the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 02 Jul 2026
Multi-scenario Hydro-climatic Mean and Peak Responses of Central–South Asia and the Tibetan Plateau to Future Warming and Stratospheric Aerosol Intervention
Abstract. Central–South Asia and the Tibetan Plateau are climate-sensitive regions where water resources are controlled by monsoon, westerlies, and cryosphere processes. This study evaluates hydroclimatic changes across three regimes: moisture-limited Central Asia (west (WCA) and east (ECA)), cryosphere-influenced Tibetan Plateau (TIB), and monsoon-dominated South Asia (SAS), under warming (SSP2-4.5, SSP5-8.5) and solar radiation management (SRM) scenarios with temperature-stabilized (G6-1.5K-SAI and Geo-SAI) and transient forcing (G6solar and G6sulfur) experiments using CESM2-WACCM for 2055–2084 relative to 2015–2034. Warming substantially amplifies annual peak hydroclimatic responses, with peak temperature increasing by 24 %, ET by 6.5 %, precipitation by up to 13 % in TIB and SAS, and available water (AW) by 18 %–23 %, alongside accelerated cryosphere melts and enhanced vegetation. In contrast, dry Central Asia shows smaller precipitation and AW increases but remains highly sensitive to evapotranspiration (ET)-driven drying and soil moisture (SM) losses. Temperature-stabilized scenarios provide stronger and more consistent suppression of warming and extremes, while transient forcing scenarios achieve only partial mitigation and retain greater variability. Across regions, SRM generally reduces temperature and ET, produces mixed precipitation responses, and partially restores AW, soil moisture, and cryosphere-related processes. The findings per unit sulfur injected exhibit highest cooling and hydrological efficiency under G6-1.5K-SAI, showing that effectiveness depends on both sulfur loading and injection strategy. SRM also moderates cryosphere loss through enhanced snowfall and reduced snowmelt over the TIB. Warming intensifies seasonal variability and advances peak timing, whereas SRM dampens these shifts to present-day conditions. Precipitation remains the dominant control on AW, indicating that SRM primarily modifies hydroclimatic magnitude rather than underlying water-cycle controls. Overall, SRM reduces hydroclimatic extremes but cannot fully offset regional water stress, and its effectiveness depends on both forcing pathway and intervention strategy, highlighting the need for climate-regime-specific and sulfur-normalized evaluation.
- Preprint
(2812 KB) - Metadata XML
-
Supplement
(634 KB) - BibTeX
- EndNote
Status: open (until 13 Aug 2026)
- RC1: 'Comment on egusphere-2026-3008', Anonymous Referee #1, 04 Jul 2026 reply
-
RC2: 'Comment on egusphere-2026-3008', Anonymous Referee #2, 25 Jul 2026
reply
In this study, the authors analyzed hydroclimate responses of Central–South Asia and the Tibetan Plateau to stratospheric aerosol injection (SAI), a proposed geoengineering method to reduce anthropogenic warming. The authors used a set of different SAI experiment results from CESM model simulations. These SAI simulations differ in the targeting temperature level, injection location, and background scenarios. In specific, 1) G6-1.5K-SAI injects SO2 at two subtropical latitudes with the aim of stabilizing global warming at 1.5K under the background scenario of SSP2-4.5; 2) G6solar directly reduces solar irradiance to bring global mean warming under the background scenario of SSP5-8.5 to the level of SSP2-4.5; 3) G6-sulfur injects SO2 into the tropical lower stratosphere with the aim of bringing down global mean warming under the background scenario of SSP5-8.5 to the level of SSP2-4.5; 4) Geo-SAI injects SO2 at four points (30NS and 15NS) with the aim of stabilizing global warming at 1.5K under the background scenario of SSP2-8.5.
