| 27 Feb 2026
The SOLCHECK Project: A State-of-the-Art Investigation into the Imprints of Solar Variability Across Multiple Timescales
Abstract. The project Solar Contribution to Climate Change on Decadal to Centennial Timescales (SOLCHECK) investigated the influence of solar variability on the atmosphere from the pre-industrial era to the present and future. Variations in the Sun’s output, ranging from weeks to millennia, leave distinct imprints on the climate system. Assessing these imprints is challenging due to limited observations, incomplete representation of feedbacks in climate models, and computational constraints. By exploiting a large ensemble of simulations with advanced chemistry–climate models incorporating realistic solar forcing, SOLCHECK particularly aimed at reducing prevailing uncertainties of the atmospheric solar imprints, and to assess the sensitivity of the atmospheric response to solar forcing on different time scales and in different climate states. One key result of SOLCHECK is that although the initial radiative and chemical response to the 11-year solar cycle is consistent across models in the upper tropical stratosphere, the tropospheric climate response in northern winter is highly sensitive to the dynamical state of the stratosphere, thus impeding a robust assessment of surface solar signatures and decadal climate prediction skill. Another important finding suggests that the climate system reacts differently to solar forcing under past, present, and future conditions, showing a stronger response to external solar variations in the tropical upper troposphere and the Arctic as anthropogenic warming progresses. SOLCHECK further highlighted potential impacts of extreme solar storms in a future climate, as such events, although occurring extremely seldom, may have substantial effects on surface UV with potential consequences for ecosystems and human health.
As summarised in the abstract, this manuscript reports climate model simulations designed to assess the “influence of solar variability on the atmosphere from the pre-industrial era to the present and future.” This is a very well-written article reporting a well-intentioned study by the authors, many of whom have a solid history in studies of this type. However, as explained further below, whether intentional or not, a somewhat unfair advantage is given to the effect of particle precipitation through emphasis on a “worst-case” SEP event occurring only once every few millennia. In contrast, the 11-yr solar UV forcing adopted for the simulations is severely diluted and underestimated, leading to no modeled top-down influence on tropospheric climate at all! Prior work on the latter mechanism is also not adequately reviewed or taken into consideration. Major revisions are needed prior to publication.
Regarding section 2, the abstract and the description in section 2 do not make it clear whether UV dose effects on human health of “worst-case” events such as that believed to have occurred in 774-775 would be limited mainly to high polar latitudes (> 70o where the ozone loss occurs) or whether effects would be substantial at middle and lower latitudes where most of the population resides. For example, the description of Figure 1 in section 2 and the figure caption do not mention that the NOy and ozone calculations are averaged over latitudes > 70oN. One has to look at the labels on the figure to find this. According to lines 109 – 110, “The long-lasting ozone reduction increases UV erythema dose by <5% at mid and low latitudes (Fig. 1c) …” However, according to the green shading in Figure 1c, the KASIMA change in UV exceeds 30% at 20o – 40oN. So this implies substantial effects outside of the polar regions. Similarly, in the Conclusions (lines 240-241), “Ozone loss exceeded 40% around 40 km, with effects on UV radiation and mid-stratospheric temperatures …” But the latitudes where this occurs are not specified (see comment 7 below). Please revise the abstract and the conclusions section to make these descriptions clearer.
Other Comments:
6. The sentence in lines 74 to 76 should be separated into two sentences.
7. In Figure 1, all parts except part (c) are for latitudes > 70N. But part (c) shows the largest increase in UVI at middle and low latitudes. Presumably, this is because the ozone loss in the upper stratosphere also affects the ozone concentration at lower altitudes where dynamical transport can transfer it to lower latitudes. If this is the case, please add text to describe this. Also, a plot of the total ozone change similar to that of Figure 9 of Reddman et al. (2023) would help the reader to understand this better.
8. Figure 2c is a plot of the ozone change in ppmV. However, most previous studies (e.g., Matthes et al., 2017) have shown the change as a percentage of the climatological mean. Please replace this figure with one showing percent change. This would produce a peak at a somewhat higher altitude.
9. Ability to detect an 11-year zonal wind signal could be enhanced in several ways. Doubling the solar cycle UV forcing amplitude in the FOCI experiment was a reasonable attempt but 11-yr zonal wind responses have been detected in other model simulations without resorting to this (e.g., Matthes et al., 2017, their Figure 10 using EMAC and WACCM; Hood et al., 2015, their Figures 10 and 11). Note that a modeled zonal wind signal may be more easily detectable in austral winter due to a more stable polar vortex in that hemisphere.
10. In Figure 3, it is very difficult to distinguish the FOCI lines from the F10.7 lines (both gray).
11. In Figure 3a, there is a strong stratopause temperature dip in ~ 1993. Could this be related to dynamical effects of the Pinatubo eruption? Were volcanic aerosol injections included in the model setup?
12. On p. 9, the last sentence (lines 190-191) is very difficult to understand. Please re-phrase.
13. Discussion of Figure 5 in lines 209-223 on p. 11: Presumably these effects are all a consequence of TSI variability and are not affected by the stratospheric effects of UV forcing. If so, please state that this is the case.
14. In Figure 5, the labels (a, b, etc.) are inconsistent with what is stated in the caption and in the text.
15. Section 5 (Conclusions). The short paragraph on solar signals of the 11-yr solar cycle (lines 245-249) is not very informative. As requested in comment 4 above, this component of the paper (section 3) either needs to be removed or augmented by carrying out new simulations of the type described there. A detailed comparison with previous results of SolarMIP and Matthes et al. (2017) should be provided.
16. In section A2.2, the method of determining solar maximum and solar minimum years is described in lines 390-395. Please state what the mean difference is in F10.7 flux units when averaged over all of the cycles considered here. It appears to be ~ 70 or 80 but whatever it is should be stated and the value should be compared to the effective values considered in previous studies (e.g., Matthes et al., 2017).
17. F10.7 is measured only back to about 1947. How was F10.7 determined for years back to 1850? Please explain. Is it possible that the early cycles are being underestimated?
18. In the title, “State-of-the-Art” should be replaced with “Chemistry-Climate Model” or just “Modeling”. “State-of-the-art” should only be used to describe the models that are being used. It should be left to others to decide if the modeling study itself is state-of-the-art.