Periodic Reporting for period 1 - CERISE (CopERnIcus climate change Service Evolution)
Período documentado: 2023-01-01 hasta 2023-12-31
The aim of CERISE is to develop new and innovative coupled land-atmosphere data assimilation approaches and land initialisation techniques to pave the way for the next generations of the C3S reanalysis and seasonal prediction systems. These developments will be combined with innovative work on observation operator developments integrating Artificial Intelligence (AI) to ensure optimal data fusion fully integrated in coupled assimilation systems. CERISE will drastically enhance the exploitation of past, current, and future Earth system observations over land surfaces, including from the Copernicus Sentinels. In addition, CERISE will provide the proof of concept to demonstrate the feasibility of the integration of the developed approaches in the core C3S (operational Service), with the delivery of reanalysis prototype datasets (demonstrated in pre-operational environment), and seasonal prediction demonstrator datasets (demonstrated in relevant environment). The CERISE outputs aim at medium to long-term upgrades of the C3S systems with targeted progressive implementation in the project duration. The project will improve the quality and consistency of the C3S reanalysis systems and of the components of the seasonal prediction multi-system, directly addressing the evolving user needs for improved and more consistent C3S Earth system products.
The overarching objectives of the project are:
• Development of land-atmosphere coupled data assimilation to improve the climate consistency of the next generation of C3S Earth system reanalyses,
• Enhancement of the quality of user-relevant seasonal forecast information by improving forecast skill and process understanding over land,
• Demonstration of the proof of concept by delivering global and regional reanalysis prototype datasets and seasonal forecast demonstrator datasets showing the feasibility and the added value of the integration in the existing core service.
The overarching objectives of the project are:
• Development of land-atmosphere coupled data assimilation to improve the climate consistency of the next generation of C3S Earth system reanalyses,
• Enhancement of the quality of user-relevant seasonal forecast information by improving forecast skill and process understanding over land,
• Demonstration of the proof of concept by delivering global and regional reanalysis prototype datasets and seasonal forecast demonstrator datasets showing the feasibility and the added value of the integration in the existing core service.
Overall, in this first 12 months, the project has started well and is on track to achieve its scientific aims and to fulfil its objectives.
With the initial phase just completed, CERISE has already several tangible results in the first 12 months of the project.
Development and implementation of ensemble perturbation methods for land-surface assimilation systems and assessment in both the regional and global data assimilation systems has been achieved (WP1), successfully completing M1, and the results documented in D1.1.
We have conducted infrastructure developments in the global and regional data assimilation systems as part of WP2, with enhanced consistency between the coupled and offline land data assimilation approaches and increased code efficiency for outer loop coupling.
Our work in WP3 resulted in our first comparison of existing C3S land initialisations, successfully completing M5, and showing that both the median and variance of root zone soil moisture are highly model dependent.
We have also completed the provision of the first ERA6-Land prototype, including soil moisture and snow data assimilation and spanning 1939-2022 as part of WP4, successfully completing M7. The prototype includes land data assimilation, including snow cover and soil moisture, it is forced by ERA5 and spans the period from 1939-2022 inclusive. The spatial resolution of 35km and temporal output frequency satisfy the requirements for the seasonal demonstrators from WP5 to which ERA6-Land-Pv1 will feed into.
In WP5, we have defined the experimental protocol of the seasonal forecast demonstrators for phases 1 and 2, including determining the definition of the set of forecasts, the selection of output variables and the arrangements for data management. We have made great progress towards delivering seasonal forecast demonstrators for phase 0 and have made inroads into the development of the SUNSET web application to carry out the analysis on assessing the seasonal forecast demonstrators.
Developments of land-surface diagnostics and new methodologies for evaluating increased fidelity of land-surface processes in the prototypes and demonstrators has been performed in WP6. The assessment of the first CERISE global land reanalysis prototype and feedback was provided to WP4 in support of the next prototype preparation.
We have implemented a central ftp archive internal to the CERISE consortium, to share in situ and satellite observations/products with (i) satellite-based Land Surface Temperature, Leaf Area Index, and snow cover and snow water equivalent products, and (ii) in situ observations of snow and soil moisture, successfully completing M14 and D7.3. This WP7 work established methodology to derive time-varying Lake Cover and Land Cover and LAI datasets back to 1925.
Overall it has been a strong start in the first year of the CERISE project. We have achieved good adoption of the governance procedures by the project team, management and quarterly reporting, and regular meetings. Our CERISE website is well established and we are actively progressing our dissemination activities, with the CERISE project being presented on 8 occasions at 6 different conferences.
With the initial phase just completed, CERISE has already several tangible results in the first 12 months of the project.
Development and implementation of ensemble perturbation methods for land-surface assimilation systems and assessment in both the regional and global data assimilation systems has been achieved (WP1), successfully completing M1, and the results documented in D1.1.
We have conducted infrastructure developments in the global and regional data assimilation systems as part of WP2, with enhanced consistency between the coupled and offline land data assimilation approaches and increased code efficiency for outer loop coupling.
Our work in WP3 resulted in our first comparison of existing C3S land initialisations, successfully completing M5, and showing that both the median and variance of root zone soil moisture are highly model dependent.
We have also completed the provision of the first ERA6-Land prototype, including soil moisture and snow data assimilation and spanning 1939-2022 as part of WP4, successfully completing M7. The prototype includes land data assimilation, including snow cover and soil moisture, it is forced by ERA5 and spans the period from 1939-2022 inclusive. The spatial resolution of 35km and temporal output frequency satisfy the requirements for the seasonal demonstrators from WP5 to which ERA6-Land-Pv1 will feed into.
In WP5, we have defined the experimental protocol of the seasonal forecast demonstrators for phases 1 and 2, including determining the definition of the set of forecasts, the selection of output variables and the arrangements for data management. We have made great progress towards delivering seasonal forecast demonstrators for phase 0 and have made inroads into the development of the SUNSET web application to carry out the analysis on assessing the seasonal forecast demonstrators.
Developments of land-surface diagnostics and new methodologies for evaluating increased fidelity of land-surface processes in the prototypes and demonstrators has been performed in WP6. The assessment of the first CERISE global land reanalysis prototype and feedback was provided to WP4 in support of the next prototype preparation.
We have implemented a central ftp archive internal to the CERISE consortium, to share in situ and satellite observations/products with (i) satellite-based Land Surface Temperature, Leaf Area Index, and snow cover and snow water equivalent products, and (ii) in situ observations of snow and soil moisture, successfully completing M14 and D7.3. This WP7 work established methodology to derive time-varying Lake Cover and Land Cover and LAI datasets back to 1925.
Overall it has been a strong start in the first year of the CERISE project. We have achieved good adoption of the governance procedures by the project team, management and quarterly reporting, and regular meetings. Our CERISE website is well established and we are actively progressing our dissemination activities, with the CERISE project being presented on 8 occasions at 6 different conferences.
This is the first year of the project. Full results and impacts will be forthcoming as the project progresses.