First preliminary demonstration of a new climate indicator “aerosol and cloud cooling”

Since pre-industrial times anthropogenic aerosols counteract the climate warming attributed to anthropogenic greenhouse gases through direct and indirect effects. . Within the ESA CLIMATE-SPACE cross-ECV project SATACI (SATellite observations to improve our understanding of Aerosol-Cloud Interactions), a feasibility study is conducted to demonstrate the use of global, long-term satellite data records to derive a new climate indicator for the monitoring of the cooling offset due to anthropogenic aerosols and aerosol modified clouds. This new climate indicator intends to complement the existing tableau of WMO climate indicators (e.g. surface temperature, atmospheric CO₂ concentrations).

The new indicator is based on off-line (dual call) two-stream radiative transfer simulations. Baseline optical aerosol properties are taken from the MACv3 aerosol climatology, which is tied to multi-annual ground-based statistics from sun-/sky photometry and derived aerosol type contributions. Aerosol indirect effects are included based on statistical associations between relevant aerosol and cloud properties. In a stepwise approach, key aerosol properties (i.e. AOD, fine mode fraction, Dust AOD, absorbing AOD) and key aerosol/ cloud associations (i.e. fine mode AOD vs cloud droplet number concentrations, low level cloud cover) will be replaced with CCI / Copernicus Climate Change Service (C3S) (and other, such as CM-SAF) satellite retrievals. Outputs are global monthly maps and time series of aerosol impact associated radiative effects at the top of the atmosphere (TOA).

Uncertainties and diversity between different satellite datasets and aerosol cloud associations will be assessed by using different satellite data records for each variable and through uncertainty propagation of those satellite inputs through the radiative transfer code following the FIDUCEO principles. This feasibility study aims at providing an initial demonstration of a cooling indicator, assessing its potential, by exploiting the value of global, consistent, multidecadal satellite records, and identifying its limitations, such as diversity and uncertainties. To ease communication, a simple parameterization (similar to the last IPCC report) to convert TOA radiative effect changes to an equivalent surface temperature change (0.7W/m² ~ 1 Celsius) will be applied.

This paper will discuss the methodology, the uncertainty propagation strategy and initial demonstrations of the climate indicator using MODIS aerosol retrievals between 2000 – 2021 as well as four different C3S dual view records (1996 – 2012 and 2017 – 2025) of AOD and Fine Mode AOD.