Periodic Reporting for period 1 - CAMAERA (CAMS AERosol Advancement)
Reporting period: 2024-01-01 to 2025-06-30
The Copernicus Atmosphere Monitoring Service (CAMS, https://atmosphere.copernicus.eu(opens in new window)) combines satellite observations with numerical modelling to provide in near-real time a wealth of information to answer questions related to air quality, climate change and air pollution and its mitigation, energy, agriculture, etc. CAMS provides both global and regional atmospheric composition products.The CAMS AERosol Advancement (CAMAERA) project will provide strong improvements of the aerosol modelling capabilities of the regional and global systems, on the assimilation of new sources of data, and on a better representation of secondary aerosols and their precursor gases. In this way CAMAERA will enhance the quality of key products of the CAMS service and therefore help CAMS to better respond to user needs such as air pollutant monitoring, along with the fulfilment of sustainable development goals. To achieve this purpose CAMAERA will develop new prototype service elements of CAMS, beyond the current state-of-art. It will do so in very close collaboration with the CAMS service providers, as well as other tier-3 projects. In particular, CAMAERA will complement research topics addressed in CAMEO, which focuses on data assimilation and uncertainties.
WP1/WP2 focuses on the data assimilation system of the ECMWF’s Integrated Forecast System for atmospheric composition (IFS-COMPO, the global CAMS system), in order to assimilate new streams of data and for inversion purposes. In WP1, an IFS-COMPO ensemble focusing on desert dust forecasts has been designed and evaluated, for the purpose of carrying out offline dust flux emission optimisation using Kalman smoothing. A dataset of 5 years of daily best estimate dust emissions has been produced. Simulations using these scaled emissions have been performed and showed some improvement in the skill of dust related products. An observation operator has been developed for the extinction and backscatter at 910nm, which is a wavelength impacted by water vapour. Assimilation of e-profile data using spherical or spheroid assumed shape for desert dust particles have been carried out over periods of 3 months. The assimilation of lidar/ceilometer data improves on the simulated extinction profiles, particularly in the case of biomass burning or desert dust plumes. However, the impact on the skill of simulated AOD and PM is more mixed.
WP3/WP4 aims to implement a modal approach to represent aerosol species and processes in IFS-COMPO, building on model developments in OpenIFS, as initiated in the EC-Earth context. The fields that contain the M7 tracers have been set up in IFS-COMPO, and the treatment of emissions in a modal aerosol context has been implemented. First technical runs with the M7 module as part of IFS-COMPO have been performed. Secondly, the mass emissions pre-processing has been modified to include information on particle size distribution and properly pass on the information of number density. A working version of IFS-M7 has been established, and first output of simulated Aerosol Optical Depth (AOD) has been achieved. The coupling with the thermodynamical module EQSAM4Clim has been established, which will allow for the production of ammonium nitrate from gaseous precursors. This is an extension to the original formulation of the M7 modal scheme, which doesn't include nitrate.
WP5/WP6 focuses on online emissions and deposition: the work on new desert dust and sea-salt emission schemes as well as on dry deposition falls in this work package. A new desert dust emission scheme has been developed, implemented in SILAM, and evaluated over an extended time period of several years showing very good skills. The formulations have been provided to ECMWF, adapted and implemented in IFS-COMPO, and preliminarily evaluations have been shown superior scores compared to the existing IFS-COMPO dust emission scheme. Deep learning methods and machine learning methods have been applied to ocean and meteorological parameters to estimate whitecap fraction, using a two-year dataset of whitecap fraction from remote sensing. The possibility to use inference models in IFS-COMPO has been implemented through the ECMWF INFERO library, and IFS-COMPO simulations using a deep learning estimate of whitecap fraction have been carried out. The 0D dry deposition intercomparison included contributions from the global system and 5 regional systems: the results have been analyzed and disseminated to all CAMAERA partners. Specific developments relating to the treatment of high latitude dust for both the new and the current operational dust emission scheme have been carried out and tested, focusing on Iceland.
WP7/WP8 focuses on the representation of secondary organic aerosols, as well as that of primary biogenic particles. A first analysis of land cover and emission potential maps for Biogenic Volatile Organic Compounds (BVOCs) has been performed, along with an investigation of the importance of different contributions to the activity factor, which, in combination, defines the emissions. In order to improve understanding of the SOA formation from anthropogenic VOC, we compared different strategies to treat the semi-volatility and aging of POA. Pilot simulations have been performed with the CHIMERE model. Three different source parameterizations for fungal spores have been implemented in the EMEP and IFS-COMPO model and the results have been compared to arabitol and mannitol measurements across Europe as well as to total PM10 observations - showing improved bias (and to some extent also correlation).
