Articles | Volume 25, issue 1
https://doi.org/10.5194/acp-25-1-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-1-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Jan 2025
Research article |
| 03 Jan 2025
| 03 Jan 2025
A numerical sensitivity study on the snow-darkening effect by black carbon deposition over the Arctic in spring
Zilu Zhang
Department of Lower Atmosphere Observation Research (LAOR), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
College of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing, China
Libo Zhou
CORRESPONDING AUTHOR
Department of Lower Atmosphere Observation Research (LAOR), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
College of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing, China
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
College of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing, China
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Related authors
No articles found.
Zhen Peng, Lili Lei, Zhe-Min Tan, Meigen Zhang, Aijun Ding, and Xingxia Kou
Atmos. Chem. Phys., 23, 14505–14520, https://doi.org/10.5194/acp-23-14505-2023, https://doi.org/10.5194/acp-23-14505-2023, 2023
Short summary
Short summary
Annual PM2.5 emissions in China consistently decreased by about 3% to 5% from 2017 to 2020 with spatial variations and seasonal dependencies. High-temporal-resolution and dynamics-based PM2.5 emission estimates provide quantitative diurnal variations for each season. Significant reductions in PM2.5 emissions in the North China Plain and northeast of China in 2020 were caused by COVID-19.
Xingxia Kou, Zhen Peng, Meigen Zhang, Fei Hu, Xiao Han, Ziming Li, and Lili Lei
Atmos. Chem. Phys., 23, 6719–6741, https://doi.org/10.5194/acp-23-6719-2023, https://doi.org/10.5194/acp-23-6719-2023, 2023
Short summary
Short summary
A CMAQ EnSRF-based regional inversion system was extended to resolve satellite retrievals into biogenic source–sink changes. The size of the assimilated biosphere sink in China inferred from GOSAT was −0.47 Pg C yr−1. The biosphere flux at the provincial scale was re-estimated following the refined description in the regional inversion.
Mengying Li, Shaocai Yu, Xue Chen, Zhen Li, Yibo Zhang, Zhe Song, Weiping Liu, Pengfei Li, Xiaoye Zhang, Meigen Zhang, Yele Sun, Zirui Liu, Caiping Sun, Jingkun Jiang, Shuxiao Wang, Benjamin N. Murphy, Kiran Alapaty, Rohit Mathur, Daniel Rosenfeld, and John H. Seinfeld
Atmos. Chem. Phys., 22, 11845–11866, https://doi.org/10.5194/acp-22-11845-2022, https://doi.org/10.5194/acp-22-11845-2022, 2022
Short summary
Short summary
This study constructed an emission inventory of condensable particulate matter (CPM) in China with a focus on organic aerosols (OAs), based on collected CPM emission information. The results show that OA emissions are enhanced twofold for the years 2014 and 2017 after the inclusion of CPM in the new inventory. Sensitivity cases demonstrated the significant contributions of CPM emissions from stationary combustion and mobile sources to primary, secondary, and total OA concentrations.
Cited articles
Abolafia-Rosenzweig, R., He, C., McKenzie Skiles, S., Chen, F., and Gochis, D.: Evaluation and Optimization of Snow Albedo Scheme in Noah-MP Land Surface Model Using In Situ Spectral Observations in the Colorado Rockies, J. Adv. Model. Earth Sy., 14, e2022MS003141, https://doi.org/10.1029/2022MS003141, 2022.
AMAP: AMAP Assessment 2015: Black carbon and ozone as Arctic climate forcers, Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway, 116 pp., ISBN 978-82-7971-092-9, 2015.
AMAP: Impacts of Short-lived Climate Forcers on Arctic Climate, Air Quality, and Human Health. Summary for Policy-makers, Arctic Monitoring and Assessment Programme (AMAP), Tromsø, Norway, 20 pp., https://www.amap.no/documents/download/6760/inline (last access: 21 December 20245), 2021.
Arteaga, D., Planche, C., Tridon, F., Dupuy, R., Baudoux, A., Banson, S., Baray, J.-L., Mioche, G., Ehrlich, A., Mech, M., Mertes, S., Wendisch, M., Wobrock, W., and Jourdan, O.: Arctic mixed-phase clouds simulated by the WRF model: Comparisons with ACLOUD radar and in situ airborne observations and sensitivity of microphysics properties, Atmos. Res., 307, 107471, https://doi.org/10.1016/j.atmosres.2024.107471, 2024.
Barry, R. G., Serreze, M. C., Maslanik, J. A., and Preller, R. H.: The Arctic Sea Ice-Climate System: Observations and modeling, Rev. Geophys., 31, 397–422, https://doi.org/10.1029/93RG01998, 1993.
Bintanja, R., van der Linden, E. C., and Hazeleger, W.: Boundary layer stability and Arctic climate change: a feedback study using EC-Earth, Clim. Dynam., 39, 2659–2673, https://doi.org/10.1007/s00382-011-1272-1, 2012.
