Articles | Volume 25, issue 7
https://doi.org/10.5194/nhess-25-2179-2025
© 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/nhess-25-2179-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Tree fall along railway lines: modelling the impact of wind and other meteorological factors
Rike Lorenz
CORRESPONDING AUTHOR
Institute of Meteorology, Freie Universität Berlin, Carl-Heinrich-Becker-Weg 6–10, 12165 Berlin, Germany
Institute of Meteorology, Freie Universität Berlin, Carl-Heinrich-Becker-Weg 6–10, 12165 Berlin, Germany
Hans Ertel Centre for Weather Research, Berlin, Germany
Barry Gardiner
CORRESPONDING AUTHOR
Faculty of Environment and Natural Resources, University of Freiburg, Tennenbacherstr. 4, 79106 Freiburg, Germany
Institut Européen de la Forêt Cultivée, 69 route d’Arcachon, 33612 Cestas, France
Institute of Meteorology, Freie Universität Berlin, Carl-Heinrich-Becker-Weg 6–10, 12165 Berlin, Germany
Marc Hanewinkel
CORRESPONDING AUTHOR
Faculty of Environment and Natural Resources, University of Freiburg, Tennenbacherstr. 4, 79106 Freiburg, Germany
Benjamin Schmitz
CORRESPONDING AUTHOR
DB InfraGO AG, Adam-Riese-Str. 11–13, Zentrale DB InfraGO, 60327 Frankfurt am Main, Germany
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Cited articles
Akay, A. E. and Taş, İ.: Mapping the risk of winter storm damage using GIS-based fuzzy logic, J. Forest. Res., 31, 729–742, https://doi.org/10.1007/s11676-019-00904-1, 2019.
Albrecht, A., Hanewinkel, M., Bauhus, J. and Kohnle, U.: How does silviculture affect storm damage in forests of south-western Germany? Results from empirical modeling based on long-term observations, Eur. J. Forest Res., 131, 229–247, https://doi.org/10.1007/s10342-010-0432-x, 2012.
Albrecht, A. T., Jung, C., and Schindler, D.: Improving empirical storm damage models by coupling with high-resolution gust speed data, Agr. Forest Meteorol., 268, 23–31, https://doi.org/10.1016/j.agrformet.2018.12.017, 2019.
Ancelin, P., Courbaud, B., and Fourcaud, T.: Development of an individual tree-based mechanical model to predict wind damage within forest stands, Forest Ecol. Manage., 203, 101–121, https://doi.org/10.1016/j.foreco.2004.07.067, 2004.
Bartels, H., Weigl, E., Reich, T., Lang, P., Wagner, A., Kohler, O., and Gerlach, N.: Routineverfahren zur Online-Aneichung der Radarniederschlagsdaten mit Hilfe von automatischen Bodenniederschlagsstationen (Ombrometer), DWD, 111, 2004.
Battaglioli, F., Groenemeijer, P., Tsonevsky, I., and Púčik, T.: Forecasting large hail and lightning using additive logistic regression models and the ECMWF reforecasts, Nat. Hazards Earth Syst. Sci., 23, 3651–3669, https://doi.org/10.5194/nhess-23-3651-2023, 2023.
Bíl, M., Andrášik, R., Nezval, V., and Bílová, M.: Identifying locations along railway networks with the highest tree fall hazard, Appl. Geogr., 87, 45–53, https://doi.org/10.1016/j.apgeog.2017.07.012, 2017.
Bonnesoeur, V., Constant, T., Moulia, B., and Fournier, M.: Forest trees filter chronic wind-signals to acclimate to high winds, New Phytol., 210, 850–860, https://doi.org/10.1111/nph.13836, 2016.
CDS: Dive into this wealth of information about the Earth's past, present and future climate, https://cds.climate.copernicus.eu (last access: October 2023), 2024.
Ciftci, C., Arwade, S. R., Kane, B., and Brena, S. F.: Analysis of the probability of failure for open-grown trees during wind storms, Probabilist. Eng. Mech., 37, 41–50, https://doi.org/10.1016/j.probengmech.2014.04.002, 2014.
Costa, M., Gardiner, B., Locatelli, T., Marchi, L., Marchi, N., and Lingua, E.: Evaluating wind damage vulnerability in the Alps: A new wind risk model parametrisation, Agr. Forest Meteorol., 341, 109660, https://doi.org/10.1016/j.agrformet.2023.109660, 2023.
Csilléry, K., Kunstler, G., Courbaud, B., Allard, D., Lassègues, P., Haslinger, K., and Gardiner, B.: Coupled effects of wind-storms and drought on tree mortality across 115 forest stands from the Western Alps and the Jura mountains, Global Change Biol., 23, 5092–5107, https://doi.org/10.1111/gcb.13773, 2017.
Cusack, S.: A long record of European windstorm losses and its comparison to standard climate indices, Nat. Hazards Earth Syst. Sci., 23, 2841–2856, https://doi.org/10.5194/nhess-23-2841-2023, 2023.
DB (Deutsche Bahn): Geo-Streckennetz, Deutsche Bahn [data set], https://data.deutschebahn.com/dataset/geo-strecke.html (last access: 30 June 2023, no longer available), 2019.
DB: Grün an der Bahn – Wie die DB Bäume und Sträucher an ihren Strecken pflegt, https://www.deutschebahn.com/de/presse/suche_Medienpakete/medienpaket_vegetationsmanagement-6854346 (last access: 25 August 2023), 2023.
Défossez, P., Veylon, G., Yang, M., Bonnefond, J., Garrigou, D., Trichet, P., and Danjon, F.: Impact of soil water content on the overturning resistance of young Pinus Pinaster in sandy soil, Forest Ecol. Manage., 480, 118614, https://doi.org/10.1016/j.foreco.2020.118614, 2021.
Díaz-Yáñez, O., Mola-Yudego, B., and González-Olabarria, J.R.: Modelling damage occurrence by snow and wind in forest ecosystems, Ecol. Modell., 408, 108741, https://doi.org/10.1016/j.ecolmodel.2019.108741, 2019.
Donat, M., Leckebusch, G., Wild, S., and Ulbrich, U.: Benefits and limitations of regional multi-model ensembles for storm loss estimations, Clim. Res., 44, 211–225, https://doi.org/10.3354/cr00891, 2010.
DWD, C. D. C.: Historische stündliche RADOLAN-Raster der Niederschlagshöhe (binär), version V001, DWD [data set], https://opendata.dwd.de/climate_environment/CDC/grids_germany/hourly/radolan/historical/bin/ (last access: 2 October 2023), 2004.
Gardiner, B.: Wind damage to forests and trees: a review with an emphasis on planted and managed forests, J. Forest Res., 26, 248–266, https://doi.org/10.1080/13416979.2021.1940665, 2021.
Gardiner, B. A., Stacey, G. R., Belcher, R. E., and Wo, C. J.: Field and wind tunnel assessments of the implications of respacing and thinning for tree stability, Forestry, 70, 233–252, https://doi.org/10.1093/forestry/70.3.233, 1997.
Gardiner, B., Berry, P., and Moulia, B.: Review: Wind impacts on plant growth, mechanics and damage, Plant Sci., 245, 94–118, https://doi.org/10.1016/j.plantsci.2016.01.006, 2016.
Gardiner, B., Blennow, K., Carnus, J.-M., Fleischer, P., Ingemarson, F., Landmann, G., Lindner, M., Marzano, M., Nicoll, B., Orazio, C., Peyron, J.-L., Schelhaas, M.-J., Schuck, A., and Usbeck, T.: Destructive storms in European forests: past and forthcoming impacts, European Forest Institute, 138, https://doi.org/10.13140/RG.2.1.1420.4006, 2010.
Gardiner, B., Byrne, K., Hale, S., Kamimura, K., Mitchell, S.J., Peltola, H., and Ruel, J.-C.: A review of mechanistic modelling of wind damage risk to forests, Forestry, 81, 447–463, https://doi.org/10.1093/forestry/cpn022, 2008.
Gardiner, B., Lorenz, R., Hanewinkel, M., Schmitz, B., Bott, F., Szymczak, S., Frick, A., and Ulbrich, U.: Predicting the risk of tree fall onto railway lines, Forest Ecol. Manage., 553, 121614, https://doi.org/10.1016/j.foreco.2023.121614, 2024.
