gesjGEOGRAPHY, ENVIRONMENT, SUSTAINABILITYGEOGRAPHY, ENVIRONMENT, SUSTAINABILITY2071-93882542-1565Russian Geographical Society10.24057/2071-9388-2025-3590gesj-3992Research ArticleRESEARCH PAPERСтатьиAssociation Of Spatial And Temporal Windthrow Distribution With Convective Parameters And Lightning Density In RussiaShikhovAndrey N.

15 Bukireva street, Perm, 614068; 3 Pyzhevsky per., Moscow, 119017

shikhovan@gmail.comYarinichYulia I.

3 Pyzhevsky per., Moscow, 119017; 1 Lenniskie Gory, Moscow, 119991

ChernokulskyAlexander V.

3 Pyzhevsky per., Moscow, 119017; 29 Staromonetniy per., Moscow, 119017

Perm State University; A.M. Obukhov Institute of Atmospheric PhysicsRussian FederationA.M. Obukhov Institute of Atmospheric Physics; Faculty of Geography, Lomonosov Moscow State University; Research Computing Center, Lomonosov Moscow State UniversityRussian FederationA.M. Obukhov Institute of Atmospheric Physics; Institute of Geography RASRussian Federation2025080420251817588Copyright © Shikhov A.N., Yarinich Y.I., Chernokulsky A.V., 20252025Shikhov A.N., Yarinich Y.I., Chernokulsky A.V.Shikhov A.N., Yarinich Y.I., Chernokulsky A.V.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://ges.rgo.ru/jour/article/view/3992

Windthrow is one of the major causes of forest loss in most forest types, depending on the frequency and intensity of severe winds and forest vulnerability. This study focuses on analyzing of the association of the spatio-temporal distribution of windthrow with the atmospheric convective parameters and lightning activity in the Russian forest zone for the period 2001-2020. The windthrow data include 1816 events that are associated with tornadoes and non-tornadic convective windstorms and are obtained from the previously developed satellite-derived database. Convective parameters are calculated based on the ERA5 reanalysis, while the Worldwide Lightning Location Network (WWLLN) is used for lightning data. It is found that both the spatial distribution and the interannual variability of windthrow events are significantly correlated with the corresponding variability of convective parameters, especially with the significant tornado parameter (STP), both in the European Russia (ER) and in Siberia. The spatial correlation between windthrow events and lightning density is also significant, with a stronger relationship in the ER than in Siberia. For inter-annual variability, it is also found a strong relationship between the number of days with supercritical STP values and the total windthrow area per season. Our results highlight STP and lightning density as informative predictors that can be used as characteristics of windthrow in the Russian forests and for further estimation of associated risks, which is important for sustainable forest management.

windthrownon-tornadic convective windstormstornadoesERA-5 reanalysisconvective indiceslightning densityThis study has been funded by the Russian Scientific Foundation and Perm Krai, Project Number 24-27-20111ReferencesBartalev S.A., Egorov V.A., Zharko V.O., Lupyan E.A., Plotnikov D.E., Khvostikov S.A., Shabanov N.V. (2016). Satellite-based mapping of the vegetation cover of Russia Moscow, Space Research Institute of RAS, 208 p. (in Russian).Bartalev S.A., Egorov V.A., Zharko V.O., Lupyan E.A., Plotnikov D.E., Khvostikov S.A., Shabanov N.V. (2016). Satellite-based mapping of the vegetation cover of Russia Moscow, Space Research Institute of RAS, 208 p. (in Russian).Baumann M., Ozdogan M., Wolter P.T., Krylov