Research of the Aerosol Optical and Microphysical Characteristics of the Atmosphere over the Black Sea Region by the FIRMS System during the Forest Fires in 2018–2019

D. V. Kalinskaya1, ✉, A. S. Papkova1, D. M. Kabanov2

1 Marine Hydrophysical Institute of RAS, Sevastopol, Russian Federation

2 Zuev Institute of Atmospheric Optics of the Siberian Branch of Russian Academy of Sciences, Tomsk, Russian Federation

✉ e-mail: kalinskaya_d_v@mail.ru

Abstract

Purpose. The Black Sea region where the forest fires were recorded by the FIRMS system, as well as the atmosphere above it, namely the fire-induced variation of the atmospheric aerosol basic optical characteristics, were the main objects of the investigation. The study is aimed at examining the fires in the Black Sea region in 2018–2019 for assessing correlation between these events and variability of the basic optical characteristics over the Black Sea.

Methods and Results. Based on the FIRMS system data, variations of intensity of the fire-induced radiation were studied. The results of statistical processing of the MODIS and VIIRS satellite data on the fires in 2018–2019 were represented. For the dates when the fire numbers were the highest in the Black Sea region, the basic optical and microphysical characteristics of the atmospheric aerosol were analyzed due to the SPM and AERONET data. The dates when the fire intensity was particularly high (based on the MODIS and VIIRS data) were analyzed and compared with the dates when the anomalous values of the atmospheric aerosol optical characteristics were recorded over the region under study.

Conclusions. For the fire events in the Black Sea region revealed due to the MODIS and VIIRS data, complex analysis of the air mass transfer was performed by the model HYSPLIT, and the aerosol was typed by the CALIPSO algorithm. On June 22, 2019 the most intense fires were recorded. According to the aerosol typing by the CALIPSO algorithm, on this day the predominant aerosol types were the contaminated dust and smoke. Using the MODIS and VIIRS data, investigation of possible source of the aerosol transfer on this date showed that the area of intense inflammationn and smoke was located to the northeast from the Black Sea region. Since the satellite-derived data on this day showed no dust transfer either from the Sahara or the Syria deserts, it is possible to conclude that increase of the values of aerosol optical depth АОD (500) was conditioned by transfer of the aerosol resulted from biomass burning from the north to the Black Sea region.

Keywords

EOSDIS, MODIS, VIIRS, SPM, AERONET, CALIPSO, 7-day back trajectories, Black Sea, HYSPLIT, smoke, soot, smog, absorbing aerosol, thermal anomalies, optical thickness of aerosol

Acknowledgements

The investigation was carried out at the support of the RFBR grant No. 19-05-50023 and the state task theme No. 0827-2019-0002. The authors are grateful to S. M. Sakerin for providing the SPM photometer and the corresponding software.

Original russian text

Original Russian Text © D. V. Kalinskaya, A. S. Papkova, D. M. Kabanov, 2020, published in MORSKOY GIDROFIZICHESKIY ZHURNAL, Vol. 36, Iss. 5, pp. 559–570 (2020)

For citation

Kalinskaya, D.V., Papkova, A.S. and Kabanov, D.M., 2020. Research of the Aerosol Optical and Microphysical Characteristics of the Atmosphere over the Black Sea Region by the FIRMS System during the Forest Fires in 2018–2019. Physical Oceanography, 27(5), pp. 514-524. doi:10.22449/1573-160X-2020-5-514-524

