the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 03 Mar 2026
Assessing Earth system responses in deep mitigation scenarios with activity-driven simulation of carbon dioxide removal
Abstract. Assessing Earth system responses arising from carbon dioxide removal (CDR) requires developing and simulating pairs of scenarios – a mitigation scenario with deployment of CDR and a corresponding no-CDR baseline. The latter describes a world where no CDR is deployed, such that net carbon emissions are higher and a given temperature target may be missed. While over the past years a rich literature on deep mitigation scenarios with CDR has been emerging, no-CDR baselines have mostly been explored in stylized Earth system model (ESM) experiments. In such simulations, a no-CDR baseline simply assumes that CDR is “switched off”, while socio-economic constraints are not considered. However, the deployment of CDR in deep mitigation scenarios, created by integrated assessment models (IAMs), is embedded in a consistent socio-economic description of plausible futures, and disallowing CDR may affect climate drivers due to changes in the energy system and in land-use dynamics. Particularly, when moving towards an activity-driven representation of CDR in emission-driven ESMs, where the activity that draws down CO2 from the atmosphere is explicitly modelled, the creation of no-CDR baselines comes with challenges and trade-offs. Here, we conceptualize a framework for emission-driven ESM simulations of IAM scenarios that allows us to determine carbon-cycle and biogeophysical feedbacks of CDR deployment using no-CDR baselines. We show that different options exist for the creation of no-CDR baselines, which offer different insights and have their specific advantages and limitations. We also demonstrate that internal variability of the climate system inherently limits our ability to detect the small signals related to CDR deployment and its feedbacks. Hence, unless a sufficiently large initial conditions ensemble is employed, stylized modelling approaches may remain preferable for some applications, e.g., the quantification of regional biogeophysical effects of CDR deployment.
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Status: open (until 26 Apr 2026)
- RC1: 'Comment on egusphere-2026-833', Irina Melnikova, 06 Apr 2026 reply
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- 1
In this manuscript, Schwinger et al. discuss the challenges of representing carbon dioxide removal (CDR) in Earth system models (ESMs) and the resulting inconsistencies with integrated assessment model (IAM) simulations. The authors identify key issues, propose a framework to address them, and provide an example using NorESM2-LM (ESM) and REMIND-MAgPIE (IAM).
This is a timely contribution in the context of the upcoming CMIP7 phase, particularly with respect to CDRMIP. The manuscript is clearly written and has the potential to make a significant contribution to both the IAM and ESM communities.
Below, I provide several suggestions for improving the manuscript along with questions that arose during my reading.
In addition, depending on the research question, there may be a need to estimate (e.g., regional) Earth system feedbacks independently of associated socioeconomic or land-use changes, i.e., isolating “pure” Earth system responses to CDR.
While the manuscript does a very good job of explaining the framework itself, I suggest adding a short section or paragraph that explicitly discusses its limitations or intended scope of application and clarifies which sources of uncertainty are included or excluded (especially, taking into account the broad ESM-IAM community, for whom the paper is addressed).
E.g., I speculate that Figure 4a would look about the same if both “CDR” and “no-CDR” were compared but just two perturbed ensemble members of the same “CDR” scenario. This raises the question of whether the illustrated variability is uniquely tied to CDR effects or simply reflects general internal variability.
In addition, the framework involves comparisons between emission-driven and concentration-driven simulations (e.g., for estimating biogeophysical effects), which are also subject to internal variability. I suggest clarifying why interannual variability is particularly critical in the context of CDR. A slight refinement of the text may be sufficient to make this point clearer.
Some other comments/questions:
L 93 “which is always activity-driven in ESMs”: maybe add smth like “see Section …” (reference to a section that provides explanation why A/R is always activity-driven
L126 would the reduction of CO2 be always less than the gross amount removed? Even during early mitigation phases under increasing emissions?
L134 NAR abbreviation. CDR and PCR have “carbon” in abbreviations. Is there any particular reason for not defining Net Atmospheric Carbon Removal or Net Carbon Removal?
Table 1. The absence of symbol for biogeophysical effects made me think whether it should be explained in radiative forcing (or temperature) space? Would including it improve clarity or overly complicate the framework?
Section 3.1.2 A/R was a bit difficult to follow (together with Figure 2, which I still do not understand completely). Maybe first explaining the difference between states and transitions could help?
Equations 9-12. Is the “no-more-active” carbon from BECCS (stored in geological reservoirs) included in delta_Cland?
Figure 3b: what does the difference between yellow and grey lines (B and BS) indicate?
L 514 “reasonable agreement”: is it given for comparing green and purple lines (with about 5 GtC difference)? Does the difference arise because “it takes up to 10-15 years until the full efficiency of an alkalinity addition has been reached” (L516)?