A.M., Vladimirova N.A., and Radeloff V.C. (2014). Landsat remote sensing of forest windfall disturbance. Remote Sensing of Environment, 143, 171-179, DOI: 10.1016/j.rse.2013.12.020.Baumann M., Ozdogan M., Wolter P.T., Krylov A.M., Vladimirova N.A., and Radeloff V.C. (2014). Landsat remote sensing of forest windfall disturbance. Remote Sensing of Environment, 143, 171-179, DOI: 10.1016/j.rse.2013.12.020.Brooks H.E., Doswell III C.A., Zhang X., Chernokulsky A., Tochimoto E., Hanstrum B., Nascimento E., Sills D., Antonescu B., and Barrett B. (2019). A century of progress in severe convective storm research and forecasting. in: A Century of Progress in Atmospheric and Related Sciences: Celebrating the American Meteorological Society Centennial. AMS, Meteorol. Monographs, Chapter 18. P.18.1–18.41.Brooks H.E., Doswell III C.A., Zhang X., Chernokulsky A., Tochimoto E., Hanstrum B., Nascimento E., Sills D., Antonescu B., and Barrett B. (2019). A century of progress in severe convective storm research and forecasting. in: A Century of Progress in Atmospheric and Related Sciences: Celebrating the American Meteorological Society Centennial. AMS, Meteorol. Monographs, Chapter 18. P.18.1–18.41.Chernokulsky A.V., Eliseev A.V., Kozlov F.A., Korshunova N.N., Kurgansky M.V., Mokhov I.I., Semenov V.A., Shvets’ N.V., Shikhov A.N., and Yarinich Y.I. (2022). Atmospheric severe convective events in Russia: Changes observed from different data. Russian Meteorology and Hydrology, 47(5), 343-354, DOI: 10.3103/S106837392205003X.Chernokulsky A.V., Eliseev A.V., Kozlov F.A., Korshunova N.N., Kurgansky M.V., Mokhov I.I., Semenov V.A., Shvets’ N.V., Shikhov A.N., and Yarinich Y.I. (2022). Atmospheric severe convective events in Russia: Changes observed from different data. Russian Meteorology and Hydrology, 47(5), 343-354, DOI: 10.3103/S106837392205003X.Chernokulsky A.V., Kurgansky M.V., Mokhov I.I., Shikhov A.N., Azhigov I.O., Selezneva E.V., Zakharchenko D.I., Antonescu B., and Kuhne T. (2021). Tornadoes in the Russian Regions. Russian Meteorology and Hydrology, 46(2), 69-82. DOI: 10.3103/S1068373921020023.Chernokulsky A.V., Kurgansky M.V., Mokhov I.I., Shikhov A.N., Azhigov I.O., Selezneva E.V., Zakharchenko D.I., Antonescu B., and Kuhne T. (2021). Tornadoes in the Russian Regions. Russian Meteorology and Hydrology, 46(2), 69-82. DOI: 10.3103/S1068373921020023.Chernokulsky A., Shikhov A., Bykov A., Kalinin N., Kurgansky M., Sherstyukov B., and Yarinich Y. (2022). Diagnosis and modelling of two destructive derecho events in European Russia in the summer of 2010. Atmospheric Research, 267, 105928, DOI: 10.1016/j.atmosres.2021.105928.Chernokulsky A., Shikhov A., Bykov A., Kalinin N., Kurgansky M., Sherstyukov B., and Yarinich Y. (2022). Diagnosis and modelling of two destructive derecho events in European Russia in the summer of 2010. Atmospheric Research, 267, 105928, DOI: 10.1016/j.atmosres.2021.105928.Chernokulsky A., Shikhov A., Yarinich Yu., and Sprygin A. (2023). An Empirical Relationship among Characteristics of Severe Convective Storms, Their Cloud-Top Properties and Environmental Parameters in Northern Eurasia. Atmosphere, 14(1), 174, DOI: 10.3390/atmos14010174.Chernokulsky A., Shikhov A., Yarinich Yu., and Sprygin A. (2023). An Empirical Relationship among Characteristics of Severe Convective Storms, Their Cloud-Top Properties and Environmental Parameters in Northern Eurasia. Atmosphere, 14(1), 174, DOI: 10.3390/atmos14010174.Christian H.J. (2003). Global frequency and distribution