Effects of sample size on estimation of rainfall extremes at high temperatures

High precipitation quantiles tend to rise with temperature, following the so-called Clausius–Clapeyron (CC) scaling. It is often reported that the CC-scaling relation breaks down and even reverts for very high temperatures. In our study, we investigate this reversal using observational climate data...

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Bibliographic Details
Published in:Natural hazards and earth system sciences 2017-09, Vol.17 (9), p.1623-1629
Main Authors: Boessenkool, Berry, Bürger, Gerd, Heistermann, Maik
Format: Article
Language:English
Subjects:
Climatic data
Environmental aspects
Environmental impact analysis
Extreme high temperatures
Extreme weather
High temperature
Humidity
Methods
Precipitation
Quantiles
Rain
Rainfall
Rainfall frequency
Rainfall intensity
Sample size
Scaling
Statistical analysis
Statistical methods
Temperature
Temperature effects
Time series
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Summary:High precipitation quantiles tend to rise with temperature, following the so-called Clausius–Clapeyron (CC) scaling. It is often reported that the CC-scaling relation breaks down and even reverts for very high temperatures. In our study, we investigate this reversal using observational climate data from 142 stations across Germany. One of the suggested meteorological explanations for the breakdown is limited moisture supply. Here we argue that, instead, it could simply originate from undersampling. As rainfall frequency generally decreases with higher temperatures, rainfall intensities as dictated by CC scaling are less likely to be recorded than for moderate temperatures. Empirical quantiles are conventionally estimated from order statistics via various forms of plotting position formulas. They have in common that their largest representable return period is given by the sample size. In small samples, high quantiles are underestimated accordingly. The small-sample effect is weaker, or disappears completely, when using parametric quantile estimates from a generalized Pareto distribution (GPD) fitted with L moments. For those, we obtain quantiles of rainfall intensities that continue to rise with temperature.
ISSN:1684-9981
1561-8633
1684-9981
DOI:10.5194/nhess-17-1623-2017