Precipitation Extremes and Their Synoptic Models in the Northwest European Sector of the Arctic during the Cold Season

Authors:
Open Access
Publisher website
Google Scholar
Abstract
Precipitation extrema over the Barents Sea and the neighbouring locations in Europe were analysed using data obtained from station observations and a highly detailed ERA5 re-analysis dataset. These data did not always spatially coincide (on average, coincidence was ~50%). Daily amounts of precipitation were typically higher in the observation data, although there may be a reverse picture. The analysis revealed that at several stations and in many of the ERA5 grids, the set of precipitation extremes exists as a mixture of two different subsets. The cumulative distribution functions (CDF) of the largest population in the context of both the re-analysis and observational data are well described by Pareto’s law. However, very rare cases exist in which the values deviate and exceed this base distribution value in regions possessing large values. These super-large anomalies do not obey the statistical law common to all other extremes. However, this does not mean that the extremes can be arbitrarily large. They do not exceed the marginal values that are typical for this type of climate and season. The analysis confirms that extreme precipitation in the western sector of the Arctic is caused by the penetration of moist air masses from the Atlantic in the circulation systems of intense cyclones. At certain times, mesoscale convective systems are embedded in atmospheric fronts and can significantly contribute to the formation of precipitation. Intensification of such cyclones corresponding to global warming should lead to a transformation of typical CDF, as modern outliers will become regular components of the Pareto law. This change in the statistics of extreme events reflects the nonstationarity of the climate state. The influence of polar lows on the formation of large daily precipitation amounts is not felt.
Funding Information
  • Russian Ministry of Science and Higher Education (075-15-2021-574, FMGE-2019-0009, 19-17-00242)
  • Institute of Geography, Russian Academy of Sciences (075-15-2021-574, FMGE-2019-0009, 19-17-00242)
  • Russian Science Foundation (RSF) (075-15-2021-574, FMGE-2019-0009, 19-17-00242)

This publication has 22 references indexed in Scilit: