  This paper presents applications of the peaks-over threshold methodology for
both the univariate and the recently introduced bivariate case, combined with a
novel bootstrap approach. We compare the proposed bootstrap methods to the more
traditional profile likelihood.
  We have investigated 63 years of the European Climate Assessment daily
precipitation data for five Hungarian grid points, first separately for the
summer and winter months, then aiming at the detection of possible changes by
investigating 20 years moving windows. We show that significant changes can be
observed both in the univariate and the bivariate cases, the most recent period
being the most dangerous, as the return levels here are the highest. We
illustrate these effects by bivariate coverage regions.