Bokhorst, S., Pedersen, S. H., Brucker, L., Anisimov, O., Bjerke, J. W., Brown, R. D., Ehrich, D., Essery, R. L., Heilig, A., Ingvander, S., Johansson, C., Johansson, M., Jonsdottir, I. S., Inga, N., Luojus, K., Macelloni, G., Mariash, H., McLennan, D., Rosqvist, G. N., Sato, A., Savela, H., Schneebeli, M., Sokolov, A., Sokratov, S. A., Terzago, S., Vikhamar-Schuler, D., Williamson, S., Qiu, Y., and Callaghan, T. V.: Changing Arctic snow cover: A review of recent developments and assessment of future needs for observations, modelling, and impacts, Ambio, 45, 516–537, https://doi.org/10.1007/s13280-016-0770-0, 2016.
Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T., DeAngelo, B. J., Flanner, M. G., Ghan, S., Kärcher, B., Koch, D., Kinne, S., Kondo, Y., Quinn, P. K., Sarofim, M. C., Schultz, M. G., Schulz, M., Venkataraman, C., Zhang, H., Zhang, S., Bellouin, N., Guttikunda, S. K., Hopke, P. K., Jacobson, M. Z., Kaiser, J. W., Klimont, Z., Lohmann, U., Schwarz, J. P., Shindell, D., Storelvmo, T., Warren, S. G., and Zender, C. S.: Bounding the role of black carbon in the climate system: A scientific assessment, J. Geophys. Res.-Atmos., 118, 5380–5552, https://doi.org/10.1002/jgrd.50171, 2013.
Bret-Harte, S., Euskirchen, E., and Edgar, C.: Terrestrial carbon, water and energy fluxes measured by eddy covariance, and associated biomet variables, at three adjacent tundra ecosystems at Imnavait Creek, Alaska, 2020, Arctic data center [data set], https://doi.org/10.18739/A2Z02Z983, 2021.
Bromwich, D. H., Hines, K. M., and Bai, L.-S.: Development and testing of Polar Weather Research and Forecasting model: 2. Arctic Ocean, J. Geophys. Res.-Atmos., 114, D08122, https://doi.org/10.1029/2008JD010300, 2009.
Bromwich, D. H., Otieno, F. O., Hines, K. M., Manning, K. W., and Shilo, E.: Comprehensive evaluation of polar weather research and forecasting model performance in the Antarctic, J. Geophys. Res.-Atmos., 118, 274–292, https://doi.org/10.1029/2012JD018139, 2013.
Brun, E.: Investigation on Wet-Snow Metamorphism in Respect of Liquid-Water Content, Ann. Glaciol., 13, 22–26, https://doi.org/10.3189/S0260305500007576, 1989.
Brutsaert, W. A.: Evaporation Into the Atmosphere, D. Reidel, Dordrecht, the Netherlands, 299 pp., ISBN 978-90-481-8365-4, 1982.
Chen, F., Janjić, Z., and Mitchell, K.: Impact of Atmospheric Surface-layer Parameterizations in the new Land-surface Scheme of the NCEP Mesoscale Eta Model, Bound.-Lay. Meteorol., 85, 391–421, https://doi.org/10.1023/A:1000531001463, 1997.
Chen, X., Kang, S., Yang, J., and Ji, Z.: Investigation of black carbon climate effects in the Arctic in winter and spring, Sci. Total Environ., 751, 142145, https://doi.org/10.1016/j.scitotenv.2020.142145, 2021.
Chen, Y., Li, X., Xing, Y., Yan, S., Wu, D., Shi, T., Cui, J., Zhang, X., and Niu, X.: Historical Changes of Black Carbon in Snow and Its Radiative Forcing in CMIP6 Models, Atmosphere-Basel, 13, 1774, https://doi.org/10.3390/atmos13111774, 2022.
Cho, H., Jun, S.-Y., Ho, C.-H., and McFarquhar, G.: Simulations of Winter Arctic Clouds and Associated Radiation Fluxes Using Different Cloud Microphysics Schemes in the Polar WRF: Comparisons With CloudSat, CALIPSO, and CERES, J. Geophys. Res.-Atmos., 125, e2019JD031413, https://doi.org/10.1029/2019JD031413, 2020.
Clarke, A. D., and Noone, K. J.: Soot in the Arctic snowpack: a cause for perturbations in radiative transfer, Atmos. Environ., 19, 2045–2053, https://doi.org/10.1016/0004-6981(85)90113-1, 1985.
Colbeck, S. C.: An overview of seasonal snow metamorphism, Rev. Geophys., 20, 45–61, https://doi.org/10.1029/RG020i001p00045, 1982.
Copernicus Climate Change Service: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2023.
Dada, L., Angot, H., Beck, I., Baccarini, A., Quelever, L. L. J., Boyer, M., Laurila, T., Brasseur, Z., Jozef, G., de Boer, G., Shupe, M. D., Henning, S., Bucci, S., Dutsch, M., Stohl, A., Petaja, T., Daellenbach, K. R., Jokinen, T., and Schmale, J.: A central arctic extreme aerosol event triggered by a warm air-mass intrusion, Nat. Commun., 13, 5290, https://doi.org/10.1038/s41467-022-32872-2, 2022.
