the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 Oct 2025
Emerging low-cloud feedback and adjustment in global satellite observations
Abstract. From mid-2003 to mid-2024, a decrease in low-cloud amount enhanced the absorption of solar radiation by 0.22±0.07 W m-2 decade-1 (±1σ range), accelerating the energy imbalance trend during that period (0.44 W m-2 decade-1). Through controlling factor analysis, here we show that the low-cloud trend is due to a combination of cloud feedback and adjustments to aerosols and greenhouse gases (respectively 0.07±0.01, 0.06±0.01, and 0.05±0.03 W m-2 decade-1), which jointly account for 82 % of the trend. The contribution of natural climate variability is weak but uncertain (0.03±0.07 W m-2 decade-1), owing to a poorly constrained trend in boundary-layer inversion strength. Importantly, the observed low-cloud radiative trend lies well within the range of values simulated by contemporary global climate models under conditions close to present day. Any systematic model error in the representation of present-day global energy imbalance trends is thus likely to originate in processes other than low clouds.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics.
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Status: open (extended)
- RC1: 'Reviewer comment on egusphere-2025-5206', Anonymous Referee #1, 26 Nov 2025 reply
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- 1
Ceppi et al. use cloud-controlling factor (CCF) analysis to investigate the role of low clouds in the observed trends of Earth's absorbed solar radiation. They combine the CERES-FBCT satellite product with reanalysis and model data to quantify how CCFs influence low clouds and how those in turn affect the amount of absorbed solar radiation. They decompose the trend into unforced and forced components, where the latter is further split into cloud feedback (to surface warming) and rapid aerosol and GHG adjustments. They find that all three of them contribute to a forced radiative trend, with cloud feedback being the strongest contributor, whereas the unforced component seems smaller but very uncertain. In my view the study is a well-founded, important and timely contribution to the dynamically evolving understanding of the observed radiative trends and certainly suitable for publication as an ACP letter, although I think that some points would benefit from clarification.
Before providing my specific comments, I'd like to mention that I'm wondering how these results based on local CCFs fit (or not) with recent work that links the observed cloud and SW absorption trends primarily to large-scale circulation trends rather than local "within-regime" factors (primarily Tselioudis et al. 2025). Could the authors add a brief discussion about this?
Overall, I recommend to publish this paper as an ACP letter subject to minor revisions.
Specific comments (including minor technical ones):
L5: "The contribution of natural climate variability is weak but uncertain [...], owing to a poorly constrained trend in boundary-layer inversion strength"; It remains somewhat unclear to me why the large uncertainty related to trends in EIS should affect the unforced component much more than the forced component. Can this be clarified?
L9 (and elsewhere): "... processes other than low clouds."; maybe this is a bit meticulous, but "low clouds" are not a process. Maybe reformulate to something like "... processes unrelated to low clouds." or so.
L37: "SW low-cloud anomalies [...] made a large contribution amounting to half of this decadal trend [of Earth’s global energy imbalance]"; It seems that the CERES total SW trend is even something like 0.8W/m2/dec, couteracted by a LW trend of around -0.3W/m2/dec (e.g., Fig. 3 in Myhre et al. 2025). Do I infer correctly that (i) the contribution of low clouds to the total SW trend is only around a quarter and that (ii) the bulk of the rest would then likely be due to mid- and high-level clouds (with more of a LW compensation)? Maybe that's worth to metion.
Figure 1: (i) I recommend to add units to the decadal trend numbers. (ii) In panel d, it would be good to mention/remind that this is about LOW-CLOUD trends, e.g., by changing the title into "Low-cloud trend contributions". (Also in the corresponding part of the caption.)
L50: "... nearly all of the RSWlow trend is associated with decreasing cloud amount, as opposed to decreasing optical depth"; I'm wondering if observational uncertainties in the way how cloud amount and optical thickness are distinguished (including the choice of a threshold from which point something is considered cloud vs. no cloud) might affect this. Related, the near-global averaged C_low seems to have much less of a trend component than R_SWlow, and in particular does not mirror the increase of R_SWlow of the last few years, making me wonder if this could be related to recent aerosol-induced changes in cloud optical thickness after all.
Fig. 2: I recommend to add units to the decadal trend numbers. (This also holds for Figs. A3 and A4.)
Fig. 3: Given that GHG adjustment seems to be an important contributor, I'd like to see a version of panel f with zoomed colorbar, plus a minimum explanation/hypothesis in the text indicating the possible physics behind this adjustment.