Gardiner, B., Schuck, A., Schelhaas, M.-J., Orazio, C., Blennow, K., and Nicoll, B.: Living with Storm Damage to Forests What Science Can Tell Us What Science Can Tell Us. European Forest Institute, Joensuu, Finland, 129, https://doi.org/10.13140/2.1.1730.2400, 2013.
Gazol, A. and Camarero, J. J.: Compound climate events increase tree drought mortality across European forests, Sci. Total Environ., 816, 151604, https://doi.org/10.1016/j.scitotenv.2021.151604, 2022.
Gliksman, D., Averbeck, P., Becker, N., Gardiner, B., Goldberg, V., Grieger, J., Handorf, D., Haustein, K., Karwat, A., Knutzen, F., Lentink, H. S., Lorenz, R., Niermann, D., Pinto, J. G., Queck, R., Ziemann, A., and Franzke, C. L. E.: Review article: A European perspective on wind and storm damage – from the meteorological background to index-based approaches to assess impacts, Nat. Hazards Earth Syst. Sci., 23, 2171–2201, https://doi.org/10.5194/nhess-23-2171-2023, 2023.
Gregow, H.: Impacts of strong winds, heavy snow loads and soil frost conditions on the risks to forests in Northern Europe, Finnish Meteorological Institute Contributions, No. 94, Finnish Meteorological Institute, Helsinki, 44, ISBN 978-951-697-782-2, 2013.
Gregow, H., Laaksonen, A., and Alper, M. E.: Increasing large scale windstorm damage in Western, Central and Northern European forests, 1951–2010, Sci. Rep., 7, 1–7, https://doi.org/10.1038/srep46397, 2017.
Gregow, H., Rantanen, M., Laurila, T. K., and Mäkelä, A.: Review on winds, extratropical cyclones and their impacts in Northern Europe and Finland, Finnish Meteorological Institute Reports, 2020:3, Finnish Meteorological Institute, Helsinki, 36., https://doi.org/10.35614/isbn.9789523361188, 2020.
Gromke, C. and Ruck, B.: On wind forces in the forest-edge region during extreme-gust passages and their implications for damage patterns, Bound.-Lay. Meteorol., 168, 269–288, https://doi.org/10.1007/s10546-018-0348-4, 2018.
Haberstroh, S. and Werner, C.: The role of species interactions for forest resilience to drought, Plant Biol., 24, 1098–1107, https://doi.org/10.1111/plb.13415, 2022.
Hale, S. E., Gardiner, B., Peace, A., Nicoll, B., Taylor, P., and Pizzirani, S.: Comparison and validation of three versions of a forest wind risk model, Environ. Modell. Softw., 68, 27–41, https://doi.org/10.1016/j.envsoft.2015.01.016, 2015.
Hall, J., Muscarella, R., Quebbeman, A., Arellano, G., Thompson, J., Zimmerman, J. K., and Uriarte, M.: Hurricane-induced rainfall is a stronger predictor of tropical forest damage in Puerto Rico than maximum wind speeds, Sci. Rep., 10, 4318, https://doi.org/10.1038/s41598-020-61164-2, 2020.
Hanewinkel, M., Breidenbach, J., Neeff, T., and Kublin, E.: Seventy-seven years of natural disturbances in a mountain forest area – the influence of storm, snow, and insect damage analysed with a long-term time series, Can. J. Forest Res., 38, 2249–2261, https://doi.org/10.1139/x08-070, 2008.
Hanewinkel, M., Kuhn, T., Bugmann, H., Lanz, A., and Brang, P.: Vulnerability of uneven-aged forests to storm damage, Forestry, 87, 525–534, https://doi.org/10.1093/forestry/cpu008, 2014.
Hart, E., Sim, K., Kamimura, K., Meredieu, C., Guyon, D., and Gardiner, B.: Use of machine learning techniques to model wind damage to forests, Agr. Forest Meteorol., 265, 16–29, https://doi.org/10.1016/j.agrformet.2018.10.022, 2019.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G.D., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R.J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteorol. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., Thépaut, J-N.: 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.