Dang, C., Brandt, R. E., and Warren, S. G.: Parameterizations for narrowband and broadband albedo of pure snow and snow containing mineral dust and black carbon, J. Geophys. Res.-Atmos., 120, 5446–5468, https://doi.org/10.1002/2014JD022646, 2015.
Dang, C., Fu, Q., and Warren, S. G.: Effect of Snow Grain Shape on Snow Albedo, J. Atmos. Sci., 73, 3573–3583, https://doi.org/10.1175/JAS-D-15-0276.1, 2016.
Dang, C., Warren, S. G., Fu, Q., Doherty, S. J., Sturm, M., and Su, J.: Measurements of light-absorbing particles in snow across the Arctic, North America, and China: Effects on surface albedo, J. Geophys. Res.-Atmos., 122, 10149–10168, https://doi.org/10.1002/2017jd027070, 2017.
Department of Atmospheric Science: University of Wyoming [data set], https://weather.uwyo.edu/upperair/sounding.html (last access: 21 December 2024), 2014.
Doherty, S. J., Warren, S. G., Grenfell, T. C., Clarke, A. D., and Brandt, R. E.: Light-absorbing impurities in Arctic snow, Atmos. Chem. Phys., 10, 11647–11680, https://doi.org/10.5194/acp-10-11647-2010, 2010.
Doherty, S. J., Grenfell, T. C., Forsström, S., Hegg, D. L., Brandt, R. E., and Warren, S. G.: Observed vertical redistribution of black carbon and other insoluble light-absorbing particles in melting snow, J. Geophys. Res.-Atmos., 118, 5553–5569, https://doi.org/10.1002/jgrd.50235, 2013.
Dou, T., Xiao, C., Shindell, D. T., Liu, J., Eleftheriadis, K., Ming, J., and Qin, D.: The distribution of snow black carbon observed in the Arctic and compared to the GISS-PUCCINI model, Atmos. Chem. Phys., 12, 7995–8007, https://doi.org/10.5194/acp-12-7995-2012, 2012.
Dou, T., Du, Z., Li, S., Zhang, Y., Zhang, Q., Hao, M., Li, C., Tian, B., Ding, M., and Xiao, C.: Brief communication: An alternative method for estimating the scavenging efficiency of black carbon by meltwater over sea ice, The Cryosphere, 13, 3309–3316, https://doi.org/10.5194/tc-13-3309-2019, 2019.
Dou, T.-F., and Xiao, C.-D.: An overview of black carbon deposition and its radiative forcing over the Arctic, Advances in Climate Change Research, 7, 115–122, https://doi.org/10.1016/j.accre.2016.10.003, 2016.
Ek, M. B., Mitchell, K. E., Lin, Y., Rogers, E., Grunmann, P., Koren, V., Gayno, G., and Tarpley, J. D.: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model, J. Geophys. Res.-Atmos., 108, D228851, https://doi.org/10.1029/2002JD003296, 2003.
Flanner, M. G.: Arctic climate sensitivity to local black carbon, J. Geophys. Res.-Atmos., 118, 1840–1851, https://doi.org/10.1002/jgrd.50176, 2013.
Flanner, M. G., and Zender, C. S.: Snowpack radiative heating: Influence on Tibetan Plateau climate, Geophys. Res. Lett., 32, L06501, https://doi.org/10.1029/2004GL022076, 2005.
Flanner, M. G., Zender, C. S., Randerson, J. T., and Rasch, P. J.: Present-day climate forcing and response from black carbon in snow, J. Geophys. Res., 112, D11202, https://doi.org/10.1029/2006jd008003, 2007.
Flanner, M. G., Liu, X., Zhou, C., Penner, J. E., and Jiao, C.: Enhanced solar energy absorption by internally-mixed black carbon in snow grains, Atmos. Chem. Phys., 12, 4699–4721, https://doi.org/10.5194/acp-12-4699-2012, 2012.
Flanner, M. G., Arnheim, J. B., Cook, J. M., Dang, C., He, C., Huang, X., Singh, D., Skiles, S. M., Whicker, C. A., and Zender, C. S.: SNICAR-ADv3: a community tool for modeling spectral snow albedo, Geosci. Model Dev., 14, 7673–7704, https://doi.org/10.5194/gmd-14-7673-2021, 2021.
Forsström, S., Isaksson, E., Skeie, R. B., Ström, J., Pedersen, C. A., Hudson, S. R., Berntsen, T. K., Lihavainen, H., Godtliebsen, F., and Gerland, S.: Elemental carbon measurements in European Arctic snow packs, J. Geophys. Res.-Atmos., 118, 13614—3627, https://doi.org/10.1002/2013jd019886, 2013.
Garratt, J. R.: The atmospheric boundary layer, Cambridge University Press, Cambridge, England, 336 pp., ISBN: 0521467454, 1992.
Guo, H. and Yang, Y.: Spring snow-albedo feedback from satellite observation, reanalysis and model simulations over the Northern Hemisphere, Sci. China Earth Sci., 65, 1463–1476, https://doi.org/10.1007/s11430-021-9913-1, 2022.
