The informational value of pressure-based single-station proxies for storm activity

Abstract

Air pressure readings and their variations are commonly used to make inferences about storm activity. More precisely, it is assumed that the variation of annual and seasonal statistics of several pressure based proxies describes changes in the past storm climate qualitatively -- an assumption that has yet to be proven. We present a systematic evaluation of the informational content of five pressure-based proxies for storm activity based on single-station observations of air pressure. We examine the number of deep lows, lower percentiles of pressure, the frequency of absolute pressure tendencies above certain thresholds, as well as mean values and high percentiles of absolute pressure tendencies. Such an evaluation needs long and homogeneous records of wind speed, something that is not available from observations. Consequently, we examine the proxies by using datasets of ground level wind speeds and air pressure from the NCEP-driven and spectrally nudged regional model REMO. We gauge the proxies against 95th and 99th percentile time series of ground level wind speeds to quantify the relation between pressure based proxies and storminess. These analyses rely on bootstrap and binomial hypothesis testing. Our analyses of single-station based proxies indicate that the proxies are generally linearly linked to storm activity and that absolute pressure tendencies have the highest informational content. Further, we investigate whether the proxies have the potential of describing storminess over larger areas, also with regard to surface conditions. We find that absolute pressure tendencies have improved informational value when describing storm activity over larger areas, while low pressure readings do not show improved informational value.