of lightning as observed from space by the Optical Transient Detector. Journal of Geophysical Research, 108, 4005, DOI: 10.1029/2002jd002347.Christian H.J. (2003). Global frequency and distribution of lightning as observed from space by the Optical Transient Detector. Journal of Geophysical Research, 108, 4005, DOI: 10.1029/2002jd002347.Diffenbaugh N.S., Scherer M., and Trapp R.J. (2013). Robust increases in severe thunderstorm environments in response to greenhouse forcing. Proceedings of the National Academy of Sciences of the USA, 110, 16361–16366, DOI: 10.1073/pnas.1307758110.Diffenbaugh N.S., Scherer M., and Trapp R.J. (2013). Robust increases in severe thunderstorm environments in response to greenhouse forcing. Proceedings of the National Academy of Sciences of the USA, 110, 16361–16366, DOI: 10.1073/pnas.1307758110.Dobbertin M. (2002). Influence of stand structure, site factors on wind damage comparing the storms Vivian and Lothar. Forest, Snow and Landscape Research, 77(1-2), 187–205.Dobbertin M. (2002). Influence of stand structure, site factors on wind damage comparing the storms Vivian and Lothar. Forest, Snow and Landscape Research, 77(1-2), 187–205.Forzieri G. et al. (2020). A spatially explicit database of wind disturbances in European forests over the period 2000–2018. Earth System Science Data, 12, 257-276, DOI: 10.5194/essd-12-257-2020.Forzieri G. et al. (2020). A spatially explicit database of wind disturbances in European forests over the period 2000–2018. Earth System Science Data, 12, 257-276, DOI: 10.5194/essd-12-257-2020.Gardiner B., Byrne K., Hale S., Kamimura K., Mitchell S. J., Peltola H., and Ruel J-C. (2008). A review of mechanistic modelling of wind damage risk to forests. Forestry, 81(3), 447-463, DOI: 10.1093/forestry/cpn022.Gardiner B., Byrne K., Hale S., Kamimura K., Mitchell S. J., Peltola H., and Ruel J-C. (2008). A review of mechanistic modelling of wind damage risk to forests. Forestry, 81(3), 447-463, DOI: 10.1093/forestry/cpn022.Groenemeijer P., Púčik T., Holzer A.M., Antonescu B., Riemann-Campe K., Schultz D.M., Kühne T., Feuerstein B., Brooks H.E., and Doswell C.A. (2017). Severe convective storms in Europe: Ten years of research and education at the European Severe Storms Laboratory. Bulletin of the American Meteorological Society, 98, 2641-2651. DOI:10.1175/BAMS-D-16-0067.1.Groenemeijer P., Púčik T., Holzer A.M., Antonescu B., Riemann-Campe K., Schultz D.M., Kühne T., Feuerstein B., Brooks H.E., and Doswell C.A. (2017). Severe convective storms in Europe: Ten years of research and education at the European Severe Storms Laboratory. Bulletin of the American Meteorological Society, 98, 2641-2651. DOI:10.1175/BAMS-D-16-0067.1.Hersbach H. et al. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146, 1999-2049, DOI: 10.1002/qj.3803.Hersbach H. et al. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146, 1999-2049, DOI: 10.1002/qj.3803.Holzworth R.H., Brundell J.B., McCarthy M.P., Jacobson A.R., Rodger C.J., and Anderson T.S. (2021). Lightning in the Arctic. Geophysical Research Letters, 48, e2020GL091366, DOI: 10.1029/2020GL091366.Holzworth R.H., Brundell J.B., McCarthy M.P., Jacobson A.R., Rodger C.J., and Anderson T.S. (2021). Lightning in the Arctic. Geophysical Research Letters, 48, e2020GL091366, DOI: 10.1029/2020GL091366.Kaplan J.O. and Lau K.H.-K. (2021). The WGLC global gridded lightning climatology and time series. Earth System Science Data, 13, 3219-3237, DOI: 10.5194/essd-13-3219-2021.Kaplan J.O. and Lau K.H.