Hall, A. and Qu, X.: Using the current seasonal cycle to constrain snow albedo feedback in future climate change, Geophys. Res. Lett., 33, L03502, https://doi.org/10.1029/2005GL025127, 2006.
Hansen, J. and Nazarenko, L.: Soot climate forcing via snow and ice albedos, P. Natl. Acad. Sci. USA, 101, 423–428, https://doi.org/10.1073/pnas.2237157100, 2004.
Hao, D., Bisht, G., Rittger, K., Bair, E., He, C., Huang, H., Dang, C., Stillinger, T., Gu, Y., Wang, H., Qian, Y., and Leung, L. R.: Improving snow albedo modeling in the E3SM land model (version 2.0) and assessing its impacts on snow and surface fluxes over the Tibetan Plateau, Geosci. Model Dev., 16, 75–94, https://doi.org/10.5194/gmd-16-75-2023, 2023.
Haywood, J. M. and Shine, K. P.: The effect of anthropogenic sulfate and soot aerosol on the clear sky planetary radiation budget, Geophys. Res. Lett., 22, 603–606, https://doi.org/10.1029/95GL00075, 1995.
He, C. and Ming, J.: Modelling light-absorbing particle–snow–radiation interactions and impacts on snow albedo: fundamentals, recent advances and future directions, Environ. Chem., 19, 296–311, https://doi.org/10.1071/en22013, 2022.
He, C., Liou, K. N., and Takano, Y.: Resolving Size Distribution of Black Carbon Internally Mixed With Snow: Impact on Snow Optical Properties and Albedo, Geophys. Res. Lett., 45, 2697–2705, https://doi.org/10.1002/2018gl077062, 2018.
He, C., Valayamkunnath, P., Barlage, M., Chen, F., Gochis, D., Cabell, R. S., Schneider, T., Rasmussen, R. M., Niu, G., Yang, Z., Niyogi, D., and Ek, M. B.: The Community Noah-MP Land Surface Modeling System Technical Description Version 5.0, No. NCAR/TN-575+STR, https://doi.org/10.5065/ew8g-yr95, 2023.
He, C., Flanner, M., Lawrence, D. M., and Gu, Y.: New Features and Enhancements in Community Land Model (CLM5) Snow Albedo Modeling: Description, Sensitivity, and Evaluation, J. Adv. Model. Earth Sy., 16, e2023MS003861, https://doi.org/10.1029/2023MS003861, 2024.
Hines, K. M. and Bromwich, D. H.: Development and Testing of Polar Weather Research and Forecasting (WRF) Model. Part I: Greenland Ice Sheet Meteorology, Mon. Weather Rev., 136, 1971–1989, https://doi.org/10.1175/2007MWR2112.1, 2008.
Hines, K. M. and Bromwich, D. H.: Simulation of Late Summer Arctic Clouds during ASCOS with Polar WRF, Mon. Weather Rev., 145, 521–541, https://doi.org/10.1175/MWR-D-16-0079.1, 2017.
Hines, K. M., Bromwich, D. H., Bai, L., Bitz, C. M., Powers, J. G., and Manning, K. W.: Sea Ice Enhancements to Polar WRF, Mon. Weather Rev., 143, 2363–2385, https://doi.org/10.1175/MWR-D-14-00344.1, 2015.
Hines, K. M., Bromwich, D. H., Wang, S.-H., Silber, I., Verlinde, J., and Lubin, D.: Microphysics of summer clouds in central West Antarctica simulated by the Polar Weather Research and Forecasting Model (WRF) and the Antarctic Mesoscale Prediction System (AMPS), Atmos. Chem. Phys., 19, 12431–12454, https://doi.org/10.5194/acp-19-12431-2019, 2019.
Huang, H., Qian, Y., He, C., Bair, E. H., and Rittger, K.: Snow Albedo Feedbacks Enhance Snow Impurity-Induced Radiative Forcing in the Sierra Nevada, Geophys. Res. Lett., 49, e2022GL098102, https://doi.org/10.1029/2022GL098102, 2022.
Huang, L., Gong, S. L., Jia, C. Q., and Lavoué, D.: Importance of deposition processes in simulating the seasonality of the Arctic black carbon aerosol, J. Geophys. Res.-Atmos., 115, D17207, https://doi.org/10.1029/2009JD013478, 2010.
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A., and Collins, W. D.: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models, J. Geophys. Res.-Atmos., 113, D13103, https://doi.org/10.1029/2008JD009944, 2008.
Jacobson, M. Z.: Climate response of fossil fuel and biofuel soot, accounting for soot's feedback to snow and sea ice albedo and emissivity, J. Geophys. Res.-Atmos., 109, D21201, https://doi.org/10.1029/2004JD004945, 2004.
Jiang, Y., Lu, Z., Liu, X., Qian, Y., Zhang, K., Wang, Y., and Yang, X.-Q.: Impacts of global open-fire aerosols on direct radiative, cloud and surface-albedo effects simulated with CAM5, Atmos. Chem. Phys., 16, 14805–14824, https://doi.org/10.5194/acp-16-14805-2016, 2016.
