Using AEOLUS Aerosol Assimilation to pave the way for EarthCARE

EarthCARE, ESA’s and JAXA’s joint mission, is expected to launch in 2024 carrying ATLID, a high-spectral resolution lidar with depolarization capability. The instrument will provide valuable data for characterizing atmospheric aerosols and for improving atmospheric composition modelling. The aim of this study is to show how working with ESA’s Aeolus wind mission prepares us for taking advantage of ATLID. Aeolus, which launched in 2018 and deorbited in 2023, was not specifically designed to observe aerosols but still provided aerosol products. Due to the lack of a cross-polar channel, it underestimated the aerosol-related backscatter by as much as 50% in scenes with non-spherical particles. During the ESA L2A+ project, an enhanced aerosol product was developed through data fusion with other data sources (such as NASA’s CALIPSO mission) to account for Aeolus deficiencies. The impact of this new product was assessed through assimilation experiments in regional NWP models, showing both the direct improvements of the new product, as well as the betterment of aerosol fields in regional models through assimilation of a profiling instrument. Our results were validated using data from the ESA-ASKOS tropical campaign, which took place in Cabo Verde during Summer and Autumn of 2021 and 2022. The open-source tools created for Aeolus are further developed to support EarthCARE. Working with simulated data, we show the impact of ATLID profile assimilation on both the representation of aerosols in the model, as well as the impact on numerical weather prediction through radiative feedback. The experiments are done using the Weather Research and Forecasting (WRF) model, alongside the Data Assimilation Research Testbed (DART), with AEOLUS and EarthCARE support added. The L2A+ team acknowledges support by ESA in the framework of the "Enhancing Aeolus L2A for depolarizing targets and impact on aerosol research and NWP project (4000139424/22/I-NS). This work was supported by computational time granted from the National Infrastructures for Research and Technology S.A. (GRNET S.A.) in the National HPC facility - ARIS - under project ID pr014048_thin.