Decadal variations of tropospheric aerosols can have a strong impact on the production of reanalyses and seasonal re-forecasts. In preparation for the next generation of C3S products, CONFESS has produced a homogenous and consistent multi-decadal record of tropospheric aerosols, exploiting the atmospheric composition capabilities that the Copernicus Atmosphere Monitoring Service (CAMS) has been developing in the Integrated Forecast System (IFS-COMPO). A time-varying climatology of multiple aerosol species is calculated from data from a multi-decadal set of model  forecasts constrained by ERA5 meteorology, and with continuously evolving chemistry and aerosols driven by specified emissions. So far, we have considered the periods 1971–2019 forced by CMIP6-style emissions data (the latest version of CEDS, together with GFED for fire emissions), and 2003–2020 forced by CAMS emissions. Creating data back to 1940 will be straightforward once the ERA5 reanalyses are complete for that period. The aerosol records are then smoothed with a nine-year running mean to represent decadal variability. The resulting product has the added advantage that the last nine years can be used as a representation of the current climate aerosol values for NWP. We plan to use time-varying aerosol climatologies produced in this way for the ECMWF model versions that will be used for the next generation of ECMWF seasonal forecasts SEAS6 and the upcoming C3S reanalyses ERA6. Having an up-to-date aerosol climatology that is consistent with the latest CAMS aerosols is also helpful in allowing us to explore the impact of interactive aerosols on numerical weather predictions

 Change in July vertically integrated aerosol [mg/m²] between 1975 (left) and 2015 (right) for selected aerosol species. The effects of increased forest fires at high latitudes, changes in nitrogen chemistry affecting fine nitrate levels, pollution controls in Europe and North America, and emissions growth in India and the Middle East are all visible. Sulphate aerosols over China have peaked and are now declining.

A new deliverable presents the results of improved vegetation variability on surface fluxes modeled with offline land surface models. In this deliverable, we present the integration of the unprecedented vegetation information, from the latest satellite campaigns in the frame of Copernicus, into the land surface models (LSMs) used for reanalysis and initialization of the seasonal to decadal prediction systems. Observational Land Cover (LC) and Leaf Area Index (LAI) from CONFESS deliverable D1-1 are implemented as boundary conditions for the CHTESSEL (ECMWF), EC-Earth HTESSEL-LPJGuess (CNR) and the ISBA-CTRIP (Météo-France) land surface models. The effects of the improved representation of vegetation variability from observations on the LSMs has been evaluated in offline simulations forced by ERA5 atmospheric forcing.

Here we present the effects of seasonally and inter-annually varying LAI (sensitivity experiment), based on Copernicus observational data, on modelled evaporation, compared to evaporation modelled using seasonally varying LAI only (control experiment). Evaporation was evaluated using DOLCEv3 evaporation as reference. The figure below shows the effect of inter-annually varying LAI on the correlation of inter-annual anomaly evaporation for the three models with respect to the reference. The correlation consistently improves (blue colours) for ECMWF and CNR models, with the largest effects in regions with transitional climates. Also for the MF model considerable improvements were found.

The knowledge from the sensitivity analysis in this report is driving the selection of better solutions and configurations to include for the initialization/simulation of the predictions in CONFESS WP3. You can read more about the results in D1.2 Improved vegetation variability.