Jiao, C., Flanner, M. G., Balkanski, Y., Bauer, S. E., Bellouin, N., Berntsen, T. K., Bian, H., Carslaw, K. S., Chin, M., De Luca, N., Diehl, T., Ghan, S. J., Iversen, T., Kirkevåg, A., Koch, D., Liu, X., Mann, G. W., Penner, J. E., Pitari, G., Schulz, M., Seland, Ø., Skeie, R. B., Steenrod, S. D., Stier, P., Takemura, T., Tsigaridis, K., van Noije, T., Yun, Y., and Zhang, K.: An AeroCom assessment of black carbon in Arctic snow and sea ice, Atmos. Chem. Phys., 14, 2399–2417, https://doi.org/10.5194/acp-14-2399-2014, 2014.
Justino, F., Wilson, A. B., Bromwich, D. H., Avila, A., Bai, L.-S., and Wang, S.-H.: Northern Hemisphere Extratropical Turbulent Heat Fluxes in ASRv2 and Global Reanalyses, J. Climate, 32, 2145–2166, https://doi.org/10.1175/JCLI-D-18-0535.1, 2019.
Kang, S., Zhang, Y., Qian, Y., and Wang, H.: A review of black carbon in snow and ice and its impact on the cryosphere, Earth-Sci. Rev., 210, 103346, https://doi.org/10.1016/j.earscirev.2020.103346, 2020.
Kitamura, Y.: Modifications to the Mellor-Yamada-Nakanishi-Niino (MYNN) Model for the Stable Stratification Case, J. Meteorol. Soc. Jpn. Ser. II, 88, 857–864, https://doi.org/10.2151/jmsj.2010-506, 2010.
Kurtz, N. T., Galin, N., and Studinger, M.: An improved CryoSat-2 sea ice freeboard retrieval algorithm through the use of waveform fitting, The Cryosphere, 8, 1217–1237, https://doi.org/10.5194/tc-8-1217-2014, 2014.
Lamare, M. L., Lee-Taylor, J., and King, M. D.: The impact of atmospheric mineral aerosol deposition on the albedo of snow & sea ice: are snow and sea ice optical properties more important than mineral aerosol optical properties?, Atmos. Chem. Phys., 16, 843–860, https://doi.org/10.5194/acp-16-843-2016, 2016.
Lau, W. K. M., Sang, J., Kim, M. K., Kim, K. M., Koster, R. D., and Yasunari, T. J.: Impacts of Snow Darkening by Deposition of Light-Absorbing Aerosols on Hydroclimate of Eurasia During Boreal Spring and Summer, J. Geophys. Res.-Atmos., 123, 8441–8461, https://doi.org/10.1029/2018jd028557, 2018.
Li, F., Wan, X., Wang, H., Orsolini, Y. J., Cong, Z., Gao, Y., and Kang, S.: Arctic sea-ice loss intensifies aerosol transport to the Tibetan Plateau, Nat. Clim. Change, 10, 1037–1044, https://doi.org/10.1038/s41558-020-0881-2, 2020.
Li, J., Miao, C., Zhang, G., Fang, Y.-H., Shangguan, W., and Niu, G.-Y.: Global Evaluation of the Noah-MP Land Surface Model and Suggestions for Selecting Parameterization Schemes, J. Geophys. Res.-Atmos., 127, e2021JD035753, https://doi.org/10.1029/2021JD035753, 2022.
Lin, T.-S., He, C. L. , Ronnie, A.-R., Chen, F., Wang, W., Barlage, M., and Gochis, D. J.: Implementation and evaluation of SNICAR snow albedo scheme in Noah-MP (version 5.0) land surface model, Ess Open Archive [preprint], https://doi.org/10.22541/essoar.170612215.54848315/v1, 24 January 2024.
Mellor, G. L. and Yamada, T.: Development of a turbulence closure model for geophysical fluid problems, Rev. Geophys., 20, 851–875, https://doi.org/10.1029/RG020i004p00851, 1982.
Minder, J. R., Letcher, T. W., and Skiles, S. M.: An evaluation of high-resolution regional climate model simulations of snow cover and albedo over the Rocky Mountains, with implications for the simulated snow-albedo feedback, J. Geophys. Res.-Atmos., 121, 9069–9088, https://doi.org/10.1002/2016jd024995, 2016.
Morrison, H. and Gettelman, A.: A New Two-Moment Bulk Stratiform Cloud Microphysics Scheme in the Community Atmosphere Model, Version 3 (CAM3). Part : Description and Numerical Tests, J. Climate, 21, 3642–3659, https://doi.org/10.1175/2008JCLI2105.1, 2008.
