Articles | Volume 16, issue 18
https://doi.org/10.5194/gmd-16-5323-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-5323-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
19 Sep 2023
Development and technical paper |
| 19 Sep 2023
| 19 Sep 2023
An optimisation method to improve modelling of wet deposition in atmospheric transport models: applied to FLEXPART v10.4
Stijn Van Leuven
CORRESPONDING AUTHOR
Belgian Nuclear Research Centre, Mol, Belgium
Royal Meteorological Institute of Belgium, Brussels, Belgium
Department of Physics and Astronomy, Ghent University, Ghent, Belgium
Pieter De Meutter
Belgian Nuclear Research Centre, Mol, Belgium
Royal Meteorological Institute of Belgium, Brussels, Belgium
Johan Camps
Belgian Nuclear Research Centre, Mol, Belgium
Piet Termonia
Royal Meteorological Institute of Belgium, Brussels, Belgium
Department of Physics and Astronomy, Ghent University, Ghent, Belgium
Andy Delcloo
Royal Meteorological Institute of Belgium, Brussels, Belgium
Department of Physics and Astronomy, Ghent University, Ghent, Belgium
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Cited articles
Adler, R., Wang, J.-J., Sapiano, M., Huffman, G., Chiu, L., Xie, P. P., Ferraro, R., Schneider, U., Becker, A., Bolvin, D., Nelkin, E., Gu, G., and NOAA CDR Program: Global Precipitation Climatology Project (GPCP) Climate Data Record (CDR), Tech. Rep. Version 2.3 (Monthly), National Centers for Environmental Information [data set], https://doi.org/10.7289/V56971M6, 2016. a
Adler, R. F., Sapiano, M. R. P., Huffman, G. J., Wang, J. J., Gu, G. J., Bolvin, D., Chiu, L., Schneider, U., Becker, A., Nelkin, E., Xie, P. P., Ferraro, R., and Shin, D. B.: The Global Precipitation Climatology Project (GPCP) Monthly Analysis (New Version 2.3) and a Review of 2017 Global Precipitation, Atmosphere, 9, 138, https://doi.org/10.3390/atmos9040138, 2018. a
Andersson, A.: Mechanisms for log normal concentration distributions in the environment, Sci. Rep.-UK, 11, 16418, https://doi.org/10.1038/s41598-021-96010-6, 2021. a
Andronache, C.: Estimated variability of below-cloud aerosol removal by rainfall for observed aerosol size distributions, Atmos. Chem. Phys., 3, 131–143, https://doi.org/10.5194/acp-3-131-2003, 2003. a, b, c
Arnold, D., Maurer, C., Wotawa, G., Draxler, R., Saito, K., and Seibert, P.: Influence of the meteorological input on the atmospheric transport modelling with FLEXPART of radionuclides from the Fukushima Daiichi nuclear accident, J. Environ. Radioactiv., 139, 212–225, https://doi.org/10.1016/j.jenvrad.2014.02.013, 2015. a, b, c, d
Baklanov, A. and Sorensen, J. H.: Parameterisation of radionuclide deposition in atmospheric long-range transport modelling, Phys. Chem. Earth Pt. B, 26, 787–799, https://doi.org/10.1016/S1464-1909(01)00087-9, 2001. a, b
Baklanov, A., Mahura, A., Jaffe, D., Thaning, L., Bergman, R., and Andres, R.: Atmospheric transport patterns and possible consequences for the European North after a nuclear accident, J. Environ. Radioactiv., 60, 23–48, https://doi.org/10.1016/S0265-931x(01)00094-7, 2002. a
Biegalski, S. R., Hosticka, B., and Mason, L. R.: Cesium-137 concentrations, trends, and sources observed in Kuwait City, Kuwait, J. Radioanal. Nucl. Ch., 248, 643–649, https://doi.org/10.1023/A:1010676208657, 2001. a
Chatterjee, A., Jayaraman, A., Rao, T. N., and Raha, S.: In-cloud and below-cloud scavenging of aerosol ionic species over a tropical rural atmosphere in India, J. Atmos. Chem., 66, 27–40, https://doi.org/10.1007/s10874-011-9190-5, 2010. a
Colbeck, I. and Lazaridis, M.: Aerosols and environmental pollution, Naturwissenschaften, 97, 117–131, https://doi.org/10.1007/s00114-009-0594-x, 2010. a
Croft, B., Lohmann, U., Martin, R. V., Stier, P., Wurzler, S., Feichter, J., Hoose, C., Heikkilä, U., van Donkelaar, A., and Ferrachat, S.: Influences of in-cloud aerosol scavenging parameterizations on aerosol concentrations and wet deposition in ECHAM5-HAM, Atmos. Chem. Phys., 10, 1511–1543, https://doi.org/10.5194/acp-10-1511-2010, 2010. a
