the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Modeling study of the snow darkening effect by black carbon deposition over the Arctic during the melting period
Abstract. The rapid warming of the Arctic, accompanied by glacier and sea ice melt, has significant consequences for the Earth's climate, ecosystems, and economy. Recent evidence suggests that the snow-darkening effect (SDE) induced by light-absorbing particles, such as black carbon (BC) deposition, could greatly influence rapid warming in the Arctic. However, there is still a lack of ensemble simulations using high-resolution models for investigating the impacts of the SDE resulting from BC deposition on the Arctic surface energy balance. By integrating the physically based Snow, Ice, Aerosol, and Radiation (SNICAR) model with a polar-optimized version of the Weather Research and Forecasting model (Polar-WRF), this study aimed to quantify the impacts of the SDE due to BC deposition and analyze the relationship between BC aerosol mass in snow (represented by snow depth) and snow albedo reduction. The simulation results indicate that BC deposition can directly affect the surface energy balance by decreasing snow albedo and its corresponding radiative forcing (RF). On average, BC deposition at 50 ng g-1 causes a radiative forcing (RF) of 1.6 W m-2 in off-line simulations (without surface feedbacks) and 1.4 W m-2 in on-line simulations (with surface feedbacks). The high RF caused by BC deposition reached 1–4 W m-2 and mainly occurred in Greenland, Baffin Island and East Siberia, where areas with deep snow depths and large snow densities are prevalent. The changes in snow albedo are indeed strongly linked to the mass of BC aerosols. Notably, a clear linear relationship was established between snow depth and the reduction in snow albedo, with a correlation coefficient exceeding 0.9 and an R-squared value greater than 0.85 when the snow depth is shallow. However, as snow depth increases, the impact of BC on snow albedo gradually diminishes until it reaches its maximum value when the snowpack becomes sufficiently optically thick. Regions with deep snowpack, such as Greenland, tend to exhibit greater sensitivity to BC deposition due to the higher absolute mass of BC and the longer duration of the SDE. For a given column-mean BC concentration in snow, the impacts of the SDE are approximately 25–41 % greater in deep snow-covered areas than in shallow snow-covered areas, leading to a 19–40 % increase in snowmelt. A comparison between off-line and on-line coupled simulations using Polar-WRF/Noah-MP and SNICAR has provided valuable insights into the critical mechanisms and key factors influencing changes in surface heat transfer due to the impacts of the SDE induced by BC deposition in the Arctic. It has been observed that various processes, such as snow melting and land‒atmosphere interactions, play significant roles in assessing changes in the surface energy balance caused by BC deposition. Notably, off-line simulations tend to overestimate the impacts of the SDE, sometimes by more than 50 %, due to the lack of relevant processes. This study emphasized the importance of the impacts of snow conditions and land‒atmosphere interactions on evaluating the impacts of the SDE by BC deposition. It is therefore necessary to prioritize high-resolution modeling studies that incorporate detailed physical processes to enhance our understanding of the impacts of the SDE on Arctic climate change.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2024-1717', Anonymous Referee #1, 21 Jul 2024
General comments
Black carbon (BC) aerosols have significant impacts on earth system radiative balance due to its strong light-absorbing properties in the visible wavelength. Once BC deposited in snow, it accelerates snow melting, and further impacts the climate. In this study, a physically based snow radiative model was coupled into Polar-WRF to investigate the SDE of BC in the arctic region. The topic is interesting, however, this manuscript cannot be published in the current state, the authors need to resolved several major issues before it can be reconsidered. Please see my comments in detail below.
- Title of the manuscript underlines the time period is melting season, however I do not see any significance of snow melting in the manuscript. The biggest problem is that the authors did not take BC amplification effects during melting period into modeling. The authors have to solve this issue before it can be reconsidered by ACP. See Flanner et al., JGR, 112, D11202, doi:10.1029/2006JD008003, 2007 and Doherty et al., JGR, 118, 5553–5569, doi:10.1002/jgrd.50235, 2013.
- An assumption of 50 ppb was applied in this study, which largely deviates from the real world. The BC mixing ratios in the arctic can vary from <10 to several hundred ppb. See Doherty et al., ACP, 10, 11647–11680, 2010 and Doherty et al., JGR, 120, 11,391–11,400, doi:10.1002/2015JD024018, 2015. Therefore, I think the SDE values reported by the authors are not trusted.
Specific comments
- Abstract: Title of the manuscript is “Modeling study of the snow darkening effect by black carbon deposition over the Arctic during the melting period.” However, I did not see any discussion related to the effects of melting on SDE due to BC in the abstract.
- The abstract is unnecessarily long, needs to be shortened substantially.
- L21: instantaneous RF or daily-averaged RF here? Please clarify.
- L31: What is Noah-MP?