Jackson, T. D., Sethi, S., Dellwik, E., Angelou, N., Bunce, A., van Emmerik, T., Duperat, M., Ruel, J.-C., Wellpott, A., Van Bloem, S., Achim, A., Kane, B., Ciruzzi, D. M., Loheide II, S. P., James, K., Burcham, D., Moore, J., Schindler, D., Kolbe, S., Wiegmann, K., Rudnicki, M., Lieffers, V. J., Selker, J., Gougherty, A. V., Newson, T., Koeser, A., Miesbauer, J., Samelson, R., Wagner, J., Ambrose, A. R., Detter, A., Rust, S., Coomes, D., and Gardiner, B.: The motion of trees in the wind: a data synthesis, Biogeosciences, 18, 4059–4072, https://doi.org/10.5194/bg-18-4059-2021, 2021.
Jung, C. and Schindler, D.: Historical Winter Storm Atlas for Germany (GeWiSA), Atmosphere, 10, 387, https://doi.org/10.3390/atmos10070387, 2019.
Jung, C., Schindler, D., Albrecht, A., and Buchholz, A.: The role of highly-resolved gust speed in simulations of storm damage in forests at the landscape scale: A case study from southwest Germany, Atmosphere, 7, 1, https://doi.org/10.3390/atmos7010007, 2016.
Kabir, E., Guikema, S., and Kane, B.: Statistical modeling of tree failures during storms, Reliab. Eng. Syst. Safe., 177, 68–79, https://doi.org/10.1016/j.ress.2018.04.026, 2018.
Kadow, C., Illing, S., Lucio-Eceiza, E. E., Bergemann, M., Ramadoss, M., Sommer, P. S., Kunst, O., Schartner, T., Pankatz, K., Grieger, J., Schuster, M., Richling, A., Thiemann, H., Kirchner, I., Rust, H. W., Ludwig, T., Cubasch, U., and Ulbrich, U.: Introduction to Freva – A Free Evaluation System Framework for Earth System Modeling, J. Open Res. Softw., 9, 13, https://doi.org/10.5334/jors.253, 2021.
Kamimura, K., Gardiner, B., Dupont, S., Guyon, D., and Meredieu, C.: Mechanistic and statistical approaches to predicting wind damage to individual maritime pine (Pinus pinaster) trees in forests, Can. J. For. Res., 46, 88–100, https://doi.org/10.1139/cjfr-2015-0237, 2016.
Kamimura, K., Kitagawa, K., Saito, S., and Mizunaga, H.: Root anchorage of hinoki (Chamaecyparis obtuse (Sieb. Et Zucc.) Endl.) under the combined loading of wind and rapidly supplied water on soil: analyses based on tree-pulling experiments, Eur. J. Forest Res., 131, 219–227, https://doi.org/10.1007/s10342-011-0508-2, 2012.
Kamimura, K., Nanko, K., Matsumoto, A., Ueno, S., Gardiner, J., and Gardiner, B.: Tree dynamic response and survival in a category-5 tropical cyclone: The case of super typhoon Trami, Sci. Adv., 8, 11, https://doi.org/10.1126/sciadv.abm7891, 2022.
Kamo, K.-I., Konoshima, M., and Yoshimoto, A.: Statistical Analysis of Tree-Forest Damage by Snow and Wind:Logistic Regression Model for Tree damage and Cox Regression for Tree Survival, FORMATH, 15, 44–55, https://doi.org/10.15684/formath.15.005, 2016.
Kannenberg, S. A., Schwalm, C. R., and Anderegg, W. R. L.: Ghosts of the past: how drought legacy effects shape forest functioning and carbon cycling, Eco. Lett., 23, 891–901, https://doi.org/10.1111/ele.13485, 2020.
Klein, T., Cahanovitc, R., Sprintsin, M., Herr, N., and Schiller, G.: A nation-wide analysis of tree mortality under climate change: Forest loss and its causes in Israel 1948–2017, Forest Ecol. Manage., 432, 840-849, https://doi.org/10.1016/j.foreco.2018.10.020, 2019.
Koks, E. E., Rozenberg, J., Zorn, C., Tariverdi, M., Vousdoukas, M., Fraser, S. A., Hall, J. W., and Hallegatte, S.: A global multi-hazard risk analysis of road and railway infrastructure assets, Nat. Commun., 10, 11, https://doi.org/10.1038/s41467-019-10442-3, 2019.
Kouki, K., Luojus, K., and Riihelä, A.: Evaluation of snow cover properties in ERA5 and ERA5-Land with several satellite-based datasets in the Northern Hemisphere in spring 1982–2018, The Cryosphere, 17, 5007–5026, https://doi.org/10.5194/tc-17-5007-2023, 2023.
