Т. D. Lev, M. M. Таlerko
Institute for Safety Problems of Nuclear Power Plants,
NAS of Ukraine, 12, Lysogirska st., Kyiv, 03028, Ukraine
The simulation of meteorological conditions of the atmospheric transport of radioactive aerosols during the periods of wildland fires (2015, 2018, 2020 and 2022) and dust storm (April 16–17, 2020) in the Chornobyl Exclusion Zone was carried out using the archive of reanalysis data of the European Center for Medium-Term Weather Forecasts (ECMWF). Modeling of meteorological conditions and preparation of aerosynoptic information for the LEDI model of atmospheric transport and deposition of pollutants during periods of intense emission of radionuclides into the atmosphere was carried out using two sources of information: the results of the numerical weather forecast model WRF-ARW (USA) using the databases of the Reanalysis Project, and forecast data obtained according to the GFS global model and the ECMWF operational model, which are stored in the database of the CDS climate data repository (ERA5 Copernicus). The used WRF-ARW numerical model is adapted for the territory of Ukraine by selecting parameterization models of the main physical processes in the atmosphere in accordance with synoptic situations and the season of the year. A description of typical and extreme synoptic situations during the analyzed periods of wildland fires is given using the archive of synoptic maps of surface pressure and topography AT500 for the European territory and modern technologies of geoinformation systems. With the help of the conducted synoptic analysis of wildland fire periods, the most typical synoptic situations associated with the passage of cold fronts and the direction of north and northwest winds, which contribute mostly to the secondary radioactive contamination of environmental objects in the zone of influence of emission sources in the Chornobyl Exclusion Zone, were identified. Because of global climate changes and unpredictable human activity in the form of arsons, military actions, etc., the number of fires in forest areas, industrial and residential facilities is increasing. Open sources of numerical weather forecast data make it possible to create modern meteorological support for modeling of atmospheric transport and deposition of pollutants and assessment of secondary environmental pollution using the LEDI-WRF software complex.
Keywords: numerical weather forecast models, extreme meteorological situation, meteorological data bases, modeling of atmospheric transport, radionuclides.
1. Giannaros T. M., Papavasileiou G., Lagouvardos K., Kotroni V., Dafis S., Karagiannidis A., Dragozi E. (2022). Meteorological analysis of the 2021 extreme wildfires in Greece: Lessons learned and implications for early warning of the potential for pyroconvection. Atmosphere, vol. 13, p. 475. doi.org/10.3390/atmos13030475.
2. Gill J., Rubiera J., Martin C., Cacic I., Mylne K., Dehui C., Jiafeng G., Xu T., Yamaguchi M., Foamouhoue K., Poolman E., Guiney J., Kootval H. (2008). Guidelines on communicating forecast uncertainty. PWS-18; WMO/TD No. 1422. World Meteorological Organisation. Available at: https://www.preventionweb.net/publication/guidelinescommunicating-forecast-uncertainty.
3. Zaiko P. О. (2020). Meteorological data assimilationin mesoscale numerical model WRF-ARW in the republic of Belarus. Wschodnioeuropejskie Czasopismo Naukowe (East European Scientific Journal), no. 3 (55), pp. 4–10.
4. Ivanov А. V., Stryzhak S. V., Zakharov М. I. (2019). [Modeling of weather conditions in the port area and in the coastal zone of the Tiksi Bay]. Proceedings of the ISP RAS, vol. 31, no. 6, pp. 163–176. doi.org/10.15514/ISPRAS-2019–31(6)-9. (in Rus.)
5. Nabokova E. V. (2010). [Experience in the application of the WRF model, taking into account two methods of parametrization of the urban sublayer for forecasting air temperature and wind speed]. Proceedings of the GMTs of Russia, vol. 344, pp. 180–195. (in Rus.)
6. Khalchenkov A. V., Kovalets I. V. (2020). [Using relaxation methods in the WRF model to analyze meteorological conditions in Ukraine over a long period]. Mathematical machines and systems, no 2, pp. 30–42. (in Rus.)
7. Kizhner L. I., Barashkova N. K., Akhmetshina A. S., Bart A. A., Polyakov D. V. (2013). [Estimation of the accuracy of numerical forecasts of meteorological conditions in the region of Tomsk using the WRF model]. Bulletin of Tomsk State University, no. 374, pp. 174–178. (in Rus.)
8. Hersbach H., Bell B., Berrisford P., et al. (2020). The ERA5 global reanalysis. Research article. Quarterly Journal of the Royal Meteorological Society, vol. 146, pp. 1999–2049.
9. National Centers for Environmental Prediction/ National Center for Atmospheric Research Reanalysis (NCEPNCAR1). Other Flux. Australian Research Data Commons (ARDC). Available at: https://researchdata.edu.au/national-centers-environmental-1-flux/15271.
