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Research Article

Incompleteness of natural disaster data and its implications on the interpretation of trends

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Received 03 Jan 2024, Accepted 04 Jul 2024, Published online: 18 Jul 2024

References

  • Aki, K. (1965). Maximum likelihood estimate of b in the formula logN = a-bM and its confidence limits. Bulletin of the Earthquake Research Institute, University of Tokyo, 43(2), 237–239. https://doi.org/10.15083/0000033631
  • Alimonti, G., & Mariani, L. (2023). Is the number of global natural disasters increasing? Environmental Hazards, 23(2), 186–202. https://doi.org/10.1080/17477891.2023.2239807
  • Alves, M. I. F., & Neves, C. (2011). Extreme value distributions. International Encyclopedia of Statistical Science, 2, 493–496. https://doi.org/10.1007/978-3-642-04898-2_246
  • Ashton, B., Hill, K., Piazza, A., & Zeitz, R. (1984). Famine in China, 1958-61. Population and Development Review, 10(4), 613. http://doi.org/10.2307/1973284
  • Clauset, A., Shalizi, C. R., & Newman, M. E. J. (2009). Power-law distributions in empirical data. SIAM Review, 51(4), 661–703. https://doi.org/10.1137/070710111
  • Cools, J., Innocenti, D., & O’Brien, S. (2016). Lessons from flood early warning systems. Environmental Science & Policy, 58, 117–122. https://doi.org/10.1016/j.envsci.2016.01.006
  • Corral, Á., & González, Á. (2019). Power law size distributions in geoscience revisited. Earth and Space Science, 6(5), 673–697. https://doi.org/10.1029/2018ea000479
  • Field, C. B., Barros, V., Stocker, T. F., & Dahe, Q. (2012). Managing the risks of extreme events and disasters to advance climate change adaptation: Special report of the intergovernmental panel on climate change. Cambridge University Press. https://doi.org/10.1017/CBO9781139177245.
  • Formetta, G., & Feyen, L. (2019). Empirical evidence of declining global vulnerability to climate-related hazards. Global Environmental Change, 57, 101920. https://doi.org/10.1016/j.gloenvcha.2019.05.004
  • Gall, M., Borden, K. A., & Cutter, S. L. (2009). When do losses count? Bulletin of the American Meteorological Society, 90(6), 799–810. https://doi.org/10.1175/2008bams2721.1
  • Gillett, N. P., Kirchmeier-Young, M., Ribes, A., Shiogama, H., Hegerl, G. C., Knutti, R., Gastineau, G., John, J. G., Li, L., Nazarenko, L., Rosenbloom, N., Seland, Ø., Wu, T., Yukimoto, S., & Ziehn, T.. (2021). Constraining human contributions to observed warming since the pre-industrial period. Nature Climate Change, 11(3), 207–212. https://doi.org/10.1038/s41558-020-00965-9
  • Guha-Sapir, D. (2023). “EM-DAT, CRED/UCLouvain, Brussels, Belgium – Www.emdat.be.” Center for Research on the Epidemiology of Disasters (CRED). www.emdat.be
  • Guha-Sapir, D., Hargitt, D., & Hoyois, P. (2004). Thirty years of natural disasters 1974–2003: The numbers. Presses univ. de Louvain.
  • Gumbel, E. J. (1958). Statistics of extremes. Columbia university press.
  • Gutenberg, B., & Richter, C. F. (1944). Frequency of earthquakes in California. Bulletin of the Seismological Society of America, 34(4), 185–188. https://doi.org/10.1785/BSSA0340040185
  • Hoeppe, P. (2016). Trends in weather related disasters – consequences for insurers and society. Weather and Climate Extremes, 11, 70–79. https://doi.org/10.1016/j.wace.2015.10.002
  • Houser, D., Sands, B., & Xiao, E. (2009). Three parts natural, seven parts man-made: Bayesian analysis of China’s Great Leap Forward demographic disaster. Journal of Economic Behavior & Organization, 69(2), 148–159. http://doi.org/10.1016/j.jebo.2007.09.008
  • IPCC. (2023). Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee & J. Romero (Eds.)]. IPCC, Geneva, Switzerland, 184 pp. https://doi.org/10.59327/IPCC/AR6-9789291691647
  • Jones, R. L., Guha-Sapir, D., & Tubeuf, S. (2022). Human and economic impacts of natural disasters: Can we trust the global data? Scientific Data, 9, 572. https://doi.org/10.1038/s41597-022-01667-x
  • Joshi, N., Roberts, R., Tryggvason, A., & Lund, B. (2024). Earthquake disaster fatality data: Temporally stable power law behavior and effects of underreporting. Seismological Research Letters, 95(4), 2422–2427. https://doi.org/10.1785/0220230342