Draxler, R., Arnold, D., Chino, M., Galmarini, S., Hort, M., Jones, A., Leadbetter, S., Malo, A., Maurer, C., Rolph, G., Saito, K., Servranckx, R., Shimbori, T., Solazzo, E., and Wotawa, G.: World Meteorological Organization's model simulations of the radionuclide dispersion and deposition from the Fukushima Daiichi nuclear power plant accident, J. Environ. Radioactiv., 139, 172–184, https://doi.org/10.1016/j.jenvrad.2013.09.014, 2015. a, b
Fang, S., Zhuang, S. H., Goto, D., Hu, X. F., Li, S., and Huang, S. X.: Coupled modeling of in- and below-cloud wet deposition for atmospheric 137Cs transport following the Fukushima Daiichi accident using WRF-Chem: A self-consistent evaluation of 25 scheme combinations, Environ. Int., 158, 106882, https://doi.org/10.1016/j.envint.2021.106882, 2022. a
Ge, B., Xu, D., Wild, O., Yao, X., Wang, J., Chen, X., Tan, Q., Pan, X., and Wang, Z.: Inter-annual variations of wet deposition in Beijing from 2014–2017: implications of below-cloud scavenging of inorganic aerosols, Atmos. Chem. Phys., 21, 9441–9454, https://doi.org/10.5194/acp-21-9441-2021, 2021. a
Grythe, H., Kristiansen, N. I., Groot Zwaaftink, C. D., Eckhardt, S., Ström, J., Tunved, P., Krejci, R., and Stohl, A.: A new aerosol wet removal scheme for the Lagrangian particle model FLEXPART v10, Geosci. Model Dev., 10, 1447–1466, https://doi.org/10.5194/gmd-10-1447-2017, 2017. a, b, c, d, e, f, g, h, i, j, k, l, m, n
Gueibe, C., Kalinowski, M. B., Bare, J., Gheddou, A., Krysta, M., and Kusmierczyk-Michulec, J.: Setting the baseline for estimated background observations at IMS systems of four radioxenon isotopes in 2014, J. Environ. Radioactiv., 178, 297–314, https://doi.org/10.1016/j.jenvrad.2017.09.007, 2017. a
Henzing, J. S., Olivié, D. J. L., and van Velthoven, P. F. J.: A parameterization of size resolved below cloud scavenging of aerosols by rain, Atmos. Chem. Phys., 6, 3363–3375, https://doi.org/10.5194/acp-6-3363-2006, 2006. a, b, c
Hertel, O., Christensen, J., Runge, E. H., Asman, W. A. H., Berkowicz, R., Hovmand, M. F., and Hov, O.: Development and Testing of a New Variable Scale Air-Pollution Model – Acdep, Atmos. Environ., 29, 1267–1290, https://doi.org/10.1016/1352-2310(95)00067-9, 1995. a
Jones, A. C., Hill, A., Hemmings, J., Lemaitre, P., Quérel, A., Ryder, C. L., and Woodward, S.: Below-cloud scavenging of aerosol by rain: a review of numerical modelling approaches and sensitivity simulations with mineral dust in the Met Office's Unified Model, Atmos. Chem. Phys., 22, 11381–11407, https://doi.org/10.5194/acp-22-11381-2022, 2022. a, b
Kaneyasu, N., Ohashi, H., Suzuki, F., Okuda, T., and Ikemori, F.: Sulfate Aerosol as a Potential Transport Medium of Radiocesium from the Fukushima Nuclear Accident, Environ. Sci. Technol., 46, 5720–5726, https://doi.org/10.1021/es204667h, 2012. a
Katata, G., Chino, M., Kobayashi, T., Terada, H., Ota, M., Nagai, H., Kajino, M., Draxler, R., Hort, M. C., Malo, A., Torii, T., and Sanada, Y.: Detailed source term estimation of the atmospheric release for the Fukushima Daiichi Nuclear Power Station accident by coupling simulations of an atmospheric dispersion model with an improved deposition scheme and oceanic dispersion model, Atmos. Chem. Phys., 15, 1029–1070, https://doi.org/10.5194/acp-15-1029-2015, 2015. a
Kyro, E. M., Gronholm, T., Vuollekoski, H., Virkkula, A., Kulmala, M., and Laakso, L.: Snow scavenging of ultrafine particles: field measurements and parameterization, Boreal Environ. Res., 14, 527–538, 2009. a
Laakso, L., Gronholm, T., Rannik, U., Kosmale, M., Fiedler, V., Vehkamaki, H., and Kulmala, M.: Ultrafine particle scavenging coefficients calculated from 6 years field measurements, Atmos. Environ., 37, 3605–3613, https://doi.org/10.1016/S1352-2310(03)00326-1, 2003. a