Myers, S., Isla, H., Kerby, J. T., Phoenix, G. K., Bjerke, J. W., Epstein, H. E., Assmann, J. J., John, C., Andreu-Hayles, L., Angers-Blondin, S., Beck, P. S. A., Berner, L. T., Bhatt, U. S., Bjorkman, A. D., Blok, D., Bryn, A., Christiansen, C. T., Cornelissen, J. H. C., Cunliffe, A. M., Elmendorf, S. C., Forbes, B. C., Goetz, S. J., Hollister, R. D., de Jong, R., Loranty, M. M., Macias-Fauria, M., Maseyk, K., Normand, S., Olofsson, J., Parker, T. C., Parmentier, F.-J. W., Post, E., Schaepman-Strub, G., Stordal, F., Sullivan, P. F., Thomas, H. J. D., Tømmervik, H., Treharne, R., Tweedie, C. E., Walker, D. A., Wilmking, M., and Wipf, S.: Complexity revealed in the greening of the Arctic, Nat. Clim. Change, 10, 106–117, https://doi.org/10.1038/s41558-019-0688-1, 2020.
Nakanishi, M. and Niino, H.: An Improved Mellor–Yamada Level-3 Model with Condensation Physics: Its Design and Verification, Bound.-Lay. Meteorol., 112, 1–31, https://doi.org/10.1023/B:BOUN.0000020164.04146.98, 2004.
Nakanishi, M. and Niino, H.: An Improved Mellor–Yamada Level-3 Model: Its Numerical Stability and Application to af Advection Fog, Bound.-Lay. Meteorol., 119, 397–407, https://doi.org/10.1007/s10546-005-9030-8, 2006.
Nakanishi, M. and Niino, H.: Development of an Improved Turbulence Closure Model for the Atmospheric Boundary Layer, J. Meteorol. Soc. Jpn. Ser. II, 87, 895–912, https://doi.org/10.2151/jmsj.87.895, 2009.
National Centers for Environmental Prediction, National Weather Service, NOAA, and US Department of Commerce: NCEP FNL Operational Model Global Tropospheric Analyses, continuing from July 1999, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory [data set], https://doi.org/10.5065/D6M043C6, 2000.
National Oceanic and Atmospheric Administration: Global Monitoring Laboratory, National Oceanic and Atmospheric Administration [data set], https://gml.noaa.gov/data/ (last access: 5 December 2024), 2024.
National Snow and Ice Data Center: CryoSat-2 Level-4 Sea Ice Elevation, Freeboard, and Thickness, Version 1, National Snow and Ice Data Center [data set], https://doi.org/10.5067/96JO0KIFDAS8, 2023.
Niu, G.-Y., Yang, Z.-L., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M., Kumar, A., Manning, K., Niyogi, D., Rosero, E., Tewari, M., and Xia, Y.: The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements, J. Geophys. Res.-Atmos., 116, D12109, https://doi.org/10.1029/2010JD015139, 2011.
Oaida, C. M., Xue, Y., Flanner, M. G., Skiles, S. M., De Sales, F., and Painter, T. H.: Improving snow albedo processes in WRF/SSiB regional climate model to assess impact of dust and black carbon in snow on surface energy balance and hydrology over western U.S., J. Geophys. Res.-Atmos., 120, 3228–3248, https://doi.org/10.1002/2014jd022444, 2015.
Olson, J. B., Kenyon, J. S., Angevine, W. A., Brown, J. M., Pagowski, M., and Sušelj, K.: A Description of the MYNN-EDMF Scheme and the Coupling to Other Components in WRF–ARW [Technical Memorandum], NOAA, https://doi.org/10.25923/n9wm-be49, 2019.
Pedersen, C. A., Gallet, J.-C., Ström, J., Gerland, S., Hudson, S. R., Forsström, S., Isaksson, E., and Berntsen, T. K.: In situ observations of black carbon in snow and the corresponding spectral surface albedo reduction, J. Geophys. Res.-Atmos., 120, 1476–1489, https://doi.org/10.1002/2014JD022407, 2015.
Previdi, M., Smith, K. L., and Polvani, L. M.: Arctic amplification of climate change: a review of underlying mechanisms, Environ. Res. Lett., 16, 093003, https://doi.org/10.1088/1748-9326/ac1c29, 2021.
Qian, Y., Yasunari, T. J., Doherty, S. J., Flanner, M. G., Lau, W. K. M., Ming, J., Wang, H., Wang, M., Warren, S. G., and Zhang, R.: Light-absorbing particles in snow and ice: Measurement and modeling of climatic and hydrological impact, Adv. Atmos. Sci., 32, 64–91, https://doi.org/10.1007/s00376-014-0010-0, 2014.
Qian, Y., Yan, H., Berg, L. K., Hagos, S., Feng, Z., Yang, B., and Huang, M.: Assessing Impacts of PBL and Surface Layer Schemes in Simulating the Surface–Atmosphere Interactions and Precipitation over the Tropical Ocean Using Observations from AMIE/DYNAMO, J. Climate, 29, 8191–8210, https://doi.org/10.1175/JCLI-D-16-0040.1, 2016.
Quinn, P. K., Stohl, A., Arneth, A., Berntsen, T. K., Burkhart, J. F., Christensen, J. H., Flanner, M. G., Kupiainen, K. J., Lihavainen, H., Shepherd, M., Shevchenko, V. P., Skov, H., and Vestreng, V.: The Impact of Black Carbon on Arctic Climate, Denmark, 74 pp., ISBN 978-82-7971-069-1, 2011.