  • Liu, C., Guo, L., Ye, L., Zhang, S., Zhao, Y., & Song, T. (2018). A review of advances in China’s flash flood early-warning system. Natural Hazards, 92(2), 619–634. https://doi.org/10.1007/s11069-018-3173-7
  • Malamud, B. D., & Turcotte, D. L. (2006). The applicability of power-Law frequency statistics to floods. Journal of Hydrology, 322(1), 168–180. https://doi.org/10.1016/j.jhydrol.2005.02.032
  • Mazhin, S. A., Farrokhi, M., Noroozi, M., Roudini, J., Hosseini, S. A., Motlagh, M. E., Kolivand, P., & Khankeh, H. (2021). Worldwide disaster loss and damage databases: A systematic review. Journal of Education and Health Promotion, 10(1), 329. https://doi.org/10.4103/jehp.jehp_1525_20
  • Mignan, A., & Woessner, J. (2012). Estimating the magnitude of completeness for earthquake catalogs. Community Online Resource for Statistical Seismicity Analysis. https://doi.org/10.5078/CORSSA-00180805. Available at http://www.corssa.org
  • Newman, M. E. J. (2005). Power laws, pareto distributions and zipf’s law. Contemporary Physics, 46(5), 323–351. https://doi.org/10.1080/00107510500052444
  • Nishenko, S. P., & Barton, C. C. (1995). Scaling laws for natural disaster fatalities. US Department of the Interior, US Geological Survey.
  • NOAA. (2023a). New 1991–2020 climate normals. National oceanic and atmospheric administration. https://www.weather.gov/tbw/newnormals
  • NOAA. (2023b). Storm events database. NOAA national centers for environmental information. https://www.ncdc.noaa.gov/stormevents/
  • Onyango, M. A., & Uwase, M. (2017). Humanitarian response to complex emergencies and natural disasters. In S. R. Quah (Ed.), International encyclopedia of public health (2nd ed.), pp. 106–116. Academic Press. https://doi.org/10.1016/B978-0-12-803678-5.00220-4.
  • Perera, D., Agnihotri, J., Seidou, O., & Djalante, R. (2020). Identifying societal challenges in flood early warning systems. International Journal of Disaster Risk Reduction, 51, 101794. https://doi.org/10.1016/j.ijdrr.2020.101794
  • Perera, D., Seidou, O., Agnihotri, J., Rasmy, M., Smakhtin, V., Coulibaly, P., & Mehmood, H. (2019). Flood warly warning systems: A review of benefits, challenges and prospects. UNU-INWEH, Hamilton.
  • Pielke, R. (2021). Economic ‘normalisation’ of disaster losses 1998–2020: A literature review and assessment. Environmental Hazards, 20(2), 93–111. https://doi.org/10.1080/17477891.2020.1800440
  • Tellman, B., Sullivan, J. A., Kuhn, C., Kettner, A. J., Doyle, C. S., Brakenridge, G. R., Erickson, T. A., & Slayback, D. A. (2021). Satellite imaging reveals increased proportion of population exposed to floods. Nature, 596(7870), 80–86. https://doi.org/10.1038/s41586-021-03695-w
  • Thielen-del Pozo, J., Thiemig, V., Pappenberger, F., Revilla-Romero, B., Salamon, P., De Groeve, T., & Hirpa, F.. (2015). The benefit of continental flood early warning systems to reduce the impact of flood disasters; EUR 27533 EN; https://doi.org/10.2788/46941
  • Thomas, V., & López, R. (2015). Global increase in climate-related disasters. Asian Development Bank Economics Working Paper Series No. 466. SSRN Electronic Journal https://doi.org/10.2139/ssrn.2709331 or https://ssrn.com/abstract=2709331
  • UN, United Nations General Assembly. (2016). Report of the open-ended intergovernmental expert working group on indicators and terminology relating to disaster risk reduction.”.
  • Utsu, T. (1965). A method for determining the value of b in a formula Log n = a-bM showing the magnitude-frequency relation for earthquakes. Geophysical Bulletin of the Hokkaido University, 13(February), 99–103. https://doi.org/10.14943/gbhu.13.99
  • Wooster, M. J., Perry, G. L. W., & Zoumas, A. (2012). Fire, drought and El niño relationships on borneo (Southeast Asia) in the Pre-MODIS Era (1980–2000). Biogeosciences (Online), 9(1), 317–340. https://doi.org/10.5194/bg-9-317-2012
  • World Meteorological Organization. (2021). WMO atlas of mortality and economic losses from weather, climate and water extremes (1970–2019). Technical Report.
  • Wyss, M., Speiser, M., & Tolis, S. (2023). Earthquake fatalities and potency. Natural Hazards, 119(2), 1091–1106. https://doi.org/10.1007/s11069-022-05627-x