Hydrology Research (Jun 2022)

Sub-daily rainfall extremes in the Nordic–Baltic region

  • Jonas Olsson,
  • Anita Verpe Dyrrdal,
  • Erika Médus,
  • Johan Södling,
  • Svetlana Aņiskeviča,
  • Karsten Arnbjerg-Nielsen,
  • Eirik Førland,
  • Viktorija Mačiulytė,
  • Antti Mäkelä,
  • Piia Post,
  • Søren Liedke Thorndahl,
  • Lennart Wern

DOI
https://doi.org/10.2166/nh.2022.119
Journal volume & issue
Vol. 53, no. 6
pp. 807 – 824

Abstract

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Short-duration rainfall extremes are associated with a range of societal hazards, notably pluvial flooding but in addition, e.g., erosion-driven nutrient transport and point-source contamination. Fundamental for all analysis, modelling and risk assessment related to short-duration rainfall extremes is the access to and analysis of high-resolution observations. In this study, sub-daily rainfall observations from 543 meteorological stations in the Nordic–Baltic region were collected, quality-controlled and consistently analyzed in terms of records, return levels, geographical and climatic dependencies, time of occurrence of maxima and trends. The results reflect the highly heterogeneous rainfall climate in the region, with longitudinal and latitudinal gradients as well as local variability, and overall agree with previous national investigations. Trend analyses in Norway and Denmark indicated predominantly positive trends in the period 1980–2018, in line with previous investigations. Gridded data sets with estimated return levels and dates of occurrence (of annual maxima) are provided open access. We encourage further efforts towards international exchange of sub-daily rainfall observations as well as consistent regional analyses in order to attain the best possible knowledge on which rainfall extremes are to be expected in present as well as future climates. HIGHLIGHTS Sub-daily annual rainfall maxima have been collected from national observation networks in the Nordic–Baltic region, including a total of 543 stations.; A consistent regional analysis of records, return levels, geographical and climatic dependencies, time of occurrence of maxima and trends is performed.; Gridded data sets with return levels and time of occurrence are provided open access.;

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