the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 31 Mar 2026
Can Aerosols improve Urban Flood Prediction? A case study of 2015 Chennai extreme event
Abstract. In December 2015, Chennai, a coastal megacity in India, faced an extreme precipitation-flooding event (EPF) that triggered a devastating 1-in-100-year flood. Several previous attempts failed to accurately simulate the spatiotemporal variability of this EPF at the urban basin scale. Even though incorporating aerosols into operational weather models can improve the accuracy of EPF simulations, it is often ignored due to its computational cost. To address this, we conducted ensemble experiments to highlight the significance of aerosol-cloud interactions in simulating this EPF. In that regard, we use a computationally intensive, high-resolution WRF model configured in large-eddy simulation (LES) mode to represent the interactions in the complex urban microphysics. The results indicate that explicit aerosol representation significantly influenced the microphysics-dynamics interaction during the 2015 EPF and produced rainfall patterns in closer agreement with satellite and rain gauge observations, with basin-scale improvement of ~22 %. Further, employing simulated rainfall in a coupled hydrologic-hydraulic modeling framework increased inundation accuracy by ~50 %. Thus, this study suggests that explicit aerosol representation can improve the space-time simulation of rainfall and flooding for the EPF in Chennai and potentially for similar coastal megacities.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-1218', Mirela-Adriana Anghelache, 21 Jul 2026
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RC2: 'Comment on egusphere-2026-1218', Anonymous Referee #2, 21 Jul 2026
This paper is about a single extreme precipitation event in a small area and its sensitivity to aerosols being represented
in the microphysics. It makes a convincing case that a justified reduction over climatological
aerosols provides a better simulation. Different reduction amounts and an ensemble of initial
conditions seem to provide some robustness to the results which are interpreted physically too.They were also able to demonstrate improvement to inputs for a hydrological model using LES resolutions of 200 m.
The paper is easily understood and close to acceptable as is. I will list some minor points below.
Minor Points
1. p3, line 26. Which of the WRF LES options was used?
2. p7, line 13. Maybe be 3a should be 2g?
3. p10, line 9. Define cold pool intensity.
4. p10, line 12. I think references to Figures 3j and 3k are reversed. Please check.
5. p10, lines 32-33. Looking at Figure 4b-c, I don't know how these percentages are defined. In 4b
the lines are very close to the dashed line, so how is it a 14% error?Citation: https://doi.org/10.5194/egusphere-2026-1218-RC2
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- 1
This study investigates how aerosol concentrations, represented by cloud condensation nuclei (CCN), influence the simulation of an extreme precipitation and flood event over Chennai on 1 December 2015. Using coupled atmospheric, hydrologic, and hydraulic models with ensemble and large-eddy simulations, it shows that reduced CCN concentrations enhance warm-rain processes, improve rainfall timing and magnitude, and lead to more accurate flood predictions. The results highlight the importance of representing aerosol–cloud interactions in extreme precipitation forecasting and their potential value for improving urban flood management and reservoir operation decisions. Overall, the manuscript presents a valuable contribution to the field and is recommended for publication after several revisions to improve the clarity of some arguments and moderate a few claims. The manuscript should definitely include a Conclusions section.
At Chapter 4 - Discussion and Implications:
Cold pools can indeed strengthen with more precipitation—but you should explain the mechanism more clearly. For example: Enhanced warm-rain production increased precipitation reaching the lower tropospehere, where evaporatio of falling raindrops strengthebed cold pools ... just in order the explanations shouldn't be too abrupt.Â
Luine 12: LES experiments further supported these findings instead of  LES experiments further demonstrated; demonstrated is quite strong.
Line 13: ....rainfall magnitude and timing, what abut their metrics?
Line 29: "... establishes quantitative aerosol microphysical plausibility ..."Â
"Plausibility" is not something typically quantified.
Instead:
-Â provides quantitative evidence for aerosol microphysical impacts, or
- provides quantitative support for aerosol microphysical efects, or
- quantifies the aerosol microphysical responseÂ
which sound much more natural.
Line 32:Â in EPF instead on EPF
I suggest replacing "prediction" with "forecasting" in the title. "Forecasting" is the more commonly used term in meteorological and hydrological applications and better reflects the operational implications discussed in the manuscript, particularly regarding improved rainfall forecasts and urban flood management.
As the study is based on a single hindcast of the 2015 Chennai flood event, future work should extend the analysis to other major Indian flood events (e.g., the 2005 Mumbai flood) to assess the robustness and generalizability of the proposed forecasting framework. This phrase can be included in the Conclusions, as well.