-K. (2021). The WGLC global gridded lightning climatology and time series. Earth System Science Data, 13, 3219-3237, DOI: 10.5194/essd-13-3219-2021.Laapas M., Lehtonen I., Venäläinen A., and Peltola H. (2019). 10-year return levels of maximum wind speeds under frozen and unfrozen soil forest conditions in Finland. Climate, 7, 62, DOI: 10.3390/cli7050062.Laapas M., Lehtonen I., Venäläinen A., and Peltola H. (2019). 10-year return levels of maximum wind speeds under frozen and unfrozen soil forest conditions in Finland. Climate, 7, 62, DOI: 10.3390/cli7050062.Laapas M., Suvanto S., Peltoniemi M., and Venäläinen A. (2023). Combining interpolated maximum wind gust speed and forest vulnerability for rapid post-storm mapping of potential forest damage areas in Finland, Forestry. International Journal of Forest Research, 96(5), 690-704, DOI: 10.1093/forestry/cpad005.Laapas M., Suvanto S., Peltoniemi M., and Venäläinen A. (2023). Combining interpolated maximum wind gust speed and forest vulnerability for rapid post-storm mapping of potential forest damage areas in Finland, Forestry. International Journal of Forest Research, 96(5), 690-704, DOI: 10.1093/forestry/cpad005.Lepore C., Abernathey R., Henderson N., Allen J.T., and Tippett M.K. (2021). Future global convective environments in CMIP6 models. Earth's Future, 9, e2021EF002277, DOI: 10.1029/2021EF002277.Lepore C., Abernathey R., Henderson N., Allen J.T., and Tippett M.K. (2021). Future global convective environments in CMIP6 models. Earth's Future, 9, e2021EF002277, DOI: 10.1029/2021EF002277.Panferov O., Doering C., Rauch E., Sogachev A., and Ahrends B. (2009). Feedbacks of windthrow for Norway spruce and Scots pine stands under changing climate. Environmental Research Letters, 4, 045002, DOI 10.1088/1748-9326/4/4/045002.Panferov O., Doering C., Rauch E., Sogachev A., and Ahrends B. (2009). Feedbacks of windthrow for Norway spruce and Scots pine stands under changing climate. Environmental Research Letters, 4, 045002, DOI 10.1088/1748-9326/4/4/045002.Panferov O. and Sogachev A. (2008). Influence of gap size on wind damage variables in a forest. Agricultural and Forest Meteorology, 148(11), 1869-1881, DOI: 10.1016/j.agrformet.2008.06.012.Panferov O. and Sogachev A. (2008). Influence of gap size on wind damage variables in a forest. Agricultural and Forest Meteorology, 148(11), 1869-1881, DOI: 10.1016/j.agrformet.2008.06.012.Peltola H., Kellomäki S., Väisänen H., and Ikonen V.P. (1999). A mechanistic model for assessing the risk of wind, snow damage to single trees and stands of Scots pine, Norway spruce and birch. Canadian Journal of Forest Research, 29(6), 647-661, DOI: 10.1139/x99-029.Peltola H., Kellomäki S., Väisänen H., and Ikonen V.P. (1999). A mechanistic model for assessing the risk of wind, snow damage to single trees and stands of Scots pine, Norway spruce and birch. Canadian Journal of Forest Research, 29(6), 647-661, DOI: 10.1139/x99-029.Rasmussen E.N. and Blanchard D.O. (1998). A Baseline Climatology of Sounding-Derived Supercell and Tornado Forecast Parameters. Weather and Forecasting, 13, 1148-1164, DOI: 10.1175/1520-0434(1998)013<1148:ABCOSD>2.0.CO;2.Rasmussen E.N. and Blanchard D.O. (1998). A Baseline Climatology of Sounding-Derived Supercell and Tornado Forecast Parameters. Weather and Forecasting, 13, 1148-1164, DOI: 10.1175/1520-0434(1998)013<1148:ABCOSD>2.0.CO;2.Seidl R. et al. (2011). Modelling natural disturbances in forest ecosystems: A review. Ecological Modelling, 222(4), 903–924. DOI: 