Periodic Reporting for period 1 - CAMEO (CAMS EvOlution)
Période du rapport: 2023-01-01 au 2024-06-30
Monitoring the composition of the atmosphere is a key objective of the European Union’s flagship Space programme Copernicus with the Copernicus Atmosphere Monitoring Service (CAMS) providing free and continuous data and information on atmospheric composition. The CAMS data products and services are essential to meet policy needs such as air pollution and greenhouse gases monitoring, the fulfilment of sustainable development goals, and sustainable and clean energy at the European and global scale.
The CAMS Service Evolution (CAMEO) project will contribute to the medium- to long-term evolution of CAMS a) by advancing the utilization of satellite observations and b) by providing quantitative uncertainty information of the CAMS products.
CAMEO will help prepare the global and regional CAMS production systems for the uptake of forthcoming satellite data, such as Sentinel-4, Sentinel-5 and 3MI, and advance the aerosol and trace gas data assimilation methods and the emission optimization capacity.
CAMEO will develop different methods to provide uncertainty information about CAMS products such as emissions inventories, policy support tools and solar radiation and deposition products using different methods and observations while considering the specific requirement of the users.
The transfer of developments from CAMEO into subsequent improvements of CAMS operational service elements is a main driver for the project and is the main pathway to impact for CAMEO.
The CAMS Service Evolution (CAMEO) project will contribute to the medium- to long-term evolution of CAMS a) by advancing the utilization of satellite observations and b) by providing quantitative uncertainty information of the CAMS products.
CAMEO will help prepare the global and regional CAMS production systems for the uptake of forthcoming satellite data, such as Sentinel-4, Sentinel-5 and 3MI, and advance the aerosol and trace gas data assimilation methods and the emission optimization capacity.
CAMEO will develop different methods to provide uncertainty information about CAMS products such as emissions inventories, policy support tools and solar radiation and deposition products using different methods and observations while considering the specific requirement of the users.
The transfer of developments from CAMEO into subsequent improvements of CAMS operational service elements is a main driver for the project and is the main pathway to impact for CAMEO.
In WP1, the technical infrastructure to assimilate aerosol reflectance observations with ECMWF’s Integrated Forecasting System (IFS) has been implemented. Off-line observation operators for aerosol optical depth (AOD), single scattering albedo (SSA) and asymmetry parameter have been developed and their result successfully checked against IFS data. The retrieval algorithm of GRASP has been reviewed taking the specifics of the aerosol modelling in the global CAMS model into account, and a 3MI proxy data set based on POLDER observations has been compiled.
In WP2, a major achievement is the technical implementation of the assimilation of retrievals from the geostationary instrument GEMS in preparation of the assimilation of Sentinel-4 and TEMPO retrievals. A new super-observation software has been tested to reduce the large data volumes of satellite retrievals while retaining the information content and representative error characteristics. Major steps towards the inversion of biogenic isoprene emissions using formaldehyde satellite retrievals have been made by developing a simplified isoprene chemistry scheme. ECMWF’s weak constraint 4D-Var system has been extended to be applied for the assimilation of retrievals of stratospheric ozone.
As result of WP3, SO2 retrievals from Sentinel 5P can now be assimilated by several regional CAMS models, and the assimilation of CO and Formaldehyde retrievals is being prepared. For the European domain the ground-based E-lidar network, a valuable resource of vertically resolved aerosol observations, has been assimilated in the CHIMERE model as part of CAMEO. The assimilation of future Sentinel-4 NO2 retrievals as well as NH3 observations from IRS-MTG is being tested by compiling and assimilating synthetic retrievals from a reference model simulation.
In WP4, extending the data bases of quality-assured observation for surface radiation and deposition of dust, nitrogen and sulphate compounds was a major achievement. A data-driven approach was developed to identify and correct contributors of uncertainty to the CAMS solar radiation products such as cloud information. The CAMS deposition products were analyzed with focus on dust deposition over the ocean and on soiling for solar energy facilities.
In WP5, uncertainty estimates of the primary PM emissions at the regional scale, NOx emissions from road transport at the global scale and global biogenic VOC emissions were produced together with the uncertainty information of the temporal profiles of the anthropogenic emissions. A framework for the evaluation and quality control of emission inversion products for CH4 and NOx was developed based on the comparison of various inventory data and inversion results. For CH4, the efforts were focused on coal, oil and gas extraction basins.
In WP6, the focus was put on the impact of non-linear chemistry, model resolution and city area definition on source-receptor modelling. Preliminary results to identify the contribution of meteorology, the modelling approach, the initial conditions, the emissions to uncertainties of CAMS global forecasts have been derived using an ensemble framework.
In WP2, a major achievement is the technical implementation of the assimilation of retrievals from the geostationary instrument GEMS in preparation of the assimilation of Sentinel-4 and TEMPO retrievals. A new super-observation software has been tested to reduce the large data volumes of satellite retrievals while retaining the information content and representative error characteristics. Major steps towards the inversion of biogenic isoprene emissions using formaldehyde satellite retrievals have been made by developing a simplified isoprene chemistry scheme. ECMWF’s weak constraint 4D-Var system has been extended to be applied for the assimilation of retrievals of stratospheric ozone.
As result of WP3, SO2 retrievals from Sentinel 5P can now be assimilated by several regional CAMS models, and the assimilation of CO and Formaldehyde retrievals is being prepared. For the European domain the ground-based E-lidar network, a valuable resource of vertically resolved aerosol observations, has been assimilated in the CHIMERE model as part of CAMEO. The assimilation of future Sentinel-4 NO2 retrievals as well as NH3 observations from IRS-MTG is being tested by compiling and assimilating synthetic retrievals from a reference model simulation.
In WP4, extending the data bases of quality-assured observation for surface radiation and deposition of dust, nitrogen and sulphate compounds was a major achievement. A data-driven approach was developed to identify and correct contributors of uncertainty to the CAMS solar radiation products such as cloud information. The CAMS deposition products were analyzed with focus on dust deposition over the ocean and on soiling for solar energy facilities.
In WP5, uncertainty estimates of the primary PM emissions at the regional scale, NOx emissions from road transport at the global scale and global biogenic VOC emissions were produced together with the uncertainty information of the temporal profiles of the anthropogenic emissions. A framework for the evaluation and quality control of emission inversion products for CH4 and NOx was developed based on the comparison of various inventory data and inversion results. For CH4, the efforts were focused on coal, oil and gas extraction basins.
In WP6, the focus was put on the impact of non-linear chemistry, model resolution and city area definition on source-receptor modelling. Preliminary results to identify the contribution of meteorology, the modelling approach, the initial conditions, the emissions to uncertainties of CAMS global forecasts have been derived using an ensemble framework.
While most of the work in the project is still in progress, some first results already move beyond the state of the art.
Examples are the proxy-3MI aerosol retrievals prepared for the global CAMS-model, the application of weak-constrained 4dVAR for stratospheric ozone, the successful assimilation of e- lidar data with the CAMS regional models, a data-driven approach to attribute and correct errors of the CAMS solar radiation products, the systematic evaluation of CH4 emission inversion products and the use of an ensemble approach to quantify the different contributions to uncertainty of the global CAMS forecast.
Examples are the proxy-3MI aerosol retrievals prepared for the global CAMS-model, the application of weak-constrained 4dVAR for stratospheric ozone, the successful assimilation of e- lidar data with the CAMS regional models, a data-driven approach to attribute and correct errors of the CAMS solar radiation products, the systematic evaluation of CH4 emission inversion products and the use of an ensemble approach to quantify the different contributions to uncertainty of the global CAMS forecast.