Kučera, M. and Dobesova, Z.: Analysis of the Degree of Threat to Railway Infrastructure by Falling Tree Vegetation, ISPRS Int. J. Geo-Info., 10, 292, https://doi.org/10.3390/ijgi10050292, 2021.
Lehtonen, I., Venäläinen, A., Kämäräinen, M., Asikainen, A., Laitila, J., Anttila, P., and Peltola, H.: Projected decrease in wintertime bearing capacity on different forest and soil types in Finland under a warming climate, Hydrol. Earth Syst. Sci., 23, 1611–1631, https://doi.org/10.5194/hess-23-1611-2019, 2019.
MacKenzie, D. I., Nichols, J. D., Royle, J. A., Pollock, K. H., Bailey, L. L. and Hines, J. E.: Chapter 3 – Fundamental Principals of Statistical Inference. in: Occupancy Estimation and Modeling (Second Edition), editd by: MacKenzie, D. I., Nichols, J. D., Royle, J. A., Pollock, K. H., Bailey, L. L., and Hines, J. E., Elsevier, 71–111 pp., https://doi.org/10.1016/b978-0-12-407197-1.00004-1, 2018.
Maringer, J., Stelzer, A.-S., Paul, C., and Albrecht, A.T.: Ninety-five years of observed disturbance-based tree mortality modeled with climate-sensitive accelerated failure time models, Eur. J. Forest Res., 140, 255–272, https://doi.org/10.1007/s10342-020-01328-x, 2020.
Mayer, P., Brang, P., Dobbertin, M., Hallenbarter, D., Renaud, J.-P., Walthert, L., and Zimmermann, S.: Forest storm damage is more frequent on acidic soils, Ann. For. Sci., 62, 303–311, https://doi.org/10.1051/forest:2005025, 2005.
McCullagh, P. and Nelder, J. A.: Generalized Linear Models, Chapman and Hall, London, 532, https://doi.org/10.1007/978-1-4899-3242-6, ISBN 9781489932426, 1989.
Meßenzehl, K.: Das Naturgefahrenmanagement der DB Netz AG, Deine Bahn, 10/2019, 16–22, 2019.
Minola, L., Zhang, F., Azorin-Molina, C., Pirooz, A. A. S., Flay, R. G. J., Hersbach, H., and Chen, D.: Near-surface mean and gust wind speeds in ERA5 across Sweden: towards an improved gust parametrization, Clim. Dynam., 55, 887–907, https://doi.org/10.1007/s00382-020-05302-6, 2020.
Mitchell, S. J.: Wind as a natural disturbance agent in forests: a synthesis, Forestry, 86, 147–157, https://doi.org/10.1093/forestry/cps058, 2013.
Mohr, S., Kunz, M., Richter, A., and Ruck, B.: Statistical characteristics of convective wind gusts in Germany, Nat. Hazards Earth Syst. Sci., 17, 957–969, https://doi.org/10.5194/nhess-17-957-2017, 2017.
Molina, M. O., Gutiérrez, C., and Sánchez, E.: Comparison of ERA surface wind speed climatologies over Europe with observations from the HadISD dataset, Int. J. Climatol., 41, 4864–4878, https://doi.org/10.1002/joc.7103, 2021.
Morimoto, J., Nakagawa, K., Takano, K. T., Aiba, M., Oguro, M., Furukawa, Y., Mishima, Y., Ogawa, K., Ito, R., Takemi, T., Nakamura, F., and Peterson, C. J.: Comparison of vulnerability to catastrophic wind between Abies plantation forests and natural mixed forests in northern Japan, Forestry: An Int. J. Forest Res., 92, 436–443, https://doi.org/10.1093/forestry/cpy045, 2019.
Neild, S. and Wood, C.: Estimating stem and root-anchorage flexibility in trees, Tree Physiol., 19, 141–151, 1999.
Pardowitz, T., Osinski, R., Kruschke, T., and Ulbrich, U.: An analysis of uncertainties and skill in forecasts of winter storm losses, Nat. Hazards Earth Syst. Sci., 16, 2391–2402, https://doi.org/10.5194/nhess-16-2391-2016, 2016.