WP9/WP10 focuses on the interface and intercomparison of the global and regional CAMS systems. The CAMS global and regional anthropogenic emission maps have been merged so as to allow simulations using the CAMS global system (IFS-COMPO) using CAMS regional emissions. IFS-COMPO simulations have been carried out using global and regional emissions, at a lower and higher resolution, in order to be fully comparable to simulations from the regional models. A full intercomparison of the PM simulated by the global system and 8 regional systems have been carried out.
WP3/WP4 aims to implement a modal approach to represent aerosol species and processes in IFS-COMPO, building on model developments in OpenIFS, as initiated in the EC-Earth context. The fields that contain the M7 tracers have been set up in IFS-COMPO, and the treatment of emissions in a modal aerosol context has been implemented. First technical runs with the M7 module as part of IFS-COMPO have been performed. Secondly, the mass emissions pre-processing has been modified to include information on particle size distribution and properly pass on the information of number density. A working version of IFS-M7 has been established, and first output of simulated Aerosol Optical Depth (AOD) has been achieved. The coupling with the thermodynamical module EQSAM4Clim has been established, which will allow for the production of ammonium nitrate from gaseous precursors. This is an extension to the original formulation of the M7 modal scheme, which doesn't include nitrate.
WP5/WP6 focuses on online emissions and deposition: the work on new desert dust and sea-salt emission schemes as well as on dry deposition falls in this work package. A new desert dust emission scheme has been developed, implemented in SILAM, and evaluated over an extended time period of several years showing very good skills. The formulations have been provided to ECMWF, adapted and implemented in IFS-COMPO, and preliminarily evaluations have been shown superior scores compared to the existing IFS-COMPO dust emission scheme. Deep learning methods and machine learning methods have been applied to ocean and meteorological parameters to estimate whitecap fraction, using a two-year dataset of whitecap fraction from remote sensing. The possibility to use inference models in IFS-COMPO has been implemented through the ECMWF INFERO library, and IFS-COMPO simulations using a deep learning estimate of whitecap fraction have been carried out. The 0D dry deposition intercomparison included contributions from the global system and 5 regional systems: the results have been analyzed and disseminated to all CAMAERA partners. Specific developments relating to the treatment of high latitude dust for both the new and the current operational dust emission scheme have been carried out and tested, focusing on Iceland.
WP7/WP8 focuses on the representation of secondary organic aerosols, as well as that of primary biogenic particles. A first analysis of land cover and emission potential maps for Biogenic Volatile Organic Compounds (BVOCs) has been performed, along with an investigation of the importance of different contributions to the activity factor, which, in combination, defines the emissions. In order to improve understanding of the SOA formation from anthropogenic VOC, we compared different strategies to treat the semi-volatility and aging of POA. Pilot simulations have been performed with the CHIMERE model. Three different source parameterizations for fungal spores have been implemented in the EMEP and IFS-COMPO model and the results have been compared to arabitol and mannitol measurements across Europe as well as to total PM10 observations - showing improved bias (and to some extent also correlation).
WP9/WP10 focuses on the interface and intercomparison of the global and regional CAMS systems. The CAMS global and regional anthropogenic emission maps have been merged so as to allow simulations using the CAMS global system (IFS-COMPO) using CAMS regional emissions. IFS-COMPO simulations have been carried out using global and regional emissions, at a lower and higher resolution, in order to be fully comparable to simulations from the regional models. A full intercomparison of the PM simulated by the global system and 8 regional systems have been carried out.
While most of the work in the project is still in progress, some first results already move beyond the state of the art.
The first use of offline trained machine learning models in IFS-COMPO through the INFERO library is a ground breaking development that open many possibilities in atmospheric composition modelling within CAMS and outside. The technical infrastructure developed in this task will be used again for many other parts of IFS-COMPO in the coming years, starting with dust emissions through ML techniques in WP6.
The implementation of a new fungal spores species in the EMEP and IFS-COMPO systems are still very experimental developments. Nonetheless, they pave the way for a possible extension of the CAMS product portfolio as these developments, once their added value is established, are transferred into CAMS.
The first use of offline trained machine learning models in IFS-COMPO through the INFERO library is a ground breaking development that open many possibilities in atmospheric composition modelling within CAMS and outside. The technical infrastructure developed in this task will be used again for many other parts of IFS-COMPO in the coming years, starting with dust emissions through ML techniques in WP6.
The implementation of a new fungal spores species in the EMEP and IFS-COMPO systems are still very experimental developments. Nonetheless, they pave the way for a possible extension of the CAMS product portfolio as these developments, once their added value is established, are transferred into CAMS.