DOI

10.22449/1573-160X-2020-5-514-524

References

  1. Rahimov, R.F., Kozlov, V.S., Panchenko, M.V., Tumakov, A.G. and Shmargunov, V.P., 2014. Properties of Atmospheric Aerosol in the Plumes of Forest Fires according to the spectronephelometric measurements. Optika Atmosfery i Okeana, 27(02), pp. 126-133 (in Russian).
  2. Kalinskaya, D.V. and Suslin, V.V., 2015. Variability of Aerosol Optical Characteristics Atmosphere over the Black Sea during the 2010 Year Summer Fires. In: IO RAS, 2015. Current Problems in Optical of Naturals Waters (ONW'2015). Moscow: IO RAS. Vol. 8, pp. 215-219 (in Russian).
  3. Kalinskaya, D.V. and Ryabokon', D.A., 2019. A Study of Aerosol Characteristics over the Black Sea by the FIRMS System during Forest Fires in 2007-2018. Sovremennye Problemy Distantsionnogo Zondirovaniya Zemli iz Kosmosa, 16(4), pp. 247-255 (in Russian).
  4. Kondratyev, K.Ya. and Grigoryev, Al.A., 2004. Forest Fires as a Component of Natural Ecodynamics. Atmospheric and Oceanic Optics, 17(4), pp. 245-255.
  5. Bondur, V.G., Gordo, K.A. and Kladov, V.L., 2016. [Temporal-Spatial Distributions of Natural Fires Areas and Emissions of Carbon-Containing Gases and Aerosols in the Territory of Northern Eurasia According to Space Monitoring Data]. Issledovanie Zemli iz Kosmosa, (6), pp. 3-20. doi:10.7868/S0205961416060105 (in Russian).
  6. Panov, A.V., Prokushkin, A.S., Bryukhanov, A.V., Korets, M.A., Ponomarev, E.I., Sidenko, N.V., Zrazhevskaya, G.K., Timokhina, A.V. and Andreae, M.O., 2018. A Complex Approach for the Estimation of Carbonaceous Emissions from Wildfires in Siberia. Meteorologiya i Gidrologiya, (5), pp. 30-38 (in Russian).
  7. Savorskiy, V.P., 2004. [A Node of Distributed Satellite Data System (TSOKHKI) FIRE RAS]. Sovremennnye Problemy Distantsionnogo Zondirovaniya Zemli iz Kosmosa, 1(1), pp. 241-247 (in Russian).
  8. Justice, C.O., Giglio, L., Korontzi, S., Owens, J., Morisette, J.T., Roy, D., Descloitres, J., Alleaume, S., Petitcolin, F. and Kaufman, Y., 2002. The MODIS Fire Products. Remote Sensing of Environment, 83(1-2), pp. 244-262. https://doi.org/10.1016/S0034-4257(02)00076-7
  9. Chen, Y., Velicogna, I., Famiglietti, J.S. and Randerson, J.T., 2013. Satellite Observations of Terrestrial Water Storage Provide Early Warning Information about Drought and Fire Season Severity in the Amazon. Journal of Geophysical Research: Biogeosciences, 118(2), pp. 495-504. doi:10.1002/jgrg.20046
  10. Chu, D.A., Kaufman, Y.J., Ichoku, C., Remer, L.A., Tanre, D. and Holben, B.N., 2002.Validation of MODIS Aerosol Optical Depth Retrieval over Land. Geophysical Research Letters, 29(12), pp. MOD2-1-MOD2-4. doi:10.1029/2001GL013205
  11. Ichoku, C., Ellison, L.T., Yue, Y., Wang, J. and Kaiser, J.W., 2016. Fire and Smoke Remote Sensing and Modeling Uncertainties: Case Studies in Northern Sub-Saharan Africa. In: K. Riley, P. Webley and M. Thompson, eds., 2016. Natural Hazard Uncertainty Assessment: Modeling and Decision Support. Washington: AGU, pp. 215-230. doi:10.1002/9781119028116.ch14
  12. Panchenko, M.V., Zhuravleva, T.B., Terpugova, S.A., Polkin, V.V. and Kozlov, V.S., 2012. An Empirical Model of Optical and Radiative Characteristics of the Tropospheric Aerosol over West Siberia in Summer. Atmospheric Measurement Techniques, 5(7) pp. 1513-1527. https://doi.org/10.5194/amt-5-1513-2012
  13. Chuvieco, E., Giglio, L. and Justice, C., 2008. Global Characterization of Fire Activity: toward Defining Fire Regimes from Earth Observation Data. Global Change Biology, 14(7), pp. 1488-1502. https://doi.org/10.1111/j.1365-2486.2008.01585.x
  14. Glasius, M., la Cour, A. and Lohse, C., 2011. Fossil and Nonfossil Carbon in Fine Particulate Matter: A Study of Five European Cities. Journal of Geophysical Researches: Atmospheres, 116(D11), D11302. https://doi.org/10.1029/2011JD015646
  15. Wooster, M.J., Roberts, G., Perry, G.L.W. and Kaufman, Y.J., 2005. Retrieval of Biomass Combustion Rates and Totals from Fire Radiative Power Observations: FRP Derivation and Calibration Relationships between Biomass Consumption and Fire Radiative Energy Release. Journal of Geophysical Research: Atmospheres, 110(D24), D24311. doi:10.1029/2005JD006318
  16. Omar, A.H., Winker, D.M., Vaughan, M.A., Hu., Y., Trepte, C.R., Ferrare, R.A., Lee, K-P., Hostetler, C.A., Kittaka, C. [et al.], 2009. The CALIPSO Automated Aerosol Classification and Lidar Ratio Selection Algorithm. Journal of Atmospheric and Oceanic Technology, 26(10), pp. 1994-2014. doi:10.1175/2009JTECHA1231.1
  17. Mielonen, T., Arola, A., Komppula, M., Kukkonen, J., Koskinen, J., de Leeuw, G. and Lehtinen, K.E.J., 2009. Comparison of CALIOP Level 2 Aerosol Subtypes to Aerosol Types Derived from AERONET Inversion Data. Geophysical Research Letters, 36(18), L18804. doi:10.1029/2009GL039609
  18. Omar, A.H., Won, J-G., Winker, D.M., Yoon, S-C., Dubovik, O. and McCormic, M.P., 2005. Development of Global Aerosol Models Using Cluster Analysis of Aerosol Robotic Network (AERONET) Measurements. Journal of Geophysical Researches: Atmospheres, 110(D10), D10S14. doi:10.1029/2004JD004874
  19. Kalinskaya, D.V. and Papkova, A.S., 2017. [Identification of Dust Aerosol over the Black Sea by CALIPSO Radiometer]. In: MHI, 2017. [Seas of Russia: Science, Safety, Resources: Abstracts of Scientific Conference Reports, Sevastopol, 3-7 October 2017]. Sevastopol: MHI, pp. 114-115 (in Russian).
  20. Papkova, A.S. and Kalinskaya, D.V., 2017. [Statistic Research of Aerosol Transport over the Black Sea Region in 2016 by the Data of HYSPLIT and AERONET Models]. In: SSU, 2017. Applied Problems of Mathematics: materials of the XXVth international scientific conference. Sevastopol: SSU, pp. 145-148 (in Russian).
  21. Kalinskaya, D.V. and Suslin, V.V., 2016. Study Properties of Aerosols over the Black Sea during the Dust Storm of 2015. Ekologicheskaya Bezopasnost' Pribrezhnoy i Shel'fovoy Zon Morya = Ecological Safety of Coastal and Shelf Zones of Sea, (3), pp. 37-43 (in Russian).

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