In recent years, changes in the distribution function of precipitation intensities, especially at short temporal and spatial resolution, have received increased attention. This research interest is partially due to practical considerations, such as the potential for socioeconomic damage and future risk, but also due to basic research questions concerning the mechanisms leading to possibly temperature-induced intensification. The most reliable way of measuring precipitation intensity in practice may be through ground based rain gauges, which e.g. collect precipitation through a tipping bucket at a very small spatial scale (~ cm) but varying temporal windows (~ minutes to hours), over which precipitation is accumulated. Numerically, precipitation intensity is usually simulated by models of varying spatial resolution (often ~ km) and temporal aggregation (~ minutes to hours). The question may then arise, how to best compare statistics of precipitation, collected at a point with that obtained from a model, where resolution should often be interpreted as a spatio-temporal average. We here use the classical Taylor hypothesis, which relates temporal and spatial scales to map point scales onto appropriate spatial scales, albeit at increased temporal resolution. The mapping is done by using the climate (or weather) model itself, hence assuming that advection is modeled reasonably well. We discuss the utility of the method along with possible practical applications.
08.03.2017
13:30 Uhr