Periodic Reporting for period 2 - CONFESS (Consistent representation of temporal variations of boundary forcings in reanalyses and seasonal forecasts)
Periodo di rendicontazione: 2021-11-01 al 2024-03-31
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 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.
CONFESS has provided a meeting point between weather and climate and between different Copernicus Services. In particular, it has exploited datasets and modelling capabilities from CAMS and CEMS to improve our understanding on the impact of variations of land properties and atmospheric composition in seasonal forecast. Results showed that the temporal variations of vegetation affect the representation of trends in the seasonal reforecast, and impact the amplitude of heat waves. Results indicate that the land-atmospheric processes varies largely among models, and there is need to further improve the land-atmosphere coupling. The multi-decadal CONFESS tropospheric aerosols temporal records were estimated from the latest aersols model from CAMS, the ERA5 atmospheric forcing and the latest aerosol emissions (likely to be used in CMIP7). These records will be used in the production of ERA6 and the upcoming ECMWF seasonal forecasting system SEAS6. CONFESS has also enabled the comparison of different stratospheric volcanic dispersion models, allowing the comparison in a multi-model framework, in both seasonal and decadal predictions. The project has also showcased the impact assessment of large biomass burning emissions in selected case studies.
CONFESS 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.
CONFESS has provided a meeting point between weather and climate and between different Copernicus Services. In particular, it has exploited datasets and modelling capabilities from CAMS and CEMS to improve our understanding on the impact of variations of land properties and atmospheric composition in seasonal forecast. Results showed that the temporal variations of vegetation affect the representation of trends in the seasonal reforecast, and impact the amplitude of heat waves. Results indicate that the land-atmospheric processes varies largely among models, and there is need to further improve the land-atmosphere coupling. The multi-decadal CONFESS tropospheric aerosols temporal records were estimated from the latest aersols model from CAMS, the ERA5 atmospheric forcing and the latest aerosol emissions (likely to be used in CMIP7). These records will be used in the production of ERA6 and the upcoming ECMWF seasonal forecasting system SEAS6. CONFESS has also enabled the comparison of different stratospheric volcanic dispersion models, allowing the comparison in a multi-model framework, in both seasonal and decadal predictions. The project has also showcased the impact assessment of large biomass burning emissions in selected case studies.
Radiative forcing, land cover/use and vegetation are prescribed as boundary conditions in reanalyses and subseasonal–seasonal–decadal integrations. Their temporal variability impacts the solution. There are new high-accuracy observational datasets for the recent period (the last 20–30 years), which are not yet used in reanalyses and re-forecasts. To facilitate the seamless approach, there is a need to create time-varying records which are consistent with those used in operational medium-range prediction. There is also a need to find the best and converging practices between the operational centres providing reanalyses and seasonal forecasts and the wider climate community. These have been the motivations for the activities in the Horizon 2020 project CONFESS (https://confess-h2020.eu/(si apre in una nuova finestra)). CONFESS aimed to improve the representation of global trends and regional extremes in the next generation of Earth system reanalyses and seasonal forecasts made available by the EU-funded Copernicus Climate Change Service (C3S) implemented by ECMWF. It has done so by taking stock of observational datasets and model developments across different Copernicus Services on vegetation, land cover, atmospheric composition and biomass burning.
The achievements of CONFESS have been possible thanks to the engagement and expertise of the project partners: Météo-France, ECMWF, Italy’s Institute of Atmospheric Sciences and Climate (CNR-ISAC), and the Barcelona Supercomputing Center (BSC).
Land cover/use and leaf area index
CONFESS has managed to identify and harmonise different datasets of land use/land cover (LULC) and leaf area index (LAI). The implementation of these datasets in different models has allowed coordinated experimentation in a multi-model framework, resulting in the quantitative assessment, for the first time, of the impact of time-varying land properties in multi-year land simulations and coupled seasonal and decadal forecasts. The multi-model assessment has indicated that time-varying land properties, especially vegetation, have a significant impact on trends, skill and extremes. However, the impact is highly dependent on the model, and there is a further need to quantify and constrain the land–atmospheric feedbacks. Therefore, the time-varying land properties will not be included in ECMWF’s next reanalysis, ERA6, or in its next seasonal forecasting system, SEAS6. They are, however, a key component of further developments for ERA6-land and ERA7. The most recent period of the CONFESS LULC and LAI datasets, treated as a fixed climatology, has proved beneficial for numerical weather prediction. It will be implemented in the next operational cycle of ECMWF’s Integrated Forecasting System (IFS), Cycle 49r1, and will therefore be inherited by ERA6 and SEAS6. CONFESS has enabled progress with the modelling of prognostic vegetation (Météo-France) and improved parameterization of fractional vegetation cover (Italian National Research Council -CNR). For these efforts, the CONFESS LAI has also been used to evaluate the quality of the new prognostic capabilities.
