the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 29 Jul 2025
Assessing the Impact of Solar Climate Intervention on Future U.S. Weather Using a Convection-Permitting WRF Model
Abstract. A primary solar climate intervention (SCI) strategy is stratospheric aerosol injection (SAI). SAI would increase the number of small reflective particles (aerosols) in the upper atmosphere to reduce climate warming by reflecting more incoming solar radiation away from Earth. Research on SCI is growing quickly, but no studies to date have examined the impact of SCI on severe storms using a mesoscale weather model. In this study, we develop a novel framework using the convection-permitting (4-km resolution) Weather Research & Forecasting (WRF) model to assess the potential impact of SCI on future convective weather over the contiguous United States (CONUS). We conduct three types of simulations for the March–August 2011 period, during which widespread convective outbreaks occurred across the CONUS: (1) a control simulation driven by ERA-5 reanalysis; (2) a Pseudo-Global Warming (PGW) simulation representing a future with increasing greenhouse gas concentrations but without SCI; and (3) a novel Pseudo-SAI (PSAI) simulation representing a future with SCI. Future climate perturbations applied to the PGW and PSAI boundary conditions are derived from ensemble-mean differences between baseline and future scenarios in Community Earth System Model (CESM) experiments with and without SCI. These perturbations are taken from two CESM projects featuring different scenarios: the Geoengineering Large Ensemble (GLENS) and the Assessing Responses and Impacts of Solar Climate Intervention on the Earth System with Stratospheric Aerosol Injection (ARISE). The PSAI simulation includes an additional aerosol optical depth perturbation to represent the shortwave radiative impact of SAI. This paper presents the novel experimental design and modeling framework, and shares preliminary results that highlight the feasibility and scientific potential of this approach for assessing potential weather-scale impacts of SCI. In particular, we show that global warming leads to an increase in extreme precipitation and more frequent deep convection over the Eastern U.S., both of which can be mitigated by SAI deployment.
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Status: open (until 26 Dec 2025)
- CC1: 'Comment on egusphere-2025-3490', Long Cao, 16 Aug 2025 reply
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RC1: 'Comment on egusphere-2025-3490', Chaochao Gao, 29 Sep 2025
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The manuscript titled “Assessing the Impact of Solar Climate Intervention on Future U.S. Weather Using a Convection-Permitting WRF Model” aims to examine the impact of SCI on severe storms over the contiguous United States, by developing a pseudo dynamical downscaling technique and applying it in parallel to the global warming and climate intervention simulations. The methodology is novel in its application and the results are sound. I therefore recommend acceptance of this study after addressing the following issues:
1.Please provide the necessary details about the WRF simulation, for example, how many ensembles are run for each scenarios? Are they all using the same initial boundary conditions? What are the starting and ending date of each ensemble, March to August?
2.Please describe in more detail the pronounced difference between the observations, the CESM, and WRF outputs, i.e., the warming/cooling and drying model biases in your study region (Figure 8 in linking to Figure 4), and discuss how would the difference affect your results.
3.Figure 9, please consider use the log-scale for Y-axis, so that the results are more distinguishable.
4.The region in Figure 10, i.e., the central America is where WRF show strong discrepancy (biases) from either the observation and the CESM results. Please discuss and justify how reliable these results are.
5.Please provide some seasonal breakup results , for example MAM and JJA, especially for the storm activities. Discuss the similarity or difference of SAI mitigation effect, and the potential mechanisms.
6.The use of “March-August 2011” in Table 2 and the caption of Figure 11 may cause unnecessary confusion. Please setup a specific subsection describing this “case study”, by providing comprehensive information about all the storms occurred during this 6-month period, where individual event like the tornado super outbreak occurred, the intensity of these storms, etc. Then come up with a better naming of this “psedo event” under global warming and SAI-mitigated scenarios.
Citation: https://doi.org/10.5194/egusphere-2025-3490-RC1 -
RC2: 'Comment on egusphere-2025-3490', Anonymous Referee #2, 08 Dec 2025
reply
Assessing the Impact of Solar Climate Intervention on Future U.S. Weather Using a Convection-Permitting WRF Model, Sun et al.
The authors have used existing ensemble simulations covering 2010-2099 of scenarios of future global warming and future global warming plus SAI to provide different lateral boundary conditions for the WRF regional model over the CONUS region. They do so to use a convection permitting model to examine the impacts on storms of a future world under global warming and SAI by simulating a single March-August period under 2011 conditions, global warming, and global warming plus SAI conditions. This pseudo global warming technique is not new, but the authors have extended it to SAI simulations and present some initial results.
The paper is well written and of interest to the scientific community. However, I have the following comments:
General – There are several figures in the manuscript that are of little value (see detailed comments below), whereas the comparison of results from the global models and the WRF convection permitting model were not made clear for precipitation changes. I understand that some features of precipitation are known to be poorly modelled by global climate models and therefore some of the metrics may not work so well for those models. However, it would have been interesting to see the comparison, at least of the mean or perhaps a 90th percentile precipitation. Some discussion of how CESM implements SAI compared to how it is done in WFR (taking the extra AOD signal from CESM simulations) is required.
Detailed comments:
Line 57-63: Can you briefly state the impacts on the hydrological cycle seen with previous studies.