10.1016/j.ecolmodel.2010.09.040.Seidl R. et al. (2011). Modelling natural disturbances in forest ecosystems: A review. Ecological Modelling, 222(4), 903–924. DOI: 10.1016/j.ecolmodel.2010.09.040.Senf C. and Seidl R. (2021a). Mapping the forest disturbance regimes of Europe. Nature Sustainability, 4, 63-70, DOI: 10.1038/s41893-020-00609-y.Senf C. and Seidl R. (2021a). Mapping the forest disturbance regimes of Europe. Nature Sustainability, 4, 63-70, DOI: 10.1038/s41893-020-00609-y.Senf C. and Seidl R. (2021b). Storm and fire disturbances in Europe: Distribution and trends. Global Change Biology, 27, 3605-3619, DOI: 10.1111/gcb.15679.Senf C. and Seidl R. (2021b). Storm and fire disturbances in Europe: Distribution and trends. Global Change Biology, 27, 3605-3619, DOI: 10.1111/gcb.15679.Shikhov A.N., Chernokulsky A.V., Azhigov I.O., and Semakina A.V. (2020). A satellite-derived database for stand-replacing windthrow events in boreal forests of European Russia in 1986–2017. Earth System Science Data, 12, 3489-3513, DOI: 10.5194/essd-12-3489-2020.Shikhov A.N., Chernokulsky A.V., Azhigov I.O., and Semakina A.V. (2020). A satellite-derived database for stand-replacing windthrow events in boreal forests of European Russia in 1986–2017. Earth System Science Data, 12, 3489-3513, DOI: 10.5194/essd-12-3489-2020.Shikhov A.N., Chernokulsky A.V., Kalinin N.A., and Pyankov S.V. (2023). Windthrow events in the forest zone of Russia and the environments of their occurrence. Perm, Perm State University, 2023, 284 p. (in Russian).Shikhov A.N., Chernokulsky A.V., Kalinin N.A., and Pyankov S.V. (2023). Windthrow events in the forest zone of Russia and the environments of their occurrence. Perm, Perm State University, 2023, 284 p. (in Russian).Shikhov A., Chernokulsky A., Kalinin N., Bykov A., and Pischalnikova E. (2021). Climatology and Formation Environments of Severe Convective Windstorms and Tornadoes in the Perm Region (Russia) in 1984–2020. Atmosphere, 12(11), 1407, DOI: 10.3390/atmos12111407.Shikhov A., Chernokulsky A., Kalinin N., Bykov A., and Pischalnikova E. (2021). Climatology and Formation Environments of Severe Convective Windstorms and Tornadoes in the Perm Region (Russia) in 1984–2020. Atmosphere, 12(11), 1407, DOI: 10.3390/atmos12111407.Suvanto S., Peltoniemi M., Tuominen S., Strandström M., and Lehtonen A. (2019) High-resolution mapping of forest vulnerability to wind for disturbance-aware forestry. Forest Ecology and Management, 453, 117619, DOI: 10.1016/j.foreco.2019.117619.Suvanto S., Peltoniemi M., Tuominen S., Strandström M., and Lehtonen A. (2019) High-resolution mapping of forest vulnerability to wind for disturbance-aware forestry. Forest Ecology and Management, 453, 117619, DOI: 10.1016/j.foreco.2019.117619.Taszarek M., Brooks H.E., and Czernecki B. (2017). Sounding-derived parameters associated with convective hazards in Europe. Monthly Weather Review, 145, 1511-1528, DOI: 10.1175/MWR-D-16-0384.1.Taszarek M., Brooks H.E., and Czernecki B. (2017). Sounding-derived parameters associated with convective hazards in Europe. Monthly Weather Review, 145, 1511-1528, DOI: 10.1175/MWR-D-16-0384.1.Taszarek M., Groenemeijer P., Allen, J.T., Edwards R., Brooks H.E., Chmielewski V., фтв Enno S.E. (2020a). Severe convective storms across Europe and the United States. Part I: Climatology of lightning, large hail, severe wind, and tornadoes. Journal of Climate, 33, 10239-10261, DOI: 10.1175/JCLI-D-20-0345.1.Taszarek M., Groenemeijer P., Allen, J.T., Edwards R., Brooks H.E., Chmielewski