Exploring Low Cloud and Aerosol Interactions in Geostationary Satellite Observations, LES and CESM: Causal Relationships and Timescales

The impact of atmospheric aerosol perturbations on cloud albedo is the most uncertain anthropogenic forcing of the climate system, primarily due to the unknown magnitude of cloud water and cloud fraction (CF) adjustments in response to these perturbations. Such adjustments are commonly inferred from linear regression analysis between cloud water path (CWP) and cloud droplet number concentration (N_d), and between CF and N_d. However, it is important to recognize that correlation alone does not imply causation. Quantifying the causal relationships between CWP and N_d, as well as CF and N_d, and their respective timescales remains challenging given the intricate interplay between meteorological conditions, aerosol and cloud properties, and other co-variabilities in natural systems. This leads to large uncertainty in the magnitude and sign of CWP and CF adjustments in response to aerosol-induced perturbations, making it difficult to evaluate and identify deficient physical processes in climate models.

In this study, we perform wavelet coherence analysis on time series of CWP and N_d obtained from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard geostationary satellite Meteosat-11. Our analysis is applied to 2ºx2º scenes over the Eastern North Atlantic region with low horizontal wind. With this analysis, we identify time periods where CWP and N_d exhibit significant coherence at time frequencies ranging from 30 minutes to 8 hours. Within the selected time periods, we examine the phase of the wavelet cross-spectrum between the CWP and N_d time series to determine the relative lag between the two variables. Our analysis enables us to classify scenarios into four distinct phase lag categories at different time frequencies: CWP positively/negatively leading N_d; N_d positively/negatively leading CWP. The four scenarios represent four distinct physical causal relationships between CWP and N_d. We quantify the magnitude and trend of aerosol-induced CWP adjustments in each scenario and their respective timescales. A comparable analysis is conducted for CF and N_d. We further extend our analysis to Large Eddy Simulation (LES) and the Community Earth System Model (CESM) to efficiently assess the representation of aerosol cloud interactions in the model.