Abstract
<jats:p>Abstract. The Earth Cloud Aerosol and Radiation Explorer (EarthCARE) satellite, launched in 2024, is the most complete cloud, aerosol, and precipitation observing satellite to date. Now in its second year of operation, EarthCARE provides a continuous stream of high-resolution data essential for refining weather and climate models. However, due to the advanced technologies and retrieval approaches used in EarthCARE, the credibility of each instrument and of their synergistic products must be verified. In this study, ground-based radiation observations from the Baseline Surface Radiation Network (BSRN) are used to validate surface global horizontal irradiance (GHI) computed using one-dimensional (1D) and three-dimensional (3D) radiative transfer models (RTMs) and reported in the EarthCARE ACM-RT product. To optimize collocation, EarthCARE's 1D fluxes are extended across-track utilizing EarthCARE's scene construction algorithm (SCA). In addition to the BSRN validation, EarthCARE irradiances are compared with gridded solar estimates from the Copernicus Atmospheric Monitoring Service (CAMS) radiation service, which infers high-resolution cloud information from geostationary satellites. Due to limited availability of the CAMS radiation service gridded dataset, this comparison is restricted to September–December 2024. The results indicate that EarthCARE's 1D RTM systematically underestimates GHI relative to both BSRN and CAMS, with Mean Bias Errors (MBEs) of –9.8 W m-2 (–2.1 %) and –20.1 W m-2 (–3.9 %), respectively. Intercomparison of EarthCARE's 1D and 3D RTMs revealed that the 3D RTM exhibits lower GHI bias against BSRN observations (–4.6 W m-2 compared to –19.5 W m-2). However, the 3D RTM substantially underestimates beam (direct) horizontal irradiance (BHI) (–51.4 W m-2) while overestimating diffuse horizontal irradiance (DHI) (47.1 W m-2), leading to the near-zero GHI bias. Spatial analysis demonstrates that EarthCARE GHI is generally lower than CAMS values across most regions, particularly in Oceania, Central Africa, and Europe, while parts of South America, Northern Africa, and Western Asia are notable exceptions where EarthCARE GHI exceeds CAMS. Approximately 65 % of EarthCARE's GHI bias against CAMS can be attributed to differences in cloud estimation, while the remaining 35 % stems from differences in the clear-sky GHI. Future data releases from BSRN and CAMS will expand the dataset, enabling a more robust assessment. These findings offer a critical early assessment of EarthCARE's performance and provide valuable benchmarks for the solar energy and atmospheric science communities.</jats:p>