This study introduces the Annual Columnar Radiative Absorptivity (ACRA24) model, a radiative balance framework specifically devised to quantify atmospheric absorptivity of both solar and infrared radiation, developed using custom Python code. By focusing on atmospheric aerosols, ACRA24 aims to enhance our understanding of their radiative impacts across diverse Northern Hemisphere climates. The model calculates key optical parameters, including visible (αVA) and infrared (αTA) absorptivity by the atmosphere, solar reflectivity (r), visible absorptivity by the surface (αVS), and other radiative balance components. The Python code ensures precise input of solar radiation, temperature, and optical thickness for accurate site-specific analysis. Significant seasonal patterns in aerosol optical depth (AOD) were observed, with a clear decline from tropical to continental climates. Tropical regions had the highest AOD, reaching ~0.55 in Dhaka due to urban-industrial and biomass-burning aerosols. Arid climates, including Kuwait and Tucson, showed AOD peaks of up to 1.5 during dust storms. The relationship between the Ångström Exponent (AE) and AOD identified dominant aerosol types. Biomass-burning and urban-industrial aerosols accounted for 46.2% of aerosols in tropical regions, while continental aerosols dominated other climates. The ACRA24 model estimated atmospheric absorptivity in the visible (αVA) and infrared (αTA) spectra, with tropical climates showing the highest values (αVA = 0.55; αTA = 0.88). Arid climates exhibited variable absorptivity due to dust, while temperate and continental regions remained stable. Aerosol radiative forcing (ARF) at the Top of the Atmosphere (TOA) showed minimal variation across climates, but Bottom of the Atmosphere (BOA) effects were strongest in tropical regions. This analysis highlights the critical importance of the ACRA24 model in advancing climate science and provides valuable insights for future aerosol–climate interaction research.
Salhi et al. (Fri,) studied this question.