| 19 Jun 2026
Cleaner air, drier land: the unintended drought consequences of near-term climate forcers mitigation
Abstract. Drought poses severe threats to water resources, ecosystems, and socioeconomic well-being worldwide. While greenhouse gas (GHG) emissions are the primary driver of global warming and the associated intensification of the hydrological cycle, the role of non-methane near-term climate forcers (NTCFs) — encompassing aerosols and their precursors, ozone-forming reactive gases, and other short-lived species — in modulating regional drought risk remains poorly constrained, particularly in arid and semi-arid regions where aerosol-induced radiative effects and circulation feedbacks interact non-linearly with the water balance. Here we employ seven Earth System Models from the CMIP6 AerChemMIP framework to quantify the contribution of NTCF emissions to drought evolution under two future pathways that share identical GHG forcing but differ in the stringency of NTCF controls: SSP3-7.0 and SSP3-7.0-lowNTCF. Using the Standardised Precipitation Evapotranspiration Index at 3-, 6-, and 12-month timescales, we characterise projected changes in drought frequency, duration, intensity, and severity by mid-21st century and identify the large-scale dynamical mechanisms driving regional responses. NTCF mitigation exerts negligible influence on global-mean drought tendency but produces strongly heterogeneous regional responses, with drought conditions worsening substantially across the Sahel, West Asia, Central Asia, and the Mediterranean, while Southeast Asia, Australia, and Central America experience significant drought reductions. These findings are robust across the majority of models and highlight that air quality policies carry regionally differentiated and sometimes counterintuitive hydrological consequences that must be considered alongside their climate and health co-benefits.
Review of “Cleaner air, drier land: the unintended drought consequences of near-term climate forcers mitigation” by Zhou et al.
Summary
This paper uses AerChemMIP simulations to quantify the effects of NTCF mitigation on droughts (frequency, intensity, duration) using the SPEI. Although a global signal is absent, there are large and contrasting regional effects (drought conditions exacerbated in many regions, but mitigated in others). In particular, drought conditions worsen across the Sahel, West Asia, Central Asia and the Mediterranean whereas drought conditions improve across SE Asia, Central America and Australia. The authors then go on to discuss the associated mechanisms, emphasizing the role of large-scale atmospheric dynamics (e.g., remote regions with mid-tropospheric subsidence), while also presenting a population weighted analysis to quantify exposure to droughts. This paper nicely points out the contrasting regional impacts of NTCF mitigation on drought characteristics, which has not received much attention. As such, this paper is an important contribution. The paper is comprehensive, nicely organized and well written, with clear figures (outside of Fig 8). I only have a small number of minor comments.
Specific Comments
L62 “Mitigating NTCFs is therefore critical not only for climate…” --> but this accelerates warming?
L74. “Numerous studies have explored the climate impacts of NTCF mitigation, with most focusing on aerosol reductions” --> what about methane? There’s the Global Methane Pledge for example. Also, the cited Allen et al. 2021 paper uses the same AerChemMIP models and the ssp370-lowNTCFCH4 experiments to quantify the effects of methane mitigation alone.
Introduction. Are there past studies that have focused on the main topic of this paper, i.e., the effects of NTCFs or aerosols on drought? If yes, some brief information would be helpful. If not, then this further motivates the topic of this paper.
L111. “This provides an upper-bound estimate of NTCF-driven changes …” yes, and this is also related to the fact the baseline ssp370 experiment features (weak) increases in most NTCFs (as is noted later).
L214. “and the wetting signal over monsoon regions and high northern latitudes” --> this looks to be occurring over China, might want to note this here as a prominent case in point?
L284, “are already positive under SSP3-7.0, effectively compounding the GHG-driven drying” and similar “GHG-driven” verbiage. When discussing the ssp370 experiment above, you may want to explicitly say that this experiment is subsequently used to diagnose GHG-driven changes.
Figure 8 does well to present a lot of data in a concise way. However, some of the numbers are too small to read. It’s also hard to differentiate italics versus non-italics. I assume the color of each box is also indicative of the number, with warm colors indicating an increase and blue colors indicating a decrease. However, I’m also a bit confused by some of the numbers, which do not seem to match the color. For example, under the lower panel for annual mean changes, the second box for intensity is orange (indicating an increase) but the number is -0.05. There are many similar examples. I am either misinterpreting the figure, or there is an error?
Supp Table 1. Why only 7 models? There are more. For example, CESM2-WACCM should have the relevant simulations?