L81: "... given the known large decadal variations in low-cloud feedback."; is this indeed meant in the sense of decadal variations that would change (temorarily) the "background state" which would then result in modified low-cloud FEEDBACK during that limited time period? Or does this actually not relate to the feedback but just the clouds themselves, so something like "... given the known large decadal variations in low-cloud cover.", which I consider much more plausible? Or, a third option, is it about decadal variations in DIAGNOSED low-cloud feedback, given that limited observational periods will certainly affect estimates of the feedback?
Paragraph starting L80: Is it possible that the smallness of the uncertainty in the forced R_SWlow component is partly due to the assumption that the GMST trend is completely forced?
L97: "Comparing with amip minimises differences in CCF trends between models and observations, thus highlighting the role of the cloud-radiative sensitivities."; Is "minimises" here really the case? I mean, aspects like EIS, which as you show are more related to T_700hPa than T_srf, may still be rather unconstrained by the prescribed SST. Maybe "reduces" would be more appropriate?
L138: "the observed substantial low-cloud radiative trend cannot be interpreted as evidence of an unexpectedly strong low-cloud feedback that climate models are systematically missing (Goessling et al., 2025)"; The Goessling et al. paper does not make a strong statement about this being the main culprit, but mentions an upper-range low-cloud feedback just as one of three possible contributors (besides aerosols and variability).
Paragraph starting L165: In principle one can retrace the CCFs to earlier literature where there's more explanation and physical argumentation around them. However, given that this chain of studies is somewhat long/complex, I would find it helpful if brief explanations of the physical rationale (and definition, see next point) of these seven CCFs could be repeated here.
L167: "sea-surface temperature (SST) advection, SSTadv"; if I'm not mistaken, this is about temperature advection by near-surface winds, where the SST gradient strongly governs the air-temperature gradient, but it's not the same as actual "sea-surface temperature advection", which sounds like ocean surface velocities were involved. Some clarification would be good.
L203: Does this equation need to be applied iteratively from top (low pressure) to bottom (high pressure), so that U(p_i) is then always something like sum(L_n(p<p_i))? And does that ultimately yield a total cloud cover that is consistent with the CERES total cloud cover, or am I thinking wrong here?
L235: "The sensitivities Θi are calculated via ridge regression, where all variables have been deseasonalised, and the CCF predictors have been standardised"; I do not quite see the justification of computing "all-year" sensitivites given that they could well vary considerably seasonally (maybe as much as regionally in places?) due to seasonal changes of the background conditions, in particular in the extratropics. Is there evidence that this is not the case? I think that should be clarified.
L265: Given that dX/dT_for and dX/dT_GHG are based on different sets of models, I'm wondering if dX/dT_for and thus the resulting dX/dT_SST would be similar if just the same subset of models was used?
L266: Similarly, here dX/dT (obs-based) and dX/dT_for (model-based) stem from different datasets, so I'm wondering how the resulting dX/dT_unfor would look like if they were obtained from consistent data. For example, if one would use a single ensemble member of a CMIP historical/scenario model simulation as surrogate observation and base dX/dT_for on a (large) ensemble of just that same model, would the diagnosed unforced components exhibit quasi-random patterns of similar magnitude (compared to the right column of plots in Fig. A2)? Could that provide evidence for the validity of the method, whereas, if magnitudes are much smaller, would that suggest that the "unforced" components found here may contain considerable amounts of in reality forced changes?
L293+294: "for the GHG adjustment trend we take the spread in CMIP6 model-simulated GHG adjustment as a measure of uncertainty, using eight models with available data" and "we combine our eight estimates of the RSWlow GHG adjustment trend with the 20 estimates of the sum of other trend contributions [...], yielding a 160-member ensemble"; my understanding is that the GHG adjustment is derived from the piClim-ghg/control simulations, and according to Tab. A1, that data is available from ten models, not eight. Have I misunderstood this?
L326: "the CCF trends are in disagreement, with CAMS showing a weak decrease and MERRA2 a weak increase in mass concentration. This is contrary to our expectation of a clear decrease in sulfate aerosol concentration, particularly following the introduction of new shipping regulations in 2020"; Could this also be related to natural variations in aerosol concentrations (e.g., wildfires, even if sulfate is not a typical wildfire aerosol)?
References:
Tselioudis et al. (2025), Contraction of the World’s Storm-Cloud Zones the Primary Contributor to the 21st Century Increase in the Earth’s Sunlight Absorption, https://doi.org/10.1029/2025GL114882
Myhre et al. (2025), Observed trend in Earth energy imbalance may provide a constraint for low climate sensitivity models, https://doi.org/10.1126/science.adt0647