Study WP5.5 Cloud and Aerosol Analysis

Description

This Study is led by Angela Benedetti and Kirsti Salonen from ECMWF. Additional contributors to this Study are Axel Lauer from DLR and Jeronimo Escribano from BSC.

The main CCI ECVs used in this Study are Aerosol, Cloud, Soil Moisture, and Water Vapour.

It is estimated that this Study will run from September 2023 to August 2024.

The Study comprises of three parts. The first part is undertaking dust aerosol analysis with the BSC system (Jeronimo Escribano, BSC). This would involve constraining global dust aerosol simulations from the BSC MONARCH model with CCI data to produce dust analyses during the extraordinary event of June 2020. The second part is to undertake Cloud / Aerosol analysis with the ECMWF system (Angela Benedetti and Kirsti Salonen, ECMWF). This would involve joint assimilation of Aerosol and Cloud ECVs in the ECMWF IFS during June 2020 and September 2021 with the IFS 4DVar scheme in CAMS configuration. The third part is to undertake the Cloud and Aerosol analysis validation Study (Angela Benedetti and Kirsti Salonen, ECMWF; Axel Lauer, DLR; and Jeronimo Escribano, BSC) involving evaluation using the ESMValTool and internal tools at BSC/ECMWF.

Results and conclusions (July 2024)

Data sets for aerosol optical depth (AOD) and cloud optical depth (COD) from Sea and Land Surface Temperature Radiometer (SLSTR) have been evaluated and tested for assimilation in the ECMWF 4DVar system. While AOD observations from other instruments are operationally used in the Copernicus Atmosphere Monitoring Service (CAMS) configuration, CODs are a new source of information and provide an interesting avenue for assimilation of cloud information into the system. Figure 1 (below) shows observation minus model background (OmB) mean difference from a passive monitoring experiment for CODs. The statistics indicate positive mean difference over regions where there is typically persistent marine stratus. Negative mean difference on the other hand is seen in the inter-tropical convergence zone. The results are in line with similar monitoring done for Ocean and Land Colour Instrument (OLCI) reflectances, indicating that the mean differences would originate from the lack of stratiform clouds in the model rather than an observational or retrieval problem. Monitoring of the CCI SLSTR AOD observations indicates good and homogeneous data quality over sea, except the regions where bias related to desert dust is present.

Impact studies have been performed in depleted observing system framework to emphasise the impact originating from the new data sources. The baseline experiment includes assimilation of conventional and gps observations and the AODs and CODs are added on top of the baseline experiment. Assimilation of the CCI AODs generally decreases the magnitude of the modified normalised mean bias as well as the fractional gross error with respect to independent AERONET AOD data. Experimenting with CODs indicates that strict quality screening of the observations is required and even so, some degradation is seen especially in the short range temperature forecasts as verified using independent observations. The final experimentation with joint use of AODs and CODs is currently ongoing.

Figure 1: Observation minus model background mean difference for SLSTR COD observations, the covered period is September 2021.