Pasztor, F., Matulla, C., Zuvela-Aloise, M., Rammer, W., and Lexer, M. J.: Developing predictive models of wind damage in Austrian forests, Ann. Forest Sci., 72, 289–301, https://doi.org/10.1007/s13595-014-0386-0, 2015.
Peltola, H., Kellomäki, S., Hassinen, A., and Granander, M.: Mechanical stability of Scots pine, Norway spruce and birch: an analysis of tree-pulling experiments in Finland, Forest Ecol. Manage., 135, 143–153, https://doi.org/10.1016/s0378-1127(00)00306-6, 2000.
Prahl, B. F., Rybski, D., Burghoff, O., and Kropp, J. P.: Comparison of storm damage functions and their performance, Nat. Hazards Earth Syst. Sci., 15, 769–788, https://doi.org/10.5194/nhess-15-769-2015, 2015.
Primo, C.: Wind gust warning verification, Adv. Sci. Res., 13, 113–120, https://doi.org/10.5194/asr-13-113-2016, 2016.
Quine, C. P., Gardiner, B. A., and Moore, J.: Wind disturbance in forests: The process of wind created gaps, tree overturning, and stem breakage, in: Plant Disturbance Ecology, editd by: Johnson, E. A. and Miyanishi, K., Elsevier, 117–184, https://doi.org/10.1016/b978-0-12-818813-2.00004-6, 2021.
Schelhaas, M., Kramer, K., Peltola, H., van der Werf, D., and Wijdeven, S.: Introducing tree interactions in wind damage simulation, Ecol. Modell., 207, 197–209, https://doi.org/10.1016/j.ecolmodel.2007.04.025, 2007.
Schindler, D., Grebhan, K., Albrecht, A., and Schönborn, J.: Modelling the wind damage probability in forests in Southwestern Germany for the 1999 winter storm `Lothar', Int. J. Biometeorol., 53, 543–554, https://doi.org/10.1007/s00484-009-0242-3, 2009.
Schindler, D. and Kolbe, S.: Assessment of the Response of a Scots Pine Tree to Effective Wind Loading, Forests, 11, 145, https://doi.org/10.3390/f11020145, 2020.
Schmidt, M., Hanewinkel, M., Kändler, G., Kublin, E., and Kohnle, U.: An inventory-based approach for modeling single-tree storm damage – experiences with the winter storm of 1999 in southwestern Germany, Can. J. For. Res., 40, 1636–1652, https://doi.org/10.1139/X10-099, 2010.
Schulz, B. and Lerch, S.: Machine Learning Methods for Postprocessing Ensemble Forecasts of Wind Gusts: A Systematic Comparison, Mon. Weather Rev., 150, 235–257, https://doi.org/10.1175/mwr-d-21-0150.1, 2022.
Schulzweida, U.: CDO User Guide, 251, Zenodo, https://doi.org/10.5281/ZENODO.10020800, 2023.
Seidl, R., Rammer, W., and Blennow, K.: Simulating wind disturbance impacts on forest landscapes: Tree-level heterogeneity matters, Environ. Modell. Softw., 51, 1–11, https://doi.org/10.1016/j.envsoft.2013.09.018, 2014.
Sheather, S.: A Modern Approach to Regression with R. Springer Science + Business Media, LLC, New York, 397, https://doi.org/10.1007/978-0-387-09608-7, ISBN 9780387096087, 2009.
Singh, V. V., Naseer, A., Mogilicherla, K., Trubin, A., Zabihi, K., Roy, A., and Erbilgin, N.: Understanding bark beetle outbreaks: exploring the impact of changing temperature regimes, droughts, forest structure, and prospects for future forest pest management, Rev. Environ. Sci. Biotechnol., 23, 257–290, https://doi.org/10.1007/s11157-024-09679-w, 2024.
Stadelmann, G., Bugmann, H., Wermelinger, B., and Bigler, C.: Spatial interactions between storm damage and subsequent infestations by the European spruce bark beetle, Forest Ecol. Manage., 318, 167–174, https://doi.org/10.1016/j.foreco.2014.01.022, 2014.
Sterken, P.: On trees and wind turbines, Arboricul. J., 43, 235–248, https://doi.org/10.1080/03071375.2021.1903239, 2021.