10. The Research Data Archive. Available at: https://rda.ucar.edu/datasets.
11. Climate Data. ERA-INTERIM. National Center for Atmospheric Research Climate Data Guide. Available at: https://climatedataguide.ucar.edu/climate-data/era-interim.
12. ERA-Interim. European Centre for Medium-Range Weather Forecasts. Available at: https://www.ecmwf.int/en/forecasts/datasets/archive-datasets/reanalysis-datasets/era-interim.
13. The World in Weather Charts. Available at: http://www1.wetter3.de/archiv_dwd_en.html.
14. Wetterzentrale. Available at: https://www.wetterzentrale.de/reanalysis.php.
15. Weather. Soundings. University of Wyoming: official website. Available at: http://weather.uwyo.edu/upperair/sounding.html.
16. Weather archive. Available at: http://www.pogodaiklimat.ru/archive.php.
17. Datasets. Climate Data Store. Available at: https://cds.climate.copernicus.eu/cdsapp#!/search?type=dataset.
18. Zverev A. S. (1977). Sinopticheskaya meteorologiya [Synoptic meteorology]. Leningrad: Gidrometeoizdat, 436 p. (in Rus.)
19. Belousov S. L., et al. (eds.) (1986). Rukovodstvo po kratkosrochnym prognozam pogody. Ch. 1. [Guide to short-range weather forecasts. Part 1]. Leningrad: Gidrometeoizdat, 696 p. (in Rus.)
20. SaveEcoBot. Maps. Available at: https://www.saveecobot.com/maps#7/50.611/31.300/pm10.
21. AERONET Aerosol Optical Depth Data Display Interface. Kyiv-AO site. Available at: https://aeronet.gsfc.nasa.gov/cgi-bin/data_display_aod_v3?site=Kyiv-AO.
22. Birmili W., Schepanski K., Ansmann A., et al. (2008). A case of extreme particulate matter concentrations over Central Europe caused by dust emitted over the southern Ukraine. Atmos. Chem. Phys., vol. 8, pp. 997–1016.
23. Anisimov A., Axisa D., Kucera P. A., et al. (2018). Observations and Cloud-Resolving Modeling of Haboob Dust Storms Over the Arabian Peninsula. Journal of Geophysical Research: Atmospheres, vol. 12, pp. 147–179. doi.org/10.1029/2018JD028486.
24. Yakovleva D. V., Tolkachenko G. A. (2008). [Analysis of the optical characteristics of atmospheric aerosol over the Black Sea from May 2006 to September 2007]. Radiophysics and Electronics, vol. 13, no. 2, pp. 185–189. (in Rus.)
25. Kalinskaya D. V. (2012). [Investigation of the features of the optical characteristics of dust aerosol over the Black Sea]. Environmental safety of coastal and shelf zones and integrated use of shelf resources, vol. 26, no. 2, pp. 151–162. Available at: http://dspace.nbuv.gov.ua/handle/123456789/56874. (in Rus.)
26. AERONET Data Download Tool. Version 3 Direct Sun Algorithm. Kyiv-AO site. — Available at: https://aeronet.gsfc.nasa.gov/cgi-bin/webtool_aod_v3?stage=3®ion=Europe&state=Ukraine&site=Kyiv-AO&place_code=10).
27. Climate Data Store. Available at: https://cds.climate.copernicus.eu.
28. Dee D. P., Uppala S. M., Simmons A. J., et al. (2022). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, vol. 137, pp. 553–597.
29. ARW Version 3.9 Modeling System User’s Guide. User’s Guide for the NMM core of the Weather Research and Forecast (WRF) modeling system. April, 2008. 214 p. Available at: http://www.mmm.ucar.edu/wrf/users.
30. ERA5 hourly data on single levels from 1979 to present. doi.org/10.24381/cds.adbb2d47. Available at: https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview.
31. ERA5 hourly data on pressure levels from 1979 to present. doi.org/10.24381/cds.bd0915c6. Available at: https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels?tab=overview.
32. Talerko M. M., Lev Т. D., Kireev S. I., Каshpur V. О., Кuzmenko G. G. (2019). Evaluation of radioactive air contamination due to a forest fire within the Exclusion zone on 5–8 June, 2018. Nuclear Power and the Environment, vol. 14, no. 2, pp. 47–57. doi.org/10.31717/2311–8253.19.1.7.
33. Таlerko M., Коvalets I., Lev Т., Igarashic Y., Romanenko O. (2021). Simulation study of radionuclide atmospheric transport after wildland fires in the Chernobyl Exclusion Zone in April 2020. Atmospheric Pollution Research, vol. 12, no. 3, pp. 193–204. doi.org/10.1016/j.apr.2021.01.010.
If the article is accepted for publication in the journal «Industrial Heat Engineering» the author must sign an agreement on transfer of copyright. The agreement is sent to the postal (original) or e-mail address (scanned copy) of the journal editions.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License International CC-BY that allows others to share the work with an acknowledgement of the work’s authorship and initial publication in this journal.