The authors focus on analyzing the mean and peak response of the regional hydroclimate in response to multiple scenarios and strategies of SAI. This study, if well done and well written, could be a useful contribution to the geoengineering and climate change community. It would help to understand regional climate response to different SAI strategies. However, the current presentation of this study is poor. Most part of this manuscript is lengthy (and repetitive) descriptions of facts. After reading through the manuscript, I see a lot of lengthy discussions on the response of different climate variables in different regions to GHG forcing and SAI forcing, but I find little new scientific insights. I think the problem is that too much similar information is listed with little focus. I think this study needs to be re-written and condensed by making main messages more salient.
Specific comments:
Line 25 (abstract): Temperature change is usually not expressed by percent.
Lines 29-31 (abstract): By stating transient forcing scenario achieve only partial mitigation, it feels like temperature stabilized simulations would achieve fully mitigation. That is obviously not true. The difference in ‘stabilized’ and ‘transient’ simulations are different cooling target for SAI. Thus, the naming of ‘stabilized’ and ‘transient’ simulations would just cause confusion.
Line 65： ‘SRM’ has not been defined. Also, there is no introduction of SRM here, which breaks the logic of this paragraph.
Line 85: A robust increase of what?
Line 95: If only two citations are given for the broad concept of SRM, these two papers cannot represent the broad SRM research.
Lines 136-138: I don’t think the naming of ‘transient’ (G6solar and G6sulfur) and ‘temperature-stabilized’ (G6-1.5K-SAI and Geo-SAI) experiments make much sense. All SSP and SAI simulations are transient forcing experiments. These naming are just confusion. The difference between ‘transient’ (G6solar and G6sulfur) and ‘temperature-stabilized’ are just the targeted temperature level for these different SAI simulations. There are no underlying dynamic difference between ‘transient’ and ‘stabilized’ runs here.
Line 138: There is no need to use AW for available water.
Lines 150-194: There is no need to give this much space for the introduction of the regions studied.
Line 225: Readers want to know what is the starting date of SAI in these simulations. Why not just state it clearly?
Lines 283-286: normalization of hydroclimatic responses by the amount of sulfur injection imply that hydroclimate variables considered here would change linearly with the amount of SAI, but it won’t be true. Please comment.
Line 288: For leaf area index (LAI), do some of these models include dynamic vegetation? This should be clarified. Static vegetation vs. dynamic vegetation would have different effects on LAI.
Lines 365-366: decrease and reduce relative to what?
Lines 358-387: This description is a bit hard for me to digest. I suggest re-organize it to focus on the main point.
Lines 430-433:
“These results demonstrate that regional hydroclimatic impacts of SAI cannot be inferred from global averages XX’
This conclusion is self-evident and one does not need to infer it from the results shown here.
Overall, I feel the section of 3.1 and 3.2 is boring. It lists a lot of facts without providing much scientific insights. I suggest condense these sections to focus on the new findings.
Lines 437-440: I have difficulty in understanding what is stated here.
Again, I find section 3.1, 3.2, 3.3, and 3.4 is really boring to read. It’s really hard for me to digest the main message conveyed. It’s just a lengthy description of facts. I suggest condense/combine these sections to make the main point more salient. By reading these four sub-sections, I just got lost.
Section 3.5: Are these seasonal cycles detrended from their respective annual mean?
Lines 576-580: As commented above, the difference between ‘transient’ (G6solar and G6sulfur) and ‘temperature-stabilized’ are just the targeted temperature level for these different SAI simulations. There are no underlying dynamic differences between ‘transient’ and ‘stabilized’ simulations here. But these statements read like there are some dynamic reasons that cause the different roles of precipitation in AW between ‘stabilized’ and ‘transient’ simulations.
Section 4.1 and 4.2
It does not make much sense to have such lengthy sections in the Discussion part. Why not condense them and merge most parts into Result section? Currently, they are just lengthy descriptions without focus. Discussion section should not be written like that.
Figure 2 (and other relevant figures): The current layout of different lines should be re-considered. For example, I don’t see the logic here by showing the lines of G6solar and ‘G6sulfur-SSP4.5’ and ‘G6sulfur-SSP8.5’ together. If the authors want to compare G6solar and G6sulfur, the authors should plot G6solar and G6sulfur together.