Rahimi, S., Liu, X., Zhao, C., Lu, Z., and Lebo, Z. J.: Examining the atmospheric radiative and snow-darkening effects of black carbon and dust across the Rocky Mountains of the United States using WRF-Chem, Atmos. Chem. Phys., 20, 10911–10935, https://doi.org/10.5194/acp-20-10911-2020, 2020.
Ren, L., Yang, Y., Wang, H., Zhang, R., Wang, P., and Liao, H.: Source attribution of Arctic black carbon and sulfate aerosols and associated Arctic surface warming during 1980–2018, Atmos. Chem. Phys., 20, 9067–9085, https://doi.org/10.5194/acp-20-9067-2020, 2020.
Rohde, A., Vogel, H., Hoshyaripour, G. A., Kottmeier, C., and Vogel, B.: Regional Impact of Snow-Darkening on Snow Pack and the Atmosphere During a Severe Saharan Dust Deposition Event in Eurasia, J. Geophys. Res.-Earth, 128, e2022JF007016, https://doi.org/10.1029/2022JF007016, 2023.
Smith, W. L., Hansen, C., Bucholtz, A., Anderson, B., Beckley, M., Corbett, J. G., Cullather, R. I., Hines, K. M., Hofton, M. A., Kato, S., Lubin, D., Moore, R. H., Segal Rosenhaimer, M., Redemann, J., Schmidt, S., Scott, R. C., Song, S., Barrick, J. D. W., Blair, J. B., Bromwich, D. H., Brooks, C., Chen, G., Cornejo, H. G., Corr, C. A., Ham, S. H., Kittelman, A. S., Knappmiller, S. R., LeBlanc, S. E., Loeb, N. G., Miller, C. R., Nguyen, L., Palikonda, R., Rabine, D., Reid, E. A., Richter-Menge, J., Pilewskie, P., Shinozuka, Y., Spangenberg, D. A., Stackhouse, P. W., Taylor, P. C., Thornhill, K. L., van Gilst, D., and Winstead, E. L.: Arctic Radiation-IceBridge Sea and Ice Experiment: The Arctic Radiant Energy System during the Critical Seasonal Ice Transition, B. Am. Meteorol. Soc., 98, 1399–1426, https://doi.org/10.1175/BAMS-D-14-00277.1, 2017.
Toon, O. B., McKay, C. P., Ackerman, T. P., and Santhanam, K.: Rapid calculation of radiative heating rates and photodissociation rates in inhomogeneous multiple scattering atmospheres, J. Geophys. Res.-Atmos., 94, 16287-16301, https://doi.org/10.1029/JD094iD13p16287, 1989.
Turton, J. V., Mölg, T., and Collier, E.: High-resolution (1 km) Polar WRF output for 79° N Glacier and the northeast of Greenland from 2014 to 2018, Earth Syst. Sci. Data, 12, 1191–1202, https://doi.org/10.5194/essd-12-1191-2020, 2020.
Verseghy, D. L.: Class – A Canadian land surface scheme for GCMS. I. Soil model, Int. J. Climatol., 11, 111–133, https://doi.org/10.1002/joc.3370110202, 1991.
von Salzen, K., Whaley, C. H., Anenberg, S. C., Van Dingenen, R., Klimont, Z., Flanner, M. G., Mahmood, R., Arnold, S. R., Beagley, S., Chien, R.-Y., Christensen, J. H., Eckhardt, S., Ekman, A. M. L., Evangeliou, N., Faluvegi, G., Fu, J. S., Gauss, M., Gong, W., Hjorth, J. L., Im, U., Krishnan, S., Kupiainen, K., Kühn, T., Langner, J., Law, K. S., Marelle, L., Olivié, D., Onishi, T., Oshima, N., Paunu, V.-V., Peng, Y., Plummer, D., Pozzoli, L., Rao, S., Raut, J.-C., Sand, M., Schmale, J., Sigmond, M., Thomas, M. A., Tsigaridis, K., Tsyro, S., Turnock, S. T., Wang, M., and Winter, B.: Clean air policies are key for successfully mitigating Arctic warming, Communications Earth and Environment, 3, 222, https://doi.org/10.1038/s43247-022-00555-x, 2022.
Wang, W., Yang, K., Zhao, L., Zheng, Z., Lu, H., Mamtimin, A., Ding, B., Li, X., Zhao, L., Li, H., Che, T., and Moore, J. C.: Characterizing Surface Albedo of Shallow Fresh Snow and Its Importance for Snow Ablation on the Interior of the Tibetan Plateau, J. Hydrometeorol., 21, 815–827, https://doi.org/10.1175/JHM-D-19-0193.1, 2020.
Wang, Z. W., Gallet, J. C., Pedersen, C. A., Zhang, X. S., Ström, J., and Ci, Z. J.: Elemental carbon in snow at Changbai Mountain, northeastern China: concentrations, scavenging ratios, and dry deposition velocities, Atmos. Chem. Phys., 14, 629–640, https://doi.org/10.5194/acp-14-629-2014, 2014.
