the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Air pollution reductions caused by the COVID-19 lockdown open up a way to preserve the Himalayan snow cover
Suvarna Fadnavis
Bernd Heinold
Thazhe Purayil Sabin
Anne Kubin
Wan Ting Katty Huang
Alexandru Rap
Rolf Müller
Abstract. The rapid melting of glaciers in the Hindu Kush Himalayas (HKH) during recent decades poses an alarming threat to water security for lager parts of Asia. If this melting persists, the entire Himalayan glaciers is estimated to disappear by end of 21st century. Here, we assess the influence of the spring 2020 COVID-19 lockdown on the HKH, demonstrating the potential benefits of a strict emission reduction roadmap. Chemistry-climate model simulations, supported by satellite and ground measurements, show that lower air pollution during lockdown led to a reduction in black carbon in snow (2–14 %) and thus in snow melting (10–40 %). This caused increases in snow cover (6–12 %) and mass (2–20 %) and a decrease in runoff (5–55 %) over the HKH and Tibetan Plateau, ultimately leading to an enhanced snow-water-equivalent (3.3–55 %). We emphasize the necessity for immediate anthropogenic pollution reductions to address the hydro-climatic threat to billions of people in South Asia.
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Suvarna Fadnavis et al.
Status: open (until 10 Apr 2023)
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RC1: 'Comment on egusphere-2022-1277', Edward Bair, 04 Mar 2023
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In "Air pollution reductions caused by the COVID-19 lockdown open up a way to preserve the Himalayan snow cover" a chemistry-climate model is used to show that reductions in emissions during the COVID-19 lockdowns led to decreased melt over most of High Mountain Asia. The simulations are supported by remote sensing and in situ aerosol measurements. This work is well motivated, the science is sound, and the results are convincing. I recommend publication subject to minor revisions.
The main issues are:
- The authors need to discuss the limitations of the spatial resolution of their grid size in the ECHAM6-HAMMOZ model (1.875x1.875 deg). This is coarse. For example, Sarangi et al. (2020) use a 12 x 12 km (~ 0.10 degree) grid in WRF-Chem-SNICAR simulations to model LAPs over much of the same region. At 1.875 deg, many of the Himalayan sub ranges are smaller than a pixel, thus the topographic influences, which are always substantial in the mountains, are not accounted for. One usual effect is that snowfall and snow on the ground are underestimated (e.g., Liu et al., 2022). This coarse grid size can impact the anamolies found here as the changes in snow mass are small, at most +16 mm, and the bias in the likely underestimated snow mass may change between the control and COVID simulations because the topography is not fully accounted for.
- The authors find that "pollution changes in COVID-19 lockdown period and associated changes in meteorology has increased snowfall" (l 235-236). I do not understand the mechanism for increased snowfall from emissions reductions. Please elaborate.
- There are many careless typographical and grammatical errors. I've noted many, but not all of these in an annotated PDF. I suggest an English language editing service.
The rest of my comments are minor and are in the attached PDF.
NB 3/3/23
Works cited:
Liu, Y., Fang, Y., Li, D., and Margulis, S. A.: How Well do Global Snow Products Characterize Snow Storage in High Mountain Asia?, Geophysical Research Letters, 49, e2022GL100082, https://doi.org/10.1029/2022GL100082, 2022.
Sarangi, C., Qian, Y., Rittger, K., Ruby Leung, L., Chand, D., Bormann, K. J., and Painter, T. H.: Dust dominates high-altitude snow darkening and melt over high-mountain Asia, Nature Climate Change, 10, 1045-1051, 10.1038/s41558-020-00909-3, 2020.
Suvarna Fadnavis et al.
Suvarna Fadnavis et al.
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