- I think the authors need to clarify in the introduction that why did they want to investigate the SDE during melting season instead of snow accumulation season or stable season? And proper citations are required.
- L98: SSNICAR->SNICAR
- L99: Please briefly describe surface feedbacks in the modeling experiments.
- L105: Please delete “and” after “processes through”.
- L109: What is Noah-LSM? Same for CLASS and BATS in L113-114. I highly suggested the authors generate a list of Abbreviations in the appendix for the readers, too many model names in the manuscript.
- Please think about remove Sec. 3.2. Similar results have been reported in other studies such as He, C. 2022, https://doi.org/10.1071/EN22013, and nothing interesting of the results.
- 3.3: I do not agree with the authors that they used a fixed BC mixing ratios in Arctic snow, and the values about BC RF they reported are with very low confidence.
- 3.4: Where is the BC deposition time series data from? I did not see the data source.
Citation: https://doi.org/10.5194/egusphere-2024-1717-RC1 - AC1: 'Reply on RC1', Zilu Zhang, 12 Sep 2024
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RC2: 'Comment on egusphere-2024-1717', Anonymous Referee #2, 31 Jul 2024
This study investigates the effect of black carbon (BC) on snow surfaces over the Arctic using the Snow, Ice, Aerosol, and Radiation (SNICAR) model online and offline with a polar-optimized version of the Weather Research and Forecasting model (Polar-WRF). The research focuses on an important problem as a better understanding of the impacts of snow conditions and land-atmosphere interactions is critical in more accurately assessing the overall impact of BC in the Arctic. However, there are a few major flaws in the manuscript.
- The modeling seems detached from the reality. Only validation of meteorological factors is included. However, other variables, such as BC concentration, snow depth, surface albedo, runoff, etc, also need to be compared with observations to ensure the numbers are in line with those in the real Earth system in order to generate meaningful results. For example, it is unclear how 50 ng/g is selected as BC mixing ratio. For the existing validation, please provide explanations of the simulated biases, especially temperature and wind direction. Also, observations from the two locations cannot sufficiently represent the whole Arctic condition.
- The manuscript states that weather models with high temporal and spatial resolution and conducting ensemble simulations are important in accurately assessing the impacts of the snow-darkening effect (SDE). However, these statements are not well justified. Also, this research uses a resolution of 27 km, which is not high.
- The manuscript needs a more comprehensive literature review. There are more studies focusing on BC impacts on snow surfaces using SNICAR over the Arctic areas.
- The Mellor-Yamada-Nakanishi-Niino (MYNN) scheme is used to represent the boundary layer. However, modeling the Arctic boundary layer is very challenging. Please explain why the MYNN is selected and how it behaves over the Arctic. Also, do clouds play a role in the simulations?
- Please explain the difference between CLM and Noah-MP, and highlight why Noah-MP is selected.
- A five-day spin up is used. However, it is unclear whether this is sufficient. For example, less variabilities are simulated during the first few days, as shown in the temporal evolution plots. Should these first few days also be considered spin-up?
- Please provide more detailed description about experimental design. For example, which experiments are offline and which ones are online. Also, what’s the meaning of “except for snow depth” etc.
- Please clarify how the model accounts for snow-ice transition. For example, after melting and refreezing, can we still treat the surface as snow? As the study does not account for ice, clarification like this is necessary.
- Section 3.4 is hard to follow. The time series plots show dense information, but the explanations are brief. It is unclear how shallow, moderate, and deep snow depths are defined. There are brief explanations on Line 444, yet information like this should be placed in the beginning of the section and also be expanded on to give a clear background to facilitate a better understanding of the temporal evolutions.
Minor:
- Inconsistent titles in the manuscript and the supplementary materials.
- In the result section, please clarify which results are coming from which experiments.
- Many typos, such as Line 105 “through and”, Line 318 “f-j”, Line 342 “each maximum levels”; Line 481 “shows the how,” etc.
- Please add more descriptions regarding the advantage of Polar-WRF. Simply refereeing to other documents is not good enough to provide a background for this study.
- Please provide brief description of the data downloaded from the Arctic Data Center.
- Line 325, how is the “absolute mass of BC represented by the snow depth”?
- For Section 2.3, please clarify whether the calculations are included in WRF as one of the diagnostics, or are these offline calculations based on modeled results.
- Please clarify “The high RF caused by BC deposition reached 1-4 W m^-2”
Citation: https://doi.org/10.5194/egusphere-2024-1717-RC2 - AC2: 'Reply on RC2', Zilu Zhang, 12 Sep 2024
Data sets
ERA5 European Centre for Medium-Range Weather Forecasts https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5
Fnl-GDAS National Centers for Environmental Prediction https://rda.ucar.edu/datasets/ds084.4/
Model code and software
SNICAR M. G. Flanner https://github.com/mflanner/SNICARv3
WRF model NACR https://github.com/wrf-model/WRF
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