Observational Constraints Suggest a Smaller Effective Radiative Forcing from Aerosol-Cloud Interactions (Data)

This dataset contains variables calculated for the analysis presented in "Observational constraints suggest a smaller effective radiative forcing from aerosol-cloud interactions" by Park et al. (2025). The dataset contains regression coefficients derived from monthly data spanning 2003–2019 across the 60°S–60°N latitude band, with a focus on ocean regions. All variables are derived using a cloud controlling factor (CCF) analysis, which constrains the influence of environmental conditions on cloud droplet number concentration (Nd) and the non-obscured low-level cloud radiative effect (CRE_lcld). The regression framework includes six environmental factors from MERRA-2 reanalysis—sea surface temperature, estimated inversion strength, horizontal surface temperature advection, relative humidity at 700 hPa, vertical velocity at 700 hPa, and near-surface wind speed—along with aerosol proxies on a natural logarithm scale: sulfate aerosol mass concentration at 925 hpa (SO₄) from MERRA-2 and aerosol index (AI) from MODIS. activation_rate.nc: This file contains the activation rate of Nd in response to aerosol proxies (SO₄ and AI). The activation rate is calculated as ∂ln(Nd)/∂ln(X), where X is either SO₄ or AI, while controlling for meteorological variability using the CCF regression framework. susceptibility_with_activation.nc: This file provides the susceptibility of CRE_lcld to aerosol concentrations (SO₄ and AI), explicitly incorporating the activation rate. This corresponds to ∂CRE_lcld/∂ln(Nd) × ∂ln(Nd)/∂ln(X), while holding all other environmental conditions constant, as described in Eq. (2) of the paper. susceptibility_without_activation.nc: This file provides the susceptibility of CRE_lcld to aerosol concentrations (SO₄ and AI) without explicitly including the activation rate. This corresponds to the regression of CRE_lcld anomalies onto ln(X), while holding all other environmental conditions constant, as described in Eq. (1) of the paper. All other datasets used in the paper are publicly available from their respective repositories and are listed in the "Data Availability" section of the paper.