V., фтв Enno S.E. (2020a). Severe convective storms across Europe and the United States. Part I: Climatology of lightning, large hail, severe wind, and tornadoes. Journal of Climate, 33, 10239-10261, DOI: 10.1175/JCLI-D-20-0345.1.Taszarek M., Allen J.T., Púcik T., Hoogewind K.A., and Brooks H.E. (2020b). Severe convective storms across Europe and the United States. Part II: ERA5 environments associated with lightning, large hail, severe wind, and tornadoes. Journal of Climate, 33(24), 10263-10286, DOI: 10.1175/JCLI-D-20-0346.1.Taszarek M., Allen J.T., Púcik T., Hoogewind K.A., and Brooks H.E. (2020b). Severe convective storms across Europe and the United States. Part II: ERA5 environments associated with lightning, large hail, severe wind, and tornadoes. Journal of Climate, 33(24), 10263-10286, DOI: 10.1175/JCLI-D-20-0346.1.Taszarek M., Czernecki B., and Szuster P. (2023). ThundeR − a rawinsonde package for processing convective parameters and visualizing atmospheric profiles, 11th European Conference on Severe Storms, Bucharest, Romania, 8–12 May 2023, ECSS2023-28, https://doi.org/10.5194/ecss2023-28.Taszarek M., Czernecki B., and Szuster P. (2023). ThundeR − a rawinsonde package for processing convective parameters and visualizing atmospheric profiles, 11th European Conference on Severe Storms, Bucharest, Romania, 8–12 May 2023, ECSS2023-28, https://doi.org/10.5194/ecss2023-28.Tarabukina L. and Kozlov V. (2020). Seasonal Variability of Lightning Activity in Yakutia in 2009–2019. Atmosphere, 11, 918. DOI: 10.3390/atmos11090918.Tarabukina L. and Kozlov V. (2020). Seasonal Variability of Lightning Activity in Yakutia in 2009–2019. Atmosphere, 11, 918. DOI: 10.3390/atmos11090918.Thompson R.L., Edwards R., Hart J.A., Elmore K.L., and Markowski P. (2003). Close proximity soundings within supercell environments obtained from the Rapid Update Cycle. Weather and Forecasting, 18, 1243-1261, DOI: 10.1175/1520-0434(2003)018<1243:CPSWSE>2.0.CO;2.Thompson R.L., Edwards R., Hart J.A., Elmore K.L., and Markowski P. (2003). Close proximity soundings within supercell environments obtained from the Rapid Update Cycle. Weather and Forecasting, 18, 1243-1261, DOI: 10.1175/1520-0434(2003)018<1243:CPSWSE>2.0.CO;2.Venäläinen A., Laapas M., Pirinen P., Horttanainen M., Hyvönen R., Lehtonen I., Junila P., Hou M., and Peltola H.M (2017). Estimation of the high-resolution variability of extreme wind speeds for a better management of wind damage risks to forest-based bioeconomy. Earth System Dynamics, 8, 529-545, DOI: 10.5194/esd-8-529-2017.Venäläinen A., Laapas M., Pirinen P., Horttanainen M., Hyvönen R., Lehtonen I., Junila P., Hou M., and Peltola H.M (2017). Estimation of the high-resolution variability of extreme wind speeds for a better management of wind damage risks to forest-based bioeconomy. Earth System Dynamics, 8, 529-545, DOI: 10.5194/esd-8-529-2017.Venäläinen A., Lehtonen I., Laapas M., Ruosteenoja K., Tikkanen O-P., Viiri H., Ikonen V.P, and Peltola H. (2020). Climate change induces multiple risks to boreal forests and forestry in Finland: A literature review. Global Change Biology, 26(8), 4178-4196, DOI: 10.1111/gcb.15183.Venäläinen A., Lehtonen I., Laapas M., Ruosteenoja K., Tikkanen O-P., Viiri H., Ikonen V.P, and Peltola H. (2020). Climate change induces multiple risks to boreal forests and forestry in Finland: A literature review. Global Change Biology, 26(8), 4178-4196, DOI: 10.1111/gcb.15183.

The authors declare that there are no conflicts of interest present.