Figure 4: What is the unit of each variable for each panel?
Figure 5: This figure just shows changes in terms of percent for the same variables of Figure 4. If so, I suggest put this one in supporting material. Also, usually, temperature change is not represented in precent.
Figure 7: I think here relative importance only represents the magnitude, but not the sign of contribution of each factor?
Now, solar radiation modification is usually used to refer to SRM, but in the manuscript, solar radiation modification and solar radiation management are both used.
Table S2: I suggest add a column listing starting year of SAI.
Citation: https://doi.org/10.5194/egusphere-2026-3008-RC2
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 62 | 30 | 10 | 102 | 11 | 13 | 16 |
- HTML: 62
- PDF: 30
- XML: 10
- Total: 102
- Supplement: 11
- BibTeX: 13
- EndNote: 16
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Review Report (egusphere-2026-3008 (ESD))
Manuscript Title: “Multi-scenario Hydro-climatic Mean and Peak Responses of Central–South Asia and the Tibetan Plateau to Future Warming and Stratospheric Aerosol Intervention”.
General Assessment
Dear Editor, thank you for providing me a chance to review the above-mentioned manuscript draft. I have critically reviewed it and provide constructive comments to authors, which I believe significantly improves the manuscript’s quality and increases reader’s and scientific community interest. This manuscript presents a comprehensive analysis of hydroclimatic responses to multiple Stratospheric Aerosol Injection (SAI) and solar radiation modification (SRM) experiments using CESM2-WACCM simulations under the GeoMIP framework. The study focuses on regional hydroclimatic changes over Asia, including the Tibetan Plateau, Central Asia, and monsoon-dominated regions, and introduces sulfur-normalized efficiency metrics and “available water” (AW) diagnostics.
The topic is relevant to current SRM research and climate intervention assessment. The use of multiple GeoMIP-style experiments (G6solar, G6sulfur, Geo-SAI, and G6-1.5K-SAI) strengthen this draft. However, the manuscript in its current form suffers from methodological inconsistencies, insufficient justification of derived metrics, and overstated physical interpretations of statistical diagnostics. Furthermore, its novelty relative to existing GeoMIP literature is not clearly established.
I recommend major revision before the manuscript can be considered for publication.
Major Comments
The manuscript does not sufficiently distinguish its contribution from prior SRM and GeoMIP studies, particularly:
The analysis framework used here (CESM2-WACCM, G6 experiments, precipitation–evapotranspiration diagnostics, and regional hydroclimatic partitioning) is largely consistent with existing literature, with incremental rather than transformative novelty.
Required revision:
The authors must clearly articulate:
Without this, the manuscript risks being perceived as a regional re-analysis of established GeoMIP outputs rather than a novel contribution.
The manuscript defines AW as:
AW = Precipitation − Evapotranspiration
This is problematic because:
Yet the manuscript repeatedly interprets AW as:
Required revision:
The authors must:
Failure to do so leads to systematic over-interpretation of model output.
The manuscript introduces sulfur-normalized response metrics to evaluate SRM “efficiency.” However:
This raises concerns about physical interpretability and comparability across experiments.
Required revision:
The authors must:
A critical methodological issue arises from the use of inconsistent baselines:
Despite acknowledgment, the manuscript still:
This introduces structural bias.
Required revision:
The authors must either:
Several statements in the manuscript imply causality beyond what is supported by the experimental design, such as:
However, SRM impacts in CESM2-WACCM are:
Required revision:
The discussion must:
The manuscript does not adequately address:
Given SRM sensitivity to variability, this is a major omission.
Required revision:
Include:
The multiple linear regression (MLR) framework shows:
This suggests the model may be:
Required revision:
Minor Comments
Overall Recommendation
I strongly recommend authors to thoroughly revised the manuscript draft by keeping in mind the detailed comments raised above with major and minor revisions. I am recommending major revisions to authors.