Abstract. With the ongoing warming of the globe, it is important to quantify changes in the recent
behaviour of extreme events given their impacts on human
health, infrastructure and the natural environment. We use the
sub-daily, multivariate, station-based HadISD dataset to study the
changes in the statistical distributions of temperature, dew point temperature and
wind speeds. Firstly, we use zonally averaged quantities to show that the
lowest temperatures during both day and night are changing more
rapidly than the highest, with the effect more pronounced in the
northern high latitudes. Along with increases in the
zonally averaged mean temperature, the
standard deviation has decreased and the skew increased (increasing
positive tail, decreasing negative tail) over the last
45 years, again with a stronger, more robust signal at higher
latitudes. Changes in the distribution of dew point temperature are
similar to those of temperature. However, changes in the distribution
of wind speeds indicate a more rapid change at higher speeds than at lower. Secondly, to assess in more
detail the spatial distribution of changes as well as changes across seasons and hours of
the day we study each station individually. For stations which show
clear indications of change in the statistical moments, the higher the
statistical moment, generally the more spatially
heterogenous the patterns of change. The standard deviations of
temperatures are increasing in a band stretching from Europe through
China but are decreasing across North America and in the high
northern latitudes, indicating broadening and narrowing of the
distributions, respectively. Large seasonal differences are
found in the change of standard deviations of temperatures over North
America and eastern China. Temperatures in eastern
Asia also have increasing skew in the winter in contrast to the
remainder of the year. The dew point temperatures show smaller
variation in all of the moments but similar patterns to the
temperatures. For wind speeds, apart from the USA, standard
deviations are decreasing across the world, indicating a decrease in
variability. Finally, we use quantile
regression to show changes in the percentiles of
distributions over time. These show an increase
in high quantiles of temperature in eastern Europe during the summer and also in northern
Europe for low quantiles in the winter, also indicating broadening and narrowing of the
distributions, respectively. In North America, the largest changes are at
the lower quantiles in northern latitudes for autumn and winter.
Quantiles of dew point temperature are changing most in the autumn and
winter, especially in the northern parts of Europe.