| 08 May 2026
Bias in satellite-derived cloud radiative effect over Arctic sea ice relative to aircraft measurements during ARCSIX
Abstract. The surface radiation budget (SRB) strongly controls the summertime evolution of sea ice and, therefore, plays a key role for the ongoing transformations of the Arctic climate system. Clouds can have a significant impact on the SRB, which is quantified by the cloud radiative effect (CRE). Consequently, continuous, Arctic-wide monitoring of clouds and further factors governing the CRE, including surface and thermodynamic properties, is required. These persistent observations can only be provided by passive remote sensing instruments aboard polar-orbiting satellites. However, cloud detection deficiencies and the lack of accurate surface albedo data over heterogeneous sea ice limit the precision of satellite products and subsequent CRE estimates. Therefore, this study quantifies the accuracy of satellite cloud products, the surface albedo assumed therein, thermodynamic analysis data, and the resulting CRE simulations. To isolate the contributions of individual parameters to the CRE bias, satellite-derived simulation input is consecutively replaced with collocated aircraft observations that were collected over sea ice north of Greenland during the Arctic Radiation–Cloud–Aerosol–Surface Interaction Experiment (ARCSIX) between May and August 2024. It is concluded that clouds warm the surface according to simulations initialized with aircraft measurements, whereas satellite-based CRE estimates suggest a cooling effect. This discrepancy is primarily caused by a negative bias in the assumed surface albedo. Substantial biases are also identified for cloud height and low-level air temperature, but compensating effects and a relatively weak sensitivity of thermal-infrared radiation to these biases mitigate their impacts on the CRE.
The manuscript presents a thorough and well-executed study of biases in satellite-derived estimates on cloud radiative effect over Arctic sea ice. The extensive research-aircraft campaign provides a unique and valuable dataset that enables a robust quantitative assessment of these biases. The analyses are comprehensive and make full use of the available satellite and aircraft observations. The care with which the analyses have been conducted is evident throughout the manuscript, giving the reader confidence in the results and their interpretation.
I have a single major comment and several minor suggestions for improvement. The issues raised should be straightforward to address. Overall, I consider this to be a high-quality contribution, and I believe the manuscript is well suited for publication in ACP following minor revisions.
Major comment
The authors should make it clear how the findings of this extensive study advance scientific understanding in the field. At present, the manuscript jumps directly from the final Results subsection (Section 4.3) to the Conclusions. The Conclusions section contains no references to earlier studies, making it difficult to assess the novelty and significance of the reported findings. The manuscript would be strengthened by either adding a dedicated Discussion section that highlights the key advances beyond existing knowledge or by incorporating a concise discussion of these advances, with appropriate references, within the Conclusions section. This would help readers better understand the study's contribution to the field and its scientific impact.
Minor comments
Line 2: Clouds have a significant impact
Lines 10-11: The phrase "between May and August" is ambiguous.
Line 18: specify the period, as the number is very sensitive to it.
Lines 33-34: Include wind forcing on ice dynamics as a factor controlling sea ice evolution. Also, in winter the origin of coldest air masses is often in northern Siberia and Canada.
Line 63: perhaps "continuous ground-based observations and temporary campaign measurements"
Lines 100-101: Do you mean "Moreover, passive satellite imagers do not provide direct information on cloud-base properties. As a result, cloud-base height (CBH) can only be inferred ..."
Lines 154 and 197: Porpoise is a small marine mammal. Perhaps you mean a purposive leg and purposive sampling.
Line 191: It is assumed that
Lines 270-276: Do multiple reflections between the cloud base and snow/ice surface play a role here?
Line 294: What do you exactly mean by aggregation for all cloud walls?
Figure 3. Explain the meaning of the grey bars?
Lines 323-332: Most of the paragraph is about weak correlations but the text ends with very positive remarks, which I found confusing.
Line 367: exhibits a behaviour similar to that in the first phase
Line 401: What do you mean by current assumptions for sea ice melt?
Line 412-414: One more challenge is representation of the the surface scattering layer (SSL) that develops through snow metamorphism and the ice-to-snow transformation process.
Line 518: This assumption seems unrealistic. Were there any alternatives for such an assumption?
Lines 545-551: This subsection is very short bu the strong impacts of surface albedo become very evident in the following sub-section. Consider merging or re-naming the subsections.
Lines 638-641: Clarify the text.
Line 649: "... and should be addressed in upcoming research."
Line 672: "... albedo values assumed ... do not well represent..."