Simple Nonparametric Techniques for Exploring Changing Probability Distributions of Weather

Christopher A. T. Ferro, Abdelwaheb Hannachi, David B. Stephenson
2005 Journal of Climate  
Anthropogenic influences are expected to cause the probability distribution of weather variables to change in non-trivial ways. This study presents simple non-parametric methods for exploring and comparing differences in pairs of probability distribution functions. The methods are based on quantiles and allow changes in all parts of the probability distribution to be investigated, including the extreme tails. Adjusted quantiles are used to investigate whether changes are simply due to shifts in
more » ... location (e.g. mean) and/or scale (e.g. variance). Sampling uncertainty in the quantile differences is assessed using simultaneous confidence intervals calculated using a bootstrap resampling method that takes account of serial (intraseasonal) dependency. The methods are simple enough to be used on large gridded data sets. They are demonstrated here by exploring the changes between European regional climate model simulations of daily minimum temperature and precipitation totals for winters in 1961-90 and 2071-2100. Projected changes in daily precipitation are generally found to be well described by simple increases in scale, whereas minimum temperature exhibits changes in both location and scale.
doi:10.1175/jcli3518.1 fatcat:4dwdspl2qbhxzeqfjrqmabifkq