| 05 Aug 2026
Validation of EarthCARE Surface Irradiance Products Against Ground-Based Observations and Geostationary Satellite Estimates
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.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Measurement Techniques.
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General
This study compared the GHI from the EarthCare ACM‑RT product against BSRN ground measurements. The EarthCare GHI is also compared with CAMS, which is based on cloud properties from geostationary satellites. Overall, the EarthCare GHI is smaller than its CAMS counterparts. For cloud‑free cases, EarthCare GHI is biased low relative to BSRN, a discrepancy that is not explained by AOT biases.
The study is thoroughly performed, and the manuscript contains relevant information for the clouds, aerosol, radiation, and modeling communities. However, I feel that the manuscript could be improved by presenting clearer messages. I suggest that the authors highlight their most important findings and consider moving several figures to an appendix or supplement, if appropriate.
Major comments:
The reason for the negative GHI biases in the EarthCare product is not well explained in this study. While the analysis shows that aerosol optical depth cannot explain the biases, it would be relevant to discuss other possible causes. Additionally, the reasons for the differences in GHI between EarthCare and CAMS are not explored, except for regions where positive differences appear (e.g., Sahara and Amazon). I do not expect the exact reasons to be fully resolved here, but the manuscript should clearly outline plausible contributing factors.
Specific Comments:
* Section 2.2: I assume there are also uncertainties in the TOA fluxes derived from BBR measurements due to the unfiltering and angular correction processes. Please provide the uncertainty ranges of the BBR fluxes or include relevant references. Are there studies comparing the accuracy of CERES and BBR TOA fluxes?
* Line 197: Figure 1 could potentially be moved to Appendix A, considering the large number of figures in the main manuscript already.
* Line 199: So only daytime EarthCare orbits were compared? This implies that daytime comparison was also considered for LW. Since daytime and nighttime LW biases often differ, it would be relevant to clarify that LW biases were examined only during daytime.
* Line 210: Have you compared cloud fractions and cloud optical depths estimated from EarthCare CAPTIVATE and the McCloud model? These two parameters should be central to explaining differences in GHI for total skies (but not cloud-free regions).
* Line 517: I assume the CAMS radiation dataset is also produced using the 1D RTM. If so, would the use of a 1D model for the EarthCare give better consistency between EarthCare and CAMS, assuming similar cloud properties? However, cloud fractions and optical depths from the two products may differ significantly, likely contributing to the GHI differences (as discussed in Fig. 10).
* Fig. 12b: Could the authors explain the large outliers when EarthCare GHI is 600–800 W/m² and CAMS GHI is 400–600 W/m²? The majority of points lie near the one‑to‑one line, indicating strong correlation. However, after accounting for outliers, the mean negative difference suggests a systematic smaller values in EarthCare GHI relative to CAMS.
* I see the point of including Fig. 13 to motivate the scale used in later figures. However, Fig. 13 could be replaced by simply referencing Line 573: “In contrast, the MBE remains scale‑invariant…”
* In Table 1, when the EarthCARE GHI was compared with BSRN, EarthCARE GHI was biased low for cloud-free cases, and EarthCARE GHI was biased high for overcast scenes. In Fig. 11, EarthCare GHI is smaller than CAMS for cloud-free scenes (CMF ~ 1), and EarthCARE GHI is larger than CAMS for overcast scenes (CMF ~ 0). Fig. 15 shows that BSRN is somewhere between EarthCARE and CAMS for all skies. How about cloud‑free cases specifically—does BSRN lie between the two? What are the main factors deriving all these differences for cloud-free cases? Since AOT was ruled out, could the authors suggest other parameters driving differences under cloud‑free conditions?
* Considering CAMS uses multiple geostationary platforms, are there discrepancies in cloud properties depending on the satellite source?
* Fig. 14c: EarthCare GHI is larger than CAMS GHI over the Sahara and Amazon, likely due to smaller AODs in EarthCare. Other regions show opposite signs. Since AOD does not explain these differences, could the authors suggest additional relevant parameters?
* When comparing RT simulations with TOA BBR or ground measurements, are the biases dependent on solar zenith angles?
* I understand that the comparison in Fig. 18 was performed to ensure consistent sampling between the surface (SFC) and TOA evaluations. However, for the TOA comparison, additional sampling could potentially be included between the ACM‑RT product and the BBR measurements. Have you, or has any previous study, carried out a direct TOA comparison between ACM‑RT and BBR measurements? If so, are the findings of this study consistent with those earlier comparisons?