Fig 1: This is showing NDSEV data that you have calculated from the ARISE and GLENS data and does not really give more insight than what you have described and what is shown in the Glade 2023 paper with MUCAPE, MUCIN, SO6, and CAPESO6 metrics. I feel this is not the place for this figure given that this is the introduction. Given that this paper is concerned with the CONUS region, it would be better to show this data averaged over the CONUS region for the WRF simulations as well as the original GLENS and ARISE simulations in the results section on precipitation. Alternatively, this figure as is could be moved to supplementary material.
Fig 2: This is simply showing the global mean temperature curves for the different ARISE and GLENS simulations which is published already and referred to in the text. Therefore, I don’t believe this adds value to this paper. The amount of global warming by 2100 could be mentioned in the text.
Fig 3: What is the red box?
Fig 5: What is the vertical dashed line?
Line 238: This sentence is repeated in line 242.
Line 260: I am not sure what is the novel simulation technique that you developed to allow comparison of current and future storms? The PGW technique has been used before.
Line 265-267: It would be better to have this just before section 4.1 as it applies to temperature and precipitation.
All figures showing anomalies: can the captions and titles in the panels make it clear that these are anomalies. The caption describes how the GLENS and ARISE anomalies are calculated but not the WRF anomalies. Please add.
Line 295: Could the extra surface cooling in GLENS-PSAI compared to GLENS-SAI be related to how SAI has been implemented in WRF compared to how it is done in CESM? I have not found a description of how it is done in CESM. Also, in CESM simulations there may have been changes in aerosol in the troposphere caused by the SAI which were not included in WRF. Please comment on this.
Section 4.2: Can you see similar matching patterns for mean precipitation in the same type of plot as Fig 8? Or if you are interested in extreme rainfall, you could look at rainfall over the 90th percentile of the historical/control simulation seen in each simulation type.
Fig 9: Can you see the same in GLENS and ARISE averaged over the same domain? I imagine GLENS and ARISE will not have the very high rainfall rates but you might see a similar pattern.
Fig 10: why are the maps zoomed in compared to all the others? There are no coastlines or latitude/longitudes so difficult to see where this is. GLENS-PGW has a similar signal to ARISE-PGW.
Fig11 and 12: Could an equivalent measure for GLENS and ARISE GW and SAI be shown even if the highest echo tops and reflectivities are lower for the global models?
Lines 429-430: Multiple years with a convection permitting model has been done using the UKMO model -
https://journals.ametsoc.org/view/journals/bams/102/6/BAMS-D-20-0020.1.xml
Line 437-438: stratospheric aerosols do fall out over a few years.
Line 441-446: I think extending the PGW to SAI only really involved adding the AOD forcing. So initial results comparing the WRF convection permitting simulations with the global CESM simulations are of interest.
Line 446-449: I believe only 1 season was simulated with WRF. Do you intend in future to simulate ensembles or multiple years either by taking each year 2060-2069 compared to baseline and using those anomalies to apply to ERA5 2011 or by using your existing mean anomalies and applying to different ERA5 years?
Citation: https://doi.org/10.5194/egusphere-2025-3490-RC2
Data sets
Global Climate Model Model codes for “Assessing the impact of solar climate intervention on future U.S. weather using a convection-permitting model” Lantao Sun https://doi.org/10.5281/zenodo.16374758
WRF data for "Assessing the Impact of Solar Climate Intervention on Future U.S. Weather Using a Convection-Permitting WRF Model" Lantao Sun https://doi.org/10.5281/zenodo.16376739
Data for: Assessing the Impact of Solar Climate Intervention on Future U.S. Weather Using a Convection-Permitting WRF Model Lantao Sun https://doi.org/10.5281/zenodo.16062478
Model code and software
Model codes for "Assessing the Impact of Solar Climate Intervention on Future U.S. Weather Using a Convection-Permitting WRF Model" Lantao Sun https://doi.org/10.5281/zenodo.16374211
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- 1
This study examined potential effect of SAI on future convective storms over the conterminous United States. The authors utilized global climate model (CESM) simulation results of stratospheric aerosol injection (SAI) to drive the mesoscale regional weather model, WRF. Two sets of ensemble SAI simulation results are used: GLENS and ARISE. The CESM simulated climate change are added to ERA5 data to drive WRF with a horizonal resolution of 4km. The novelty of this study lies in the fact that only a few studies examined the effect of SAI on the thermodynamic environments relevant to weather pattern, and no studies have examined how SAI would affect mesoscale weather using a convective permitting weather model. This study found that SAI could mitigate warming, extreme precipitation, and intense convective activities. I recommend publication after the following comments are addressed:
Lines 35-38: It might not be appropriate to emphasize a single country’s policy in a scientific paper that is not devoted to policy discussion.
Lines 51-52: It would be helpful to briefly describe the experiment design and strategy for GeoMIP and GLENS simulations. This is important because all climate response to SAI would be dependent on the SAI strategy.
Lines 70-77: It’s a bit unconventional to have a ‘result’ figure (Figure. 1) in the Introduction part.
Line 103: What is ‘delta signal’ ? This should be elaborated more.
Lines 104-105: “This results in future thermodynamic environments for the same weather events simulated in the control run.” I don’t quite understand this sentence. Please rephrase.
Line 191: What is the horizonal resolution for ERA5 reanalysis and ARISE and GLENS output? I believe some data interpolation have been done before adding simulated climate change signal to ERA5. This information would be useful.
Line 206: How to modify relative humidity? Please explain
Line 276: Stratospheric aerosol absorb infrared and longwave radiation.
Line 366: What is ‘RR’ in equations (1) and (2)?