Assimilation of ground based lidar and ceilometer observations of aerosols from the European E-Profile network into ECMWF's Integrated Forecasting System (IFS-COMPO, CY49R1)

Abstract. The Integrated Forecasting System with its extension for atmospheric composition (IFS-COMPO) provides global forecasts of atmospheric trace gases and aerosols for the Copernicus Atmosphere Monitoring Service (CAMS). The present system constrains aerosol concentrations by assimilating aerosol optical depth (AOD) from different satellites. Here, we explore the possibility of assimilating, in addition, ground-based lidar and ceilometer observations from the European E-Profile network. The system performance is evaluated by comparison to non-assimilated E-Profile stations, AOD observations from Aeronet, and aerosol surface concentrations from AirBase. Assimilation of E-Profile data significantly reduces biases and root mean square errors (RMSE) of model-equivalent vertical profiles of the attenuated backscatter coefficient. Without assimilation of E-Profile, surface concentrations of particles smaller than 2.5 μm (PM2.5) are frequently overestimated during summer, while corresponding concentrations of particles smaller than 10 μm (PM10) tend to be underestimated. Assimilation of E-Profile can reduce the RMSE of PM2.5 by up to 50 % and of PM10 by up to 10 %. Since the present analysis system uses the total aerosol mass mixing ratio as control variable, it cannot simultaneously reduce the positive PM2.5 bias and the negative PM10 bias. It typically reduces the PM2.5 bias at the expense of PM10, since fine particles make the dominant contribution to the optical cross sections per mass. Tests of different assimilation-system configurations reveal that the best overall performance is obtained by treating optical properties of dust with a spheroid model, suppressing vertical correlations in the background error covariances, and applying a relatively aggressive cloud mask.