Warren, S. G., and Wiscombe, W. J.: A Model for the Spectral Albedo of Snow. II: Snow Containing Atmospheric Aerosols, J. Atmos. Sci., 37, 2734–2745, https://doi.org/10.1175/1520-0469(1980)037<2734:AMFTSA>2.0.CO;2, 1980.
Wilson, A. B., Bromwich, D. H., and Hines, K. M.: Evaluation of Polar WRF forecasts on the Arctic System Reanalysis domain: Surface and upper air analysis, J. Geophys. Res.-Atmos., 116, D11112, https://doi.org/10.1029/2010JD015013, 2011.
Wiscombe, W. J. and Warren, S. G.: A Model for the Spectral Albedo of Snow. I: Pure Snow, J. Atmos. Sci., 37, 2712–2733, https://doi.org/10.1175/1520-0469(1980)037, 1980.
Xue, J., Bromwich, D. H., Xiao, Z., and Bai, L.: Impacts of initial conditions and model configuration on simulations of polar lows near Svalbard using Polar WRF with 3DVAR, Q. J. Roy. Meteorol. Soc., 147, 3806–3834, https://doi.org/10.1002/qj.4158, 2021.
Yang, Q., Dan, L., Lv, M., Wu, J., Li, W., and Dong, W.: Quantitative assessment of the parameterization sensitivity of the Noah-MP land surface model with dynamic vegetation using ChinaFLUX data, Agr. Forest Meteorol., 307, 108542, https://doi.org/10.1016/j.agrformet.2021.108542, 2021.
Yang, Z.-L. and Niu, G.-Y.: The Versatile Integrator of Surface and Atmosphere processes: Part 1. Model description, Global Planet. Change, 38, 175–189, https://doi.org/10.1016/S0921-8181(03)00028-6, 2003.
Yang, Z.-L., Dickinson, R. E., Robock, A., and Vinnikov, K. Y.: Validation of the Snow Submodel of the Biosphere–Atmosphere Transfer Scheme with Russian Snow Cover and Meteorological Observational Data, J. Climate, 10, 353–373, https://doi.org/10.1175/1520-0442(1997)010<0353:VOTSSO>2.0.CO;2, 1997.
You, Q., Cai, Z., Pepin, N., Chen, D., Ahrens, B., Jiang, Z., Wu, F., Kang, S., Zhang, R., Wu, T., Wang, P., Li, M., Zuo, Z., Gao, Y., Zhai, P., and Zhang, Y.: Warming amplification over the Arctic Pole and Third Pole: Trends, mechanisms and consequences, Earth-Sci. Rev., 217, 103625, https://doi.org/10.1016/j.earscirev.2021.103625, 2021.
You, Y., Huang, C., Hou, J., Zhang, Y., Wang, Z., and Zhu, G.: Improving the estimation of snow depth in the Noah-MP model by combining particle filter and Bayesian model averaging, J. Hydrol., 617, 128877, https://doi.org/10.1016/j.jhydrol.2022.128877, 2023.
Zhang, Z., Zhou, L., and Zhang, M.: A progress review of black carbon deposition on Arctic snow and ice and its impact on climate change, Advances in Polar Science, 35, 178–191, https://doi.org/10.12429/j.advps.2023.0024, 2024a.
Zhang, Z., Zhou, L., and Zhang, M.: A numerical sensitivity study on the snow-darkening effect by black carbon deposition over the Arctic in spring, Zenodo [code], https://doi.org/10.5281/zenodo.14543287, 2024b (code available at: https://github.com/mflanner/SNICARv3 and https://github.com/ZhangZiLu0831/PWRF_NoahMP_SNICAR, last access: 21 December 2024).
Zhao, X., Huang, K., Fu, J. S., and Abdullaev, S. F.: Long-range transport of Asian dust to the Arctic: identification of transport pathways, evolution of aerosol optical properties, and impact assessment on surface albedo changes, Atmos. Chem. Phys., 22, 10389–10407, https://doi.org/10.5194/acp-22-10389-2022, 2022.
Zhong, E., Li, Q., Sun, S., Chen, S., and Chen, W.: Analysis of euphotic depth in snow with SNICAR transfer scheme, Atmos. Sci. Lett., 18, 484–490, https://doi.org/10.1002/asl.792, 2017.
Zhou, C., Penner, J. E., Flanner, M. G., Bisiaux, M. M., Edwards, R., and McConnell, J. R.: Transport of black carbon to polar regions: Sensitivity and forcing by black carbon, Geophys. Res. Lett., 39, L22804, https://doi.org/10.1029/2012GL053388, 2012.
Short summary
By integrating the SNICAR model with Polar-WRF, we find that 50 ng g−1 black carbon (BC) deposition decreases snow albedo, increasing radiative forcing (RF) by 1–4 W m−2, especially in Greenland, Baffin Island, and eastern Siberia. The impact is strongly linked to BC mass, with deep snowpacks showing greater sensitivity. Snowmelt and land–atmosphere interactions are crucial. High-resolution modelling is necessary to better understand these effects on Arctic climate change.
By integrating the SNICAR model with Polar-WRF, we find that 50 ng g−1 black carbon (BC)...
Altmetrics
Final-revised paper
Preprint