtain both a more accurate representation of the present -day climatology, and a much more accurate representation of the time-evolution at a regional scale.
• A test-suite for this new approach has been successfully implemented.
• A climatology was created from the Global Fire Assimilation System (GFAS) developed and maintained by CAMS, which is due to be made available in the Atmosphere Data Store.
• Observed emissions from GFAS are already implemented in the IFS ENS which will be used to carry out the experiments.
WP3
• The experimental protocol for the experiments in WP3 has been developed, covering all the experiments in the WP (Tasks 1, 2 and 3).
• Production of re-forecasts with prescribed changes in land surface conditions will start in the second year of the project.
WP4
• Project management structure has been set up
• The kick-off meeting was organised virtually, with an open General Assembly being prepared to be held virtually on 1st December 2021.
• The project website D4.2 has been developed and is being maintained with regular news items and updates.
WP1
• A harmonized observational Leaf Area Index (LAI) dataset covering the 1993-2019 period has been finalized and disseminated to CONFESS partners.
• The Land Use / Land Cover (LULC) dataset has been adapted to IFS Vegetation Types and shared with partners
• The FCover dataset has been retrieved and finalized to support modelling in task 1.2 and 1.3.
• Annual maps of LULC derived from LUH2 have been produced consistently with SURFEX plant functional types
• Vegetation and atmospheric input (ERA5 hourly forcing) have been prepared separately for each partner.
• A list of land model output (variables, frequency) has been agreed and shared between partners.
• Performed a historical land-only simulation with interactive vegetation.
WP2
• A new approach has been developed to derive a new version of the CAMS aerosol climatology, using the latest IFS version with full chemistry and aerosol, and including 14 aerosol types.
• A new climatology will be derived over a multi-decadal period to allow the creation of a time-varying climatology, to obtain both a more accurate representation of the present -day climatology, and a much more accurate representation of the time-evolution at a regional scale.
• A test-suite for this new approach has been successfully implemented.
• A climatology was created from the Global Fire Assimilation System (GFAS) developed and maintained by CAMS, which is due to be made available in the Atmosphere Data Store.
• Observed emissions from GFAS are already implemented in the IFS ENS which will be used to carry out the experiments.
WP3
• The experimental protocol for the experiments in WP3 has been developed, covering all the experiments in the WP (Tasks 1, 2 and 3).
• Production of re-forecasts with prescribed changes in land surface conditions will start in the second year of the project.
WP4
• Project management structure has been set up
• The kick-off meeting was organised virtually, with an open General Assembly being prepared to be held virtually on 1st December 2021.
• The project website D4.2 has been developed and is being maintained with regular news items and updates.
1. Land
The unprecedented vegetation global-scale information that is being provided by the latest satellite campaigns in the frame of Copernicus will be integrated in the land surface models used for reanalysis and initialization of the seasonal prediction systems. The variability of vegetation properties such as leaf density, green vegetation cover and types of land cover will be considered in the land models based on both EO and new prognostic parametrization of the vegetation dynamics, therefore allowing to go beyond the current limitations of analysis/short term predictions over the affected land regions.
One ambition of CONFESS is to contribute in closing the gap between models used for short-term climate prediction and the latest developments of Earth System Models used for climate-change research (CMIP6 framework) that is believed to considerably limit the current level of performance and usefulness of seasonal predictions.
Two strategies for modelling vegetation variability are possible, and this project will help decide which is the more suited to representing the water, carbon and energy fluxes between the land and the atmosphere. One consists in prescribing observed LAI. This approach allows to correct model biases in vegetation mean state and variability. The other strategy is to consider the dynamic evolution of the vegetation through a prognostic parametrisation of LAI. The modelled vegetation may remain biased but it can evolve consistently with simulated environment variables impacting the vegetation phenology (soil moisture, incoming radiation, temperature).
2. Tropospheric Aerosols and biomass burning
Improved representation of aerosol forcings will contribute to improvements in accuracy of long-term trends and low frequency variability in reanalyses and seasonal forecast systems, without incurring the additional costs and complexity of full aerosol and emission modelling. Although small in absolute terms, the improvements are important because they will enable a more accurate calibration of the climate change signal in seasonal forecasts, and more consistent estimations of the earth energy balance in reanalysis.
3. Stratospheric volcanic aerosols
The implementation of the FVF methodology and CMIP volcanic aerosol datasets in the IFS will bring that model up to the state-of-the-art for specifying observed volcanic aerosol properties for past events - this is all that is needed for re-analyses of the past. It would also allow, if desired, seasonal re-forecasts to be run with a more accurate specification of past stratospheric states.
The unprecedented vegetation global-scale information that is being provided by the latest satellite campaigns in the frame of Copernicus will be integrated in the land surface models used for reanalysis and initialization of the seasonal prediction systems. The variability of vegetation properties such as leaf density, green vegetation cover and types of land cover will be considered in the land models based on both EO and new prognostic parametrization of the vegetation dynamics, therefore allowing to go beyond the current limitations of analysis/short term predictions over the affected land regions.
One ambition of CONFESS is to contribute in closing the gap between models used for short-term climate prediction and the latest developments of Earth System Models used for climate-change research (CMIP6 framework) that is believed to considerably limit the current level of performance and usefulness of seasonal predictions.
Two strategies for modelling vegetation variability are possible, and this project will help decide which is the more suited to representing the water, carbon and energy fluxes between the land and the atmosphere. One consists in prescribing observed LAI. This approach allows to correct model biases in vegetation mean state and variability. The other strategy is to consider the dynamic evolution of the vegetation through a prognostic parametrisation of LAI. The modelled vegetation may remain biased but it can evolve consistently with simulated environment variables impacting the vegetation phenology (soil moisture, incoming radiation, temperature).
2. Tropospheric Aerosols and biomass burning
Improved representation of aerosol forcings will contribute to improvements in accuracy of long-term trends and low frequency variability in reanalyses and seasonal forecast systems, without incurring the additional costs and complexity of full aerosol and emission modelling. Although small in absolute terms, the improvements are important because they will enable a more accurate calibration of the climate change signal in seasonal forecasts, and more consistent estimations of the earth energy balance in reanalysis.
3. Stratospheric volcanic aerosols
The implementation of the FVF methodology and CMIP volcanic aerosol datasets in the IFS will bring that model up to the state-of-the-art for specifying observed volcanic aerosol properties for past events - this is all that is needed for re-analyses of the past. It would also allow, if desired, seasonal re-forecasts to be run with a more accurate specification of past stratospheric states.