Tropospheric aerosols
CONFESS has also enabled a major step in the treatment of time-varying tropospheric aerosols, by merging the capabilities for the EU-funded Copernicus Atmosphere Monitoring Service (CAMS) implemented by ECMWF, the C3S reanalysis ERA5, and the latest repository of tropospheric aerosol emissions (an update to CMIP6, likely to be used in CMIP7). The aerosol optical properties in ECMWF’s IFS have also been revised. This new dataset will be implemented in IFS Cycle 49r2, to be used in ERA6 and SEAS6. Having an up-to-date aerosol climatology that is consistent with the latest CAMS aerosols also helps us to explore the impact of interactive aerosols on numerical weather prediction.
The achievements of CONFESS have been possible thanks to the engagement and expertise of the project partners: Météo-France, ECMWF, Italy’s Institute of Atmospheric Sciences and Climate (CNR-ISAC), and the Barcelona Supercomputing Center (BSC).
Land cover/use and leaf area index
CONFESS has managed to identify and harmonise different datasets of land use/land cover (LULC) and leaf area index (LAI). The implementation of these datasets in different models has allowed coordinated experimentation in a multi-model framework, resulting in the quantitative assessment, for the first time, of the impact of time-varying land properties in multi-year land simulations and coupled seasonal and decadal forecasts. The multi-model assessment has indicated that time-varying land properties, especially vegetation, have a significant impact on trends, skill and extremes. However, the impact is highly dependent on the model, and there is a further need to quantify and constrain the land–atmospheric feedbacks. Therefore, the time-varying land properties will not be included in ECMWF’s next reanalysis, ERA6, or in its next seasonal forecasting system, SEAS6. They are, however, a key component of further developments for ERA6-land and ERA7. The most recent period of the CONFESS LULC and LAI datasets, treated as a fixed climatology, has proved beneficial for numerical weather prediction. It will be implemented in the next operational cycle of ECMWF’s Integrated Forecasting System (IFS), Cycle 49r1, and will therefore be inherited by ERA6 and SEAS6. CONFESS has enabled progress with the modelling of prognostic vegetation (Météo-France) and improved parameterization of fractional vegetation cover (Italian National Research Council -CNR). For these efforts, the CONFESS LAI has also been used to evaluate the quality of the new prognostic capabilities.
Tropospheric aerosols
CONFESS has also enabled a major step in the treatment of time-varying tropospheric aerosols, by merging the capabilities for the EU-funded Copernicus Atmosphere Monitoring Service (CAMS) implemented by ECMWF, the C3S reanalysis ERA5, and the latest repository of tropospheric aerosol emissions (an update to CMIP6, likely to be used in CMIP7). The aerosol optical properties in ECMWF’s IFS have also been revised. This new dataset will be implemented in IFS Cycle 49r2, to be used in ERA6 and SEAS6. Having an up-to-date aerosol climatology that is consistent with the latest CAMS aerosols also helps us to explore the impact of interactive aerosols on numerical weather prediction.
Hazardous events
The activities in CONFESS have also made steps towards enabling prediction and monitoring systems to react to hazardous events, such as large volcanic eruptions and biomass burning. A new model for volcanic stratospheric aerosols (EVA_H) has been implemented in the IFS. This made it necessary to revise the aerosol optical properties. The EVA_H model has been thoroughly evaluated in seasonal and decadal forecasts, and it will be used in SEAS6 re-forecasts. The performance of the EVA_H and EVA and their impact on the climate has been thoroughly evaluated in decadal forecasts, following coordinated experimentation. It has also been possible to quantify the impact of large biomass burning emissions in sub-seasonal and seasonal forecasts. The results, based on experimentation with prognostic aerosols in the IFS targeting three case studies, show that although there is a noticeable impact on predictions of local surface temperature, the amplitude is modest and it does not alter the large-scale atmospheric circulation. But this work was done before revising the IFS aerosol optical properties, and it should be repeated with more recent upgrade Cycles.
The activities in CONFESS have also made steps towards enabling prediction and monitoring systems to react to hazardous events, such as large volcanic eruptions and biomass burning. A new model for volcanic stratospheric aerosols (EVA_H) has been implemented in the IFS. This made it necessary to revise the aerosol optical properties. The EVA_H model has been thoroughly evaluated in seasonal and decadal forecasts, and it will be used in SEAS6 re-forecasts. The performance of the EVA_H and EVA and their impact on the climate has been thoroughly evaluated in decadal forecasts, following coordinated experimentation. It has also been possible to quantify the impact of large biomass burning emissions in sub-seasonal and seasonal forecasts. The results, based on experimentation with prognostic aerosols in the IFS targeting three case studies, show that although there is a noticeable impact on predictions of local surface temperature, the amplitude is modest and it does not alter the large-scale atmospheric circulation. But this work was done before revising the IFS aerosol optical properties, and it should be repeated with more recent upgrade Cycles.