SATACI

The SATACI project is a science exploitation study which utilises multiple Essential Climate Variable data products developed via ESA's Climate Change Initiative (CCI) to improve understanding the climate system that are directly relevant to IPCC assessments.

The objective of SATACI objective is to deepen understanding of Aerosol-Cloud interactions and the associated Radiative Forcing, capitalising on the heritage from the ESA Climate Change Initiative aerosol and cloud projects and state-of-art algorithms for the consistent retrieval of aerosols and clouds. Two main activities will be performed during this three-year study:

• Aerosol-Cloud (ACI) analyses from satellite data to tackle aerosol indirect effects on liquid clouds as well as the relationship between dust concentration and cloud glaciation temperature
• Feasibility study for a new aerosol-cloud climate indicator to monitor the cooling effect of ACI on the climate and complement existing WMO Climate Indicators.

Aerosol-cloud analyses from satellite data

ACI analyses will use data from geostationary and polar-orbiting satellites to study the impact of aerosols on clouds at different spatial and temporal resolutions, relying on previous efforts to expand the retrieval of aerosols in the vicinity of clouds. Two scientific studies will be undertaken to develop the analysis methods:

• Scientific Study I: Analysis on aerosols' indirect effect on liquid clouds. This work relies on aerosol and cloud datasets obtained with the CISAR and ORAC retrieval algorithms. External datasets could be included, as necessary, to mitigate limitations in the retrieval from the retrieval algorithms. Statistical analysis of aerosol-cloud relations will be carried out considering proxies for aerosols and clouds such as AOD and CDNC.
• Scientific study II: Cloud glaciation temperature and dust concentration. This study is investigating the sensitivity of the cloud phase occurrences to dust concentration, the dominating INPs initiating cloud glaciation (Han et al., 2023) for sub-zero temperatures above -38°C (heterogeneous freezing). This study will exploit aerosol and cloud data including dust or coarse mode aerosol optical depth, aerosol layer height, clout top temperature and cloud phase, available through cloud-CCI and Copernicus Climate Change Service (C3S) datasets.

Two feasibility studies will be performed to ensure that the proposed methodology is appropriate. Methods to repeat the statistical analysis at different temporal and spatial resolutions; and to test the usefulness of the outcome of these studies will be proposed, using the Norwegian Earth System Model (NorESM) model (Seland et al., 2020) - a state-of-the-art CMIP6 class model. Adaptations need to be implemented to increase, for instance, the output frequency, and - eventually - simulate satellite observations to ensure more consistent comparisons.

Feasibility study for a new aerosol-cloud climate indicator

A feasibility study to derive a new aerosol-cloud climate indicator will be performed within this proposal, aiming at delivering a new tool to monitor the cooling offset due to aerosols and clouds and complement the existing World Meteorological Organisation (WMO) indicators.

This activity aims to visualise the greenhouse gas warming concealed by aerosols and clouds developing a new climate indicator ‘aerosol / cloud cooling offset’. This aerosol overall cooling has contributions by direct (aerosol presence) effects and by indirect effects - mainly through aerosol modified water clouds. Global, long-term satellite data records will be used to demonstrate the feasibility of a method to derive a new climate indicator which enables monitoring the cooling offset due to (anthropogenic) aerosols and (aerosol modified) clouds. This new indicator would complement the existing WMO climate indicators based on off-line (dual call) two-stream radiative transfer simulations Kinne, 2019.  

Consistency Study

The two activities will run in parallel and culminate in a synthesis work package where the statistics obtained from regional satellite observations (Activity I) will be compared with the climate indicator results for overlapping regions/periods. To support this exercise, a singular vector decomposition (SVD) will be performed, to compare the temporal evolution of various spatial modes/patterns in the climate indicator and cloud/aerosol property time series. This should reveal which aerosol and cloud properties are driving the value of the indicator. Furthermore, the SVD analysis can be exploited to investigate possible correlation between the new climate indicator and the existing WMO indices. The radiative effect calculations performed on the ensemble of Level-3 products used within Activity 2 will be compared with the values obtained averaging and regridding the fluxes calculated using Level-2, to assess the impact of spatial and temporal regridding.

The proposed approach will investigate the consistency between observational evidence obtained from available datasets of aerosols and clouds and the model predictions, trying to improve our knowledge on aerosol-cloud interaction and their radiative impact on the Earth’s climate.