气候变化研究中关于温度极端指数的处理方法Using a Monte Carlo simulation, it is demonstrated that percentile-based temperature indices computed
for climate change detection and monitoring may contain artificial discontinuities at the beginning and end
of the period that is used for calculating the percentiles (base period). This would make these exceedance
frequency time series unsuitable for monitoring and detecting climate change. The problem occurs because
the threshold calculated in the base period is affected by sampling error. On average, this error leads to
overestimated exceedance rates outside the base period. A bootstrap resampling procedure is proposed to
estimate exceedance frequencies during the base period. The procedure effectively removes the inhomogeneity.