Sulik, S. and Kejna, M.: The origin and course of severe thunderstorm outbreaks in Poland on 10 and 11 August, 2017, B. Geography. Phys. Geogr. Ser., 18, 25–39, https://doi.org/10.2478/bgeo-2020-0003, 2020.
Suvanto, S., Henttonen, H. M., Nöjd, P., and Mäkinen, H.: Forest susceptibility to storm damage is affected by similar factors regardless of storm type: Comparison of thunder storms and autumn extra-tropical cyclones in Finland, Forest Ecol. Manage., 381, 17–28, https://doi.org/10.1016/j.foreco.2016.09.005, 2016.
Szymczak, S., Bott, F., Babeck, P., Frick, A., Stöckigt, B., and Wagner, K.: Estimating the hazard of tree fall along railway lines: a new GIS tool, Nat. Hazards, 112, 2237–2258, https://doi.org/10.1007/s11069-022-05263-5, 2022.
Temperli, C., Bugmann, H., and Elkin, C.: Cross-scale interactions among bark beetles, climate change, and wind disturbances: a landscape modeling approach, Ecol. Monogr., 83, 383–402, https://doi.org/10.1890/12-1503.1, 2013.
Tervo, R., Láng, I., Jung, A., and Mäkelä, A.: Predicting power outages caused by extratropical storms, Nat. Hazards Earth Syst. Sci., 21, 607–627, https://doi.org/10.5194/nhess-21-607-2021, 2021.
Valta, H., Lehtonen, I., Laurila, T. K., Venäläinen, A., Laapas, M., and Gregow, H.: Communicating the amount of windstorm induced forest damage by the maximum wind gust speed in Finland, Adv. Sci. Res., 16, 31–37, https://doi.org/10.5194/asr-16-31-2019, 2019.
Venäläinen, A., Lehtonen, I., Laapas, M., Ruosteenoja, K., Tikkanen, O., Viiri, H., Ikonen, V., and Peltola, H.: Climate change induces multiple risks to boreal forests and forestry in Finland: A literature review, Global Change Biol., 26, 4178–4196, https://doi.org/10.1111/gcb.15183, 2020.
Wilks, D. S.: Statistical methods in the atmospheric sciences, Elsevier, Oxford, 704, https://doi.org/10.1016/C2017-0-03921-6, ISBN 9780123850225, 2011.
Wohlgemuth, T., Hanewinkel, M., and Seidl, R.: Wind Disturbances. in: Disturbance Ecology, editd by: Wohlgemuth, T., Jentsch, A., and Seidl, R., Springer International Publishing, 173–194, https://doi.org/10.1007/978-3-030-98756-5_8, 2022.
Zeppenfeld, T., Jung, C., Schindler, D., Sennhenn-Reulen, H., Ipsen, M. J., and Schmidt, M.: Winter storm risk assessment in forests with high resolution gust speed data, Eur. J. Forest Res., 142, 1045–1058, https://doi.org/10.1007/s10342-023-01575-8, 2023.
Zubkov, P., Gardiner, B., Nygaard, B. E., Guttu, S., Solberg, S., and Eid, T.: Predicting snow damage in conifer forests using a mechanistic snow damage model and high-resolution snow accumulation data, Scan. J. Forest Res., 39, 59–75, https://doi.org/10.1080/02827581.2023.2289660, 2023.
Zweifel, R., Etzold, S., Sterck, F., Gessler, A., Anfodillo, T., Mencuccini, M., von Arx, G., Lazzarin, M., Haeni, M., Feichtinger, L., Meusburger, K., Knuesel, S., Walthert, L., Salmon, Y., Bose, A.K., Schoenbeck, L., Hug, C., Girardi, N. D., Giuggiola, A., Schaub, M., and Rigling, A.: Determinants of legacy effects in pine trees – implications from an irrigation-stop experiment, New Phytol., 227, 1081–1096, https://doi.org/10.1111/nph.16582, 2020.
Short summary
Tree fall events have an impact on forests and transport systems. Our study explored tree fall in relation to wind and other weather conditions. We used tree fall data along railway lines and ERA5 and radar meteorological data to build a logistic regression model. We found that high and prolonged wind speeds, wet conditions, and high air density increase tree fall risk. These factors might change in the changing climate, which in return will change risks for trees, forests and transport.
Tree fall events have an impact on forests and transport systems. Our study explored tree fall...
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