Leadbetter, S. J., Hort, M. C., Jones, A. R., Webster, H. N., and Draxler, R. R.: Sensitivity of the modelled deposition of Caesium-137 from the Fukushima Dai-ichi nuclear power plant to the wet deposition parameterisation in NAME, J. Environ. Radioactiv., 139, 200–211, https://doi.org/10.1016/j.jenvrad.2014.03.018, 2015. a
Lohmann, U. and Feichter, J.: Global indirect aerosol effects: a review, Atmos. Chem. Phys., 5, 715–737, https://doi.org/10.5194/acp-5-715-2005, 2005. a
Masson, O., Ringer, W., Mala, H., Rulik, P., Dlugosz-Lisiecka, M., Eleftheriadis, K., Meisenberg, O., De Vismes-Ott, A., and Gensdarmes, F.: Size Distributions of Airborne Radionuclides from the Fukushima Nuclear Accident at Several Places in Europe, Environ. Sci. Technol., 47, 10995–11003, https://doi.org/10.1021/es401973c, 2013. a
Masson, O., Ott, A. D., Bourcier, L., Paulat, P., Ribeiro, M., Pichon, J. M., Sellegri, K., and Gurriaran, R.: Change of radioactive cesium (Cs-137 and Cs-134) content in cloud water at an elevated site in France, before and after the Fukushima nuclear accident: Comparison with radioactivity in rainwater and in aerosol particles, Atmos. Res., 151, 45–51, https://doi.org/10.1016/j.atmosres.2014.03.031, 2015. a
Miyamoto, Y., Yasuda, K., and Magara, M.: Size distribution of radioactive particles collected at Tokai, Japan 6 d after the nuclear accident, J. Environ. Radioactiv., 132, 1–7, https://doi.org/10.1016/j.jenvrad.2014.01.010, 2014. a
Morino, Y., Ohara, T., and Nishizawa, M.: Atmospheric behavior, deposition, and budget of radioactive materials from the Fukushima Daiichi nuclear power plant in March 2011, Geophys. Res. Lett., 38, L00g11, https://doi.org/10.1029/2011gl048689, 2011. a
Pisso, I., Sollum, E., Grythe, H., Kristiansen, N. I., Cassiani, M., Eckhardt, S., Arnold, D., Morton, D., Thompson, R. L., Groot Zwaaftink, C. D., Evangeliou, N., Sodemann, H., Haimberger, L., Henne, S., Brunner, D., Burkhart, J. F., Fouilloux, A., Brioude, J., Philipp, A., Seibert, P., and Stohl, A.: The Lagrangian particle dispersion model FLEXPART version 10.4, Geosci. Model Dev., 12, 4955–4997, https://doi.org/10.5194/gmd-12-4955-2019, 2019a. a, b, c, d, e
Pisso, I., Sollum, E., Grythe, H., Kristiansen, N. I., Cassiani, M., Eckhardt, S., Arnold, D., Morton, D., Thompson, R. L., Groot Zwaaftink, C. D., Evangeliou, N., Sodemann, H., Haimberger, L., Henne, S., Brunner, D., Burkhart, J. F., Fouilloux, A., Brioude, J., Philipp, A., Seibert, P., and Stohl, A.: FLEXPART 10.4. In Geosci. Model Dev. Discuss. (10.4), Zenodo [code], https://doi.org/10.5281/zenodo.3542278, 2019b. a
Querel, A., Roustan, Y., Quelo, D., and Benoit, J. P.: Hints to discriminate the choice of wet deposition models applied to an accidental radioactive release, Int. J. Environ. Pollut., 58, 268–279, https://doi.org/10.1504/Ijep.2015.077457, 2015. a
Querel, A., Quelo, D., Roustan, Y., and Mathieu, A.: Sensitivity study to select the wet deposition scheme in an operational atmospheric transport model, J. Environ. Radioactiv., 237, 106712, https://doi.org/10.1016/j.jenvrad.2021.106712, 2021. a
Schneider, U., Becker, A., Finger, P., Meyer-Christoffer, A., Rudolf, B., and Ziese, M.: GPCC Full Data Reanalysis Version 6.0 at 0.5∘: Monthly Land-Surface Precipitation from Rain-Gauges built on GTS-based and Historic Data, https://doi.org/10.5676/DWD_GPCC/FD_M_V6_050, 2011. a
Slinn, W. G. N.: Precipitation scavenging, in: Atmospheric Science and Power Production, edited by: Randerson, D., Tech. Inf. Cent., Off. of Sci. and Techn. Inf., Dep. of Energy, Washington, DC, USA, 466–532, ISBN 978-0870791260, 1984. a
Solazzo, E. and Galmarini, S.: The Fukushima-Cs-137 deposition case study: properties of the multi-model ensemble, J. Environ. Radioactiv., 139, 226–233, https://doi.org/10.1016/j.jenvrad.2014.02.017, 2015. a
Sportisse, B.: A review of parameterizations for modelling dry deposition and scavenging of radionuclides, Atmos. Environ., 41, 2683–2698, https://doi.org/10.1016/j.atmosenv.2006.11.057, 2007. a, b, c, d
Stohl, A., Hittenberger, M., and Wotawa, G.: Validation of the Lagrangian particle dispersion model FLEXPART against large-scale tracer experiment data, Atmos. Environ., 32, 4245–4264, https://doi.org/10.1016/S1352-2310(98)00184-8, 1998. a, b
Stohl, A., Forster, C., Frank, A., Seibert, P., and Wotawa, G.: Technical note: The Lagrangian particle dispersion model FLEXPART version 6.2, Atmos. Chem. Phys., 5, 2461–2474, https://doi.org/10.5194/acp-5-2461-2005, 2005. a
Stohl, A., Seibert, P., Wotawa, G., Arnold, D., Burkhart, J. F., Eckhardt, S., Tapia, C., Vargas, A., and Yasunari, T. J.: Xenon-133 and caesium-137 releases into the atmosphere from the Fukushima Dai-ichi nuclear power plant: determination of the source term, atmospheric dispersion, and deposition, Atmos. Chem. Phys., 12, 2313–2343, https://doi.org/10.5194/acp-12-2313-2012, 2012. a, b, c, d, e
Terada, H., Nagai, H., Tsuduki, K., Furuno, A., Kadowaki, M., and Kakefuda, T.: Refinement of source term and atmospheric dispersion simulations of radionuclides during the Fukushima Daiichi Nuclear Power Station accident, J. Environ. Radioactiv., 213, 106104, https://doi.org/10.1016/j.jenvrad.2019.106104, 2020.
a, b, c, d, e
Tipka, A., Haimberger, L., and Seibert, P.: Flex_extract v7.1.2 – a software package to retrieve and prepare ECMWF data for use in FLEXPART, Geosci. Model Dev., 13, 5277–5310, https://doi.org/10.5194/gmd-13-5277-2020, 2020. a
Van Leuven, S.: MATLAB code for “An optimisation method to improve modelling of wet deposition in atmospheric transport models: applied to FLEXPART v10.4”, Zenodo [code], https://doi.org/10.5281/zenodo.7789039, 2023a. a
Van Leuven, S.: Flexpart input/output data for “An optimisation method to improve modelling of wet deposition in atmospheric transport models: applied to FLEXPART v10.4”, Zenodo [data set], https://doi.org/10.5281/zenodo.7906927, 2023b. a
Wang, X., Zhang, L., and Moran, M. D.: Uncertainty assessment of current size-resolved parameterizations for below-cloud particle scavenging by rain, Atmos. Chem. Phys., 10, 5685–5705, https://doi.org/10.5194/acp-10-5685-2010, 2010. a, b
Wang, X., Zhang, L., and Moran, M. D.: On the discrepancies between theoretical and measured below-cloud particle scavenging coefficients for rain – a numerical investigation using a detailed one-dimensional cloud microphysics model, Atmos. Chem. Phys., 11, 11859–11866, https://doi.org/10.5194/acp-11-11859-2011, 2011. a, b
Wetherbee, G. A., Gay, D. A., Debey, T. M., Lehmann, C. M. B., and Nilles, M. A.: Wet Deposition of Fission-Product Isotopes to North America from the Fukushima Dai-ichi Incident, March 2011, Environ. Sci. Technol., 46, 2574–2582, https://doi.org/10.1021/es203217u, 2012. a
World Health Organization: Health risk assessment from the nuclear accident after the 2011 Great East Japan earthquake and tsunami, based on a preliminary dose estimation, ISBN 9789241505130, 2013. a
Xu, D. H., Ge, B. Z., Wang, Z. F., Sun, Y. L., Chen, Y., Ji, D. S., Yang, T., Ma, Z. Q., Cheng, N. L., Hao, J. Q., and Yao, X. F.: Below-cloud wet scavenging of soluble inorganic ions by rain in Beijing during the summer of 2014, Environ. Pollut., 230, 963–973, https://doi.org/10.1016/j.envpol.2017.07.033, 2017. a
Short summary
Precipitation collects airborne particles and deposits these on the ground. This process is called wet deposition and greatly determines how airborne radioactive particles (released routinely or accidentally) contaminate the surface. In this work we present a new method to improve the calculation of wet deposition in computer models. We apply this method to the existing model FLEXPART by simulating the Fukushima nuclear accident (2011) and show that it improves the simulation of wet deposition.
Precipitation collects airborne